Patent Publication Number: US-2023164241-A1

Title: Federated mec framework for automotive services

Description:
This application claims the benefit of priority to U.S. Provisional Pat. Application Serial No. 63/028,783, filed May 22, 2020, which is incorporated herein by reference in its entirety. 
    
    
     BACKGROUND 
     Edge computing, at a general level, refers to the implementation, coordination, and use of computing and resources at locations closer to the “edge” or collection of “edges” of the network. The purpose of this arrangement is to reduce application and network latency, reduce network backhaul traffic and associated energy consumption, improve service capabilities, and improve compliance with security or data privacy requirements (especially as compared to conventional cloud computing). Components that can perform edge computing operations (“edge nodes”) can reside in whatever location needed by the system architecture or ad hoc service (e.g., in high performance compute data center or cloud installation; a designated edge node server, an enterprise server, a roadside server, a telecom central office; or a local or peer at-the-edge device being served consuming edge services). 
     Applications that have been adapted for edge computing include but are not limited to virtualization of traditional network functions (e.g., to operate telecommunications or Internet services) and the introduction of next-generation features and services (e.g., to support 5G network services). Use cases that are projected to extensively utilize edge computing include connected self-driving cars, surveillance, Internet of Things (IoT) device data analytics, video encoding and analytics, location-aware services, device sensing in Smart Cities, among many other networks, and compute-intensive services. 
     Edge computing may, in some scenarios, offer node management services with orchestration and management for applications and coordinated service instances among many types of storage and compute resources. Edge computing is also expected to be closely integrated with existing use cases and technology developed for IoT and Fog/distributed networking configurations, as endpoint devices, clients, and gateways attempt to access network resources and applications at locations closer to the edge of the network. Edge computing can also be used to help enhance communication between user devices or between loT devices. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       In the drawings, which are not necessarily drawn to scale, like numerals may describe similar components in different views. Like numerals having different letter suffixes may represent different instances of similar components. Some embodiments are illustrated by way of example, and not limitation, in the figures of the accompanying drawings in which: 
         FIG.  1    illustrates an overview of an edge cloud configuration for edge computing; 
         FIG.  2    illustrates operational layers among endpoints, an edge cloud, and cloud computing environments; 
         FIG.  3    illustrates an example approach for networking and services in an edge computing system; 
         FIG.  4    illustrates deployment of a virtual edge configuration in an edge computing system operated among multiple edge nodes and multiple tenants; 
         FIG.  5    illustrates various compute arrangements deploying containers in an edge computing system; 
         FIG.  6    illustrates a compute and communication use case involving mobile access to applications in an edge computing system; 
         FIG.  7 A  provides an overview of example components for compute deployed at a compute node in an edge computing system; 
         FIG.  7 B  provides a further overview of example components within a computing device in an edge computing system; 
         FIG.  7 C  illustrates a software distribution platform, according to some embodiments; 
         FIG.  8 A  illustrates a MEC network architecture supporting federation management, according to an example embodiment; 
         FIG.  8 B  illustrates a MEC reference architecture in a Network Function Virtualization (NFV) environment, according to an example embodiment; 
         FIG.  9    illustrates a 3GPP-based 5G system architecture and an example of the mapping of MEC entities to some of the 5G system’s components (namely, AF and UPF), according to an example embodiment; 
         FIG.  10    illustrates a V2X multi-stakeholder scenario which can be used in connection with federated management functions, according to an example embodiment; 
         FIG.  11    illustrates a MEC federation reference scenario for a multi-OEM vehicle use case where both MNOs have MEC platforms with instantiated MEC application Y (“MEC App Y”), according to an example embodiment; 
         FIG.  12    illustrates an exemplary MEC system deployment scenario per ETSI MEC reference architecture including a service layer which can be used in connection with federated management functions, according to an example embodiment; 
         FIG.  13    illustrates a high-level GSMA operator platform, according to an example embodiment; 
         FIG.  14    illustrates hierarchical functional levels based on which a MEC federation can be formed, according to an example embodiment; 
         FIG.  15    illustrates service consumption options within a single MEC system, according to an example embodiment; 
         FIG.  16    illustrates a MEC federation scenario enabling edge service consumption across MEC systems, according to an example embodiment; 
         FIG.  17    illustrates a MEC federation scenario including communication between two MEC platforms belonging to two MEC systems of a MEC federation using an Mpp-fed reference point, according to an example embodiment; 
         FIG.  18    illustrates a MEC federation scenario including communication using an Mfm-fed federation management reference point connecting a MEC system Mobile Edge Orchestrator (MEO) with a federation manager present in each MEC system, according to an example embodiment; 
         FIG.  19    illustrates a MEC federation scenario including communication using an Mfm-fed federation management reference point connecting a MEC system MEO with a common federation manager associated with multiple MEC systems, according to an example embodiment; 
         FIG.  20    is a message sequence chart between multiple federation managers and MEOs in a federated MEC network, according to an example embodiment; 
         FIG.  21    illustrates a MEC federation scenario including communication using a Meo-fed federation management reference point connecting MEOs in a federated MEC network, according to an example embodiment; 
         FIG.  22    illustrates a sequence diagram of signaling for establishing hierarchical inter-MEC system communication for service consumption in a federated MEC network, according to an example embodiment; 
         FIG.  23    illustrates MEC federation reference points in a federated MEC network using a separate federation manager per MEC system, according to an example embodiment; 
         FIG.  24    illustrates MEC federation reference points in a federated MEC network using a single federation manager, according to an example embodiment; and 
         FIG.  25    illustrates a flowchart of a method for implementing a federation management entity in a federated MEC network, according to an example embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     The following embodiments generally relate to a hierarchical signaling framework configured to implement a Multi-Access Edge Computing (MEC) federation constituting of MEC systems which can be operated by different parties (e.g., mobile network operators, or MNOs). The signaling framework refers to the following hierarchical inter-MEC system communication levels: (a) MEC system (i.e., below business level) discovery, including security (authentication/ authorization, system topology hiding/encryption), charging, identity management, and monitoring aspects as an essential prerequisite to forming a MEC federation; (b) MEC platform discovery, either at high granularity (i.e., at MEC platform level) or at low granularity (e.g., at zone, zone group, network function virtualization instance (NFVI) Point-of-Presence, and NFVI node if a needed service is deployed as a VNF); and (d) Information exchange at MEC platform level, for the needs of MEC service consumption, or MEC app-to-app communication. The disclosed techniques may be used to facilitate the establishment of MEC applications and adoption from stakeholders in interoperable scenarios. Such a development will enable and support new business and market opportunities with regards to MEC and cloud computing technology, such as data centers. More particularly, the proposed signaling framework can be used to address the MNOs′ needs to form MEC system federations aiming to enhance service performance (e.g., V2X service continuity in automotive communication scenarios or other communication scenarios). 
     Systems according to embodiments extend the concepts of Named-Data-Networks (NDNs) and Information Centric Networks (ICNs) by providing computing and storage services that can be registered, discovered, and accessed in a way similar to how cached content is accessed in NDNs and ICNs. End nodes can operate in a default mode of operation that can be extended dynamically to take advantage of additional services offered by edge nodes when communicating with peer devices. Besides enhancing end devices capabilities in a P2P exchange, or any additional exchange, such capabilities could incite edge network providers, communication service providers, or cloud service providers, to propose significant compute/caching/storage capabilities at the edges for these end nodes to use them as part of their processing path. Example embodiments can be implemented in systems similar to those shown in any of the systems described below in reference to  FIGS.  1 - 7 C . Additional description of federated MEC frameworks in connection with an edge architecture and edge computing devices is provided hereinbelow in connection with at least  FIG.  8 A  -  FIG.  25   . 
       FIG.  1    is a block diagram  100  showing an overview of a configuration for edge computing, which includes a layer of processing referred to in many of the following examples as an “edge cloud”. As shown, the edge cloud  110  is co-located at an edge location, such as an access point or base station  140 , a local processing hub  150 , or a central office  120 , and thus may include multiple entities, devices, and equipment instances. The edge cloud  110  is located much closer to the endpoint (consumer and producer) data sources  160  (e.g., autonomous vehicles  161 , user equipment  162 , business and industrial equipment  163 , video capture devices  164 , drones  165 , smart cities and building devices  166 , sensors and IoT devices  167 , etc.) than the cloud data center  130 . Compute, memory, and storage resources which are offered at the edges in the edge cloud  110  are critical to providing ultra-low latency response times for services and functions used by the endpoint data sources  160  as well as reduce network backhaul traffic from the edge cloud  110  toward cloud data center  130  thus improving energy consumption and overall network usages among other benefits. 
     Compute, memory, and storage are scarce resources, and generally decrease depending on the edge location (e.g., fewer processing resources being available at consumer endpoint devices, than at a base station, than at a central office). However, the closer that the edge location is to the endpoint (e.g., user equipment (UE)), the more that space and power are often constrained. Thus, edge computing attempts to reduce the number of resources needed for network services, through the distribution of more resources that are located closer to both geographically and in-network access time. In this manner, edge computing attempts to bring the compute resources to the workload data where appropriate, or, bring the workload data to the compute resources. 
     The following describes aspects of an edge cloud architecture that covers multiple potential deployments and addresses restrictions that some network operators or service providers may have in their infrastructures. These include a variety of configurations based on the edge location (because edges at a base station level, for instance, may have more constrained performance and capabilities in a multi-tenant scenario); configurations based on the type of compute, memory, storage, fabric, acceleration, or like resources available to edge locations, tiers of locations, or groups of locations; the service, security, and management and orchestration capabilities; and related objectives to achieve usability and performance of end services. These deployments may accomplish processing in network layers that may be considered as “near edge”, “close edge”, “local edge”, “middle edge”, or “far edge” layers, depending on latency, distance, and timing characteristics. 
     Edge computing is a developing paradigm where computing is performed at or closer to the “edge” of a network, typically through the use of a compute platform (e.g., x86 or ARM compute hardware architecture) implemented at base stations, gateways, network routers, or other devices which are much closer to endpoint devices producing and consuming the data. For example, edge gateway servers may be equipped with pools of memory and storage resources to perform computation in real-time for low latency use cases (e.g., autonomous driving or video surveillance) for connected client devices. Or as an example, base stations may be augmented with compute and acceleration resources to directly process service workloads for the connected user equipment, without further communicating data via backhaul networks. Or as another example, central office network management hardware may be replaced with standardized compute hardware that performs virtualized network functions and offers compute resources for the execution of services and consumer functions for connected devices. Within edge computing networks, there may be scenarios in services in which the compute resource will be “moved” to the data, as well as scenarios in which the data will be “moved” to the compute resource. Or as an example, base station compute, acceleration and network resources can provide services to scale to workload demands on an as-needed basis by activating dormant capacity (subscription, capacity-on-demand) to manage corner cases, emergencies or to provide longevity for deployed resources over a significantly longer implemented lifecycle. 
     In some aspects, the edge cloud  110  and the cloud data center  130  can be configured with federation management functions (FMF)  111 . As used herein, the term “federation management functions” includes one or more of the following functionalities: (1) configure a computing node or a network function virtualization instance as a federation manager, Mobile Edge Orchestrator (MEO), or federation broker to manage multiple federation managers; (2) establish and manage the following hierarchical inter-MEC system communication levels: (a) MEC system (i.e., below business level) discovery, including security (authentication/ authorization, system topology hiding/ encryption), charging, identity management, and monitoring aspects as an essential prerequisite to form a MEC federation; (b) MEC platform discovery, either at high granularity (i.e., at MEC platform level) or at low granularity (e.g., at zone, zone group, network function virtualization instance (NFVI) Point-of-Presence, and NFVI node if a needed service is deployed as a VNF); and (d) Information exchange at MEC platform level, for the needs of MEC service consumption, or for MEC app-to-app communication; (3) configure the use of a federation management reference point Mfm-fed for communications between a federation manager (including a common federation manager for at least two MEC systems) and a MEO; (4) configure the use of a federation management reference points Meo-fed for communications between two MEOs; and (5) configure the use of a federation management reference points Mpp-fed for communications between two MEC platforms. 
     In some embodiments, network management entities within the edge cloud  110  and the cloud data center  130  can be configured with a federation manager (or another management entity) performing the FMF  111  to facilitate exchanges between MEC systems and improve inter- and intra-MEC system communications (e.g., associated with mobile devices in V2X communications) within a federated network environment. In some embodiments, the federated network environment is formed by a federation of multiple MEC systems, and communication between such systems is managed by a federation manager. Each of the MEC systems can include its federation manager, and inter-MEC system communication can be facilitated by a federation broker configured to manage the federation managers of the MEC systems. Additional functionalities and techniques associated with the FMF  111  are discussed in connection with  FIG.  8 A  -  FIG.  25   . 
       FIG.  2    illustrates operational layers among endpoints, an edge cloud, and cloud computing environments. Specifically,  FIG.  2    depicts examples of computational use cases  205 , utilizing the edge cloud  110  among multiple illustrative layers of network computing. The layers begin at an endpoint (devices and things) layer  200 , which accesses the edge cloud  110  to conduct data creation, analysis, and data consumption activities. The edge cloud  110  may span multiple network layers, such as an edge devices layer  210  having gateways, on-premise servers, or network equipment (nodes  215 ) located in physically proximate edge systems; a network access layer  220 , encompassing base stations, radio processing units, network hubs, regional data centers (DC), or local network equipment (equipment  225 ); and any equipment, devices, or nodes located therebetween (in layer  212 , not illustrated in detail). The network communications within the edge cloud  110  and among the various layers may occur via any number of wired or wireless mediums, including via connectivity architectures and technologies not depicted. Any of the communication use cases  205  can be configured based on FMF  111 , which may be performed by a communication node configured as a federation manager (or another federation management entity) within a federated MEC network as discussed in connection with  FIG.  8 A  -  FIG.  25   . 
     Examples of latency, resulting from network communication distance and processing time constraints, may range from less than a millisecond (ms) when among the endpoint layer  200 , under 5 ms at the edge devices layer  210 , to even between 10 to 40 ms when communicating with nodes at the network access layer  220 . Beyond the edge cloud  110  are core network  230  and cloud data center  240  layers, each with increasing latency (e.g., between 50-60 ms at the core network layer  230 , to 100 or more ms at the cloud data center layer). As a result, operations at a core network data center  235  or a cloud data center  245 , with latencies of at least 50 to 100 ms or more, will not be able to accomplish many time-critical functions of the use cases  205 . Each of these latency values are provided for purposes of illustration and contrast; it will be understood that the use of other access network mediums and technologies may further reduce the latencies In some examples, respective portions of the network may be categorized as “close edge”, “local edge”, “near edge”, “middle edge”, or “far edge” layers, relative to a network source and destination. For instance, from the perspective of the core network data center  235  or a cloud data center  245 , a central office or content data network may be considered as being located within a “near edge” layer (“near” to the cloud, having high latency values when communicating with the devices and endpoints of the use cases  205 ), whereas an access point, base station, on-premise server, or network gateway may be considered as located within a “far edge” layer (“far” from the cloud, having low latency values when communicating with the devices and endpoints of the use cases  205 ). It will be understood that other categorizations of a particular network layer as constituting a “close”, “local”, “near”, “middle”, or “far” edge may be based on latency, distance, a number of network hops, or other measurable characteristics, as measured from a source in any of the network layers  200 - 240 . 
     The various use cases  205  may access resources under usage pressure from incoming streams, due to multiple services utilizing the edge cloud. To achieve results with low latency, the services executed within the edge cloud  110  balance varying requirements in terms of (a) Priority (throughput or latency; also referred to as service level objective or SLO) and Quality of Service (QoS) (e.g., traffic for an autonomous car may have higher priority than a temperature sensor in terms of response time requirement; or, a performance sensitivity/bottleneck may exist at a compute/accelerator, memory, storage, or network resource, depending on the application); (b) Reliability and Resiliency (e.g., some input streams need to be acted upon and the traffic routed with mission-critical reliability, whereas some other input streams may tolerate an occasional failure, depending on the application); and (c) Physical constraints (e.g., power, cooling, and form-factor). 
     The end-to-end service view for these use cases involves the concept of a service-flow and is associated with a transaction. The transaction details the overall service requirement for the entity consuming the service, as well as the associated services for the resources, workloads, workflows, and business functional and business level requirements. The services executed with the “terms” described may be managed at each layer in a way to assure real-time, and runtime contractual compliance for the transaction during the lifecycle of the service. When a component in the transaction is missing its agreed to SLA, the system as a whole (components in the transaction) may provide the ability to (1) understand the impact of the SLA violation, and (2) augment other components in the system to resume overall transaction SLA, and (3) implement steps to remediate. 
     Thus, with these variations and service features in mind, edge computing within the edge cloud  110  may provide the ability to serve and respond to multiple applications of the use cases  205  (e.g., object tracking, video surveillance, connected cars, etc.) in real-time or near real-time, and meet ultra-low latency requirements for these multiple applications. These advantages enable a whole new class of applications (Virtual Network Functions (VNFs), Function as a Service (FaaS), Edge as a Service (EaaS), standard processes, etc.), which cannot leverage conventional cloud computing due to latency or other limitations. 
     However, with the advantages of edge computing comes the following caveats. The devices located at the edge are often resource-constrained and therefore there is pressure on the usage of edge resources. Typically, this is addressed through the pooling of memory and storage resources for use by multiple users (tenants) and devices. The edge may be power and cooling constrained and therefore the power usage needs to be accounted for by the applications that are consuming the most power. There may be inherent power-performance tradeoffs in these pooled memory resources, as many of them are likely to use emerging memory technologies, where more power requires greater memory bandwidth. Likewise, improved security of hardware and root of trust trusted functions are also required because edge locations may be unmanned and may even need permission access (e.g., when housed in a third-party location). Such issues are magnified in the edge cloud  110  in a multi-tenant, multi-owner, or multi-access setting, where services and applications are requested by many users, especially as network usage dynamically fluctuates and the composition of the multiple stakeholders, use cases, and services changes. 
     At a more generic level, an edge computing system may be described to encompass any number of deployments at the previously discussed layers operating in the edge cloud  110  (network layers  200 - 240 ), which provide coordination from the client and distributed computing devices. One or more edge gateway nodes, one or more edge aggregation nodes, and one or more core data centers may be distributed across layers of the network to provide an implementation of the edge computing system by or on behalf of a telecommunication service provider (“telco”, or “TSP”), internet-of-things service provider, the cloud service provider (CSP), enterprise entity, or any other number of entities. Various implementations and configurations of the edge computing system may be provided dynamically, such as when orchestrated to meet service objectives. 
     Consistent with the examples provided herein, a client compute node may be embodied as any type of endpoint component, device, appliance, or other thing capable of communicating as a producer or consumer of data. Further, the label “node” or “device” as used in the edge computing system does not necessarily mean that such node or device operates in a client or agent/minion/follower role; rather, any of the nodes or devices in the edge computing system refer to individual entities, nodes, or subsystems which include discrete or connected hardware or software configurations to facilitate or use the edge cloud  110 . 
     As such, the edge cloud  110  is formed from network components and functional features operated by and within edge gateway nodes, edge aggregation nodes, or other edge compute nodes among network layers  210 - 230 . The edge cloud  110  thus may be embodied as any type of network that provides edge computing and/or storage resources which are proximately located to radio access network (RAN) capable endpoint devices (e.g., mobile computing devices, IoT devices, smart devices, etc.), which are discussed herein. In other words, the edge cloud  110  may be envisioned as an “edge” that connects the endpoint devices and traditional network access points that serve as an ingress point into service provider core networks, including mobile carrier networks (e.g., Global System for Mobile Communications (GSM) networks, Long-Term Evolution (LTE) networks, 5G/6G networks, etc.), while also providing storage and/or compute capabilities. Other types and forms of network access (e.g., Wi-Fi, long-range wireless, wired networks including optical networks) may also be utilized in place of or in combination with such 3GPP carrier networks. 
     The network components of the edge cloud  110  may be servers, multi-tenant servers, appliance computing devices, and/or any other type of computing device. For example, the edge cloud  110  may include an appliance computing device that is a self-contained electronic device including a housing, a chassis, a case, or a shell In some circumstances, the housing may be dimensioned for portability such that it can be carried by a human and/or shipped. Example housings may include materials that form one or more exterior surfaces that partially or fully protect the contents of the appliance, in which protection may include weather protection, hazardous environment protection (e.g., EMI, vibration, extreme temperatures), and/or enable submergibility. Example housings may include power circuitry to provide power for stationary and/or portable implementations, such as AC power inputs, DC power inputs, AC/DC or DC/AC converter(s), power regulators, transformers, charging circuitry, batteries, wired inputs and/or wireless power inputs. Example housings and/or surfaces thereof may include or connect to mounting hardware to enable attachment to structures such as buildings, telecommunication structures (e.g., poles, antenna structures, etc.), and/or racks (e.g., server racks, blade mounts, etc). Example housings and/or surfaces thereof may support one or more sensors (e.g., temperature sensors, vibration sensors, light sensors, acoustic sensors, capacitive sensors, proximity sensors, etc.). One or more such sensors may be contained in, carried by, or otherwise embedded in the surface and/or mounted to the surface of the appliance. Example housings and/or surfaces thereof may support mechanical connectivity, such as propulsion hardware (e.g., wheels, propellers, etc.) and/or articulating hardware (e.g., robot arms, pivotable appendages, etc.). In some circumstances, the sensors may include any type of input devices such as user interface hardware (e.g., buttons, switches, dials, sliders, etc.). In some circumstances, example housings include output devices contained in, carried by, embedded therein, and/or attached thereto. Output devices may include displays, touchscreens, lights, LEDs, speakers, I/O ports (e.g., USB), etc. In some circumstances, edge devices are devices presented in the network for a specific purpose (e.g., a traffic light), but may have processing and/or other capacities that may be utilized for other purposes. Such edge devices may be independent of other networked devices and may be provided with a housing having a form factor suitable for its primary purpose; yet be available for other compute tasks that do not interfere with its primary task. Edge devices include Internet of Things devices. The appliance computing device may include hardware and software components to manage local issues such as device temperature, vibration, resource utilization, updates, power issues, physical and network security, etc. Example hardware for implementing an appliance computing device is described in conjunction with  FIGS.  7 A- 7 B . The edge cloud  110  may also include one or more servers and/or one or more multi-tenant servers. Such a server may include an operating system and a virtual computing environment. A virtual computing environment may include a hypervisor managing (spawning, deploying, destroying, etc.) one or more virtual machines, one or more containers, etc. Such virtual computing environments provide an execution environment in which one or more applications and/or other software, code, or scripts may execute while being isolated from one or more other applications, software, code, or scripts. 
     In  FIG.  3   , various client endpoints  310  (in the form of mobile devices, computers, autonomous vehicles, business computing equipment, industrial processing equipment) exchange requests and responses that are specific to the type of endpoint network aggregation. For instance, client endpoints  310  may obtain network access via a wired broadband network, by exchanging requests and responses  322  through an on-premise network system  332 . Some client endpoints  310 , such as mobile computing devices, may obtain network access via a wireless broadband network, by exchanging requests and responses  324  through an access point (e.g., cellular network tower)  334 . Some client endpoints  310 , such as autonomous vehicles may obtain network access for requests and responses  326  via a wireless vehicular network through a street-located network system  336 . However, regardless of the type of network access, the TSP may deploy aggregation points  342 ,  344  within the edge cloud  110  to aggregate traffic and requests. Thus, within the edge cloud  110 , the TSP may deploy various compute and storage resources, such as at edge aggregation nodes  340 , to provide requested content. The edge aggregation nodes  340  and other systems of the edge cloud  110  are connected to a cloud or data center  360 , which uses a backhaul network  350  to fulfill higher-latency requests from a cloud/data center for websites, applications, database servers, etc. Additional or consolidated instances of the edge aggregation nodes  340  and the aggregation points  342 ,  344 , including those deployed on a single server framework, may also be present within the edge cloud  110  or other areas of the TSP infrastructure. In an example embodiment, the edge cloud  110  and the cloud or data center  360  utilize FMF  111  in connection with disclosed techniques. The FMF  111  may be performed by a communication node configured as a federation manager (or another federation management entity) within a federated MEC network as discussed in connection with  FIG.  8 A  -  FIG.  25   . 
       FIG.  4    illustrates deployment and orchestration for virtual edge configurations across an edge computing system operated among multiple edge nodes and multiple tenants. Specifically,  FIG.  4    depicts the coordination of a first edge node  422  and a second edge node  424  in an edge computing system  400 , to fulfill requests and responses for various client endpoints  410  (e.g., smart cities/building systems, mobile devices, computing devices, business/logistics systems, industrial systems, etc.), which access various virtual edge instances. Here, the virtual edge instances  432 ,  434  (or virtual edges) provide edge compute capabilities and processing in an edge cloud, with access to a cloud/data center  440  for higher-latency requests for websites, applications, database servers, etc. However, the edge cloud enables coordination of processing among multiple edge nodes for multiple tenants or entities. 
     In the example of  FIG.  4   , these virtual edge instances include: a first virtual edge  432 , offered to a first tenant (Tenant 1), which offers the first combination of edge storage, computing, and services; and a second virtual edge  434 , offering a second combination of edge storage, computing, and services. The virtual edge instances  432 ,  434  are distributed among the edge nodes  422 ,  424 , and may include scenarios in which a request and response are fulfilled from the same or different edge nodes. The configuration of the edge nodes  422 ,  424  to operate in a distributed yet coordinated fashion occurs based on edge provisioning functions  450 . The functionality of the edge nodes  422 ,  424  to provide coordinated operation for applications and services, among multiple tenants, occurs based on orchestration functions  460 . In an example embodiment, the edge provisioning functions  450  and the orchestration functions  460  can utilize FMF  111  in connection with disclosed techniques. The FMF  111  may be performed by a communication node configured as a federation manager (or another federation management entity) within a federated MEC network as discussed in connection with  FIG.  8 A  -  FIG.  25   . 
     It should be understood that some of the devices in the various client endpoints  410  are multi-tenant devices where Tenant  1  may function within a tenant1 ‘slice’ while Tenant 2 may function within a tenant2 slice (and, in further examples, additional or sub-tenants may exist; and each tenant may even be specifically entitled and transactionally tied to a specific set of features all the way day to specific hardware features). A trusted multi-tenant device may further contain a tenant-specific cryptographic key such that the combination of key and slice may be considered a “root of trust” (RoT) or tenant-specific RoT. An RoT may further be computed dynamically composed using a DICE (Device Identity Composition Engine) architecture such that a single DICE hardware building block may be used to construct layered trusted computing base contexts for layering of device capabilities (such as a Field Programmable Gate Array (FPGA)). The RoT may further be used for a trusted computing context to enable a “fan-out” that is useful for supporting multi-tenancy. Within a multi-tenant environment, the respective edge nodes  422 ,  424  may operate as security feature enforcement points for local resources allocated to multiple tenants per node. Additionally, tenant runtime and application execution (e.g., in virtual edge instances  432 ,  434 ) may serve as an enforcement point for a security feature that creates a virtual edge abstraction of resources spanning potentially multiple physical hosting platforms. Finally, the orchestration functions  460  at an orchestration entity may operate as a security feature enforcement point for marshaling resources along tenant boundaries. 
     Edge computing nodes may partition resources (memory, central processing unit (CPU), graphics processing unit (GPU), interrupt controller, input/output (I/O) controller, memory controller, bus controller, etc.) where respective partitionings may contain an RoT capability and where fan-out and layering according to a DICE model may further be applied to Edge Nodes. Cloud computing nodes consisting of containers, FaaS engines, Servlets, servers, or other computation abstraction may be partitioned according to a DICE layering and fan-out structure to support an RoT context for each. Accordingly, the respective RoTs spanning devices in  410 ,  422 , and  440  may coordinate the establishment of a distributed trusted computing base (DTCB) such that a tenant-specific virtual trusted secure channel linking all elements end to end can be established. 
     Further, it will be understood that a container may have data or workload-specific keys protecting its content from a previous edge node. As part of the migration of a container, a pod controller at a source edge node may obtain a migration key from a target edge node pod controller where the migration key is used to wrap the container-specific keys. When the container/pod is migrated to the target edge node, the unwrapping key is exposed to the pod controller that then decrypts the wrapped keys. The keys may now be used to perform operations on container specific data. The migration functions may be gated by properly attested edge nodes and pod managers (as described above). 
     In further examples, an edge computing system is extended to provide for orchestration of multiple applications through the use of containers (a contained, deployable unit of software that provides code and needed dependencies) in a multi-owner, multi-tenant environment A multi-tenant orchestrator may be used to perform key management, trust anchor management, and other security functions related to the provisioning and lifecycle of the trusted ‘slice’ concept in  FIG.  4   . For instance, an edge computing system may be configured to fulfill requests and responses for various client endpoints from multiple virtual edge instances (and, from a cloud or remote data center). The use of these virtual edge instances may support multiple tenants and multiple applications (e.g., augmented reality (AR)/virtual reality (VR), enterprise applications, content delivery, gaming, compute offload) simultaneously. Further, there may be multiple types of applications within the virtual edge instances (e.g., normal applications; latency-sensitive applications; latency-critical applications; user plane applications; networking applications; etc.). The virtual edge instances may also be spanned across systems of multiple owners at different geographic locations (or, respective computing systems and resources which are co-owned or co-managed by multiple owners). 
     For instance, each edge node  422 ,  424  may implement the use of containers, such as with the use of a container “pod”  426 ,  428  providing a group of one or more containers. In a setting that uses one or more container pods, a pod controller or orchestrator is responsible for local control and orchestration of the containers in the pod. Various edge node resources (e.g., storage, compute, services, depicted with hexagons) provided for the respective edge slices of virtual edges  432 ,  434  are partitioned according to the needs of each container. 
     With the use of container pods, a pod controller oversees the partitioning and allocation of containers and resources. The pod controller receives instructions from an orchestrator (e.g., performing orchestration functions  460 ) that instructs the controller on how best to partition physical resources and for what duration, such as by receiving key performance indicator (KPI) targets based on SLA contracts. The pod controller determines which container requires which resources and for how long to complete the workload and satisfy the SLA. The pod controller also manages container lifecycle operations such as: creating the container, provisioning it with resources and applications, coordinating intermediate results between multiple containers working on a distributed application together, dismantling containers when workload completes, and the like. Additionally, a pod controller may serve a security role that prevents the assignment of resources until the right tenant authenticates or prevents provisioning of data or a workload to a container until an attestation result is satisfied. 
     Also, with the use of container pods, tenant boundaries can still exist but in the context of each pod of containers. If each tenant-specific pod has a tenant-specific pod controller, there will be a shared pod controller that consolidates resource allocation requests to avoid typical resource starvation situations. Further controls may be provided to ensure the attestation and trustworthiness of the pod and pod controller. For instance, the orchestrator  460  may provision an attestation verification policy to local pod controllers that perform attestation verification. If an attestation satisfies a policy for a first tenant pod controller but not a second tenant pod controller, then the second pod could be migrated to a different edge node that does satisfy it. Alternatively, the first pod may be allowed to execute and a different shared pod controller is installed and invoked before the second pod executing. 
       FIG.  5    illustrates additional compute arrangements deploying containers in an edge computing system. As a simplified example, system arrangements  510 ,  520  depict settings in which a pod controller (e.g., container managers  511 ,  521 , and container orchestrator  531 ) is adapted to launch containerized pods, functions and functions-as-a-service instances through execution via compute nodes ( 515  in arrangement  510 ) or to separately execute containerized virtualized network functions through execution via compute nodes ( 523  in arrangement  520 ). This arrangement is adapted for use of multiple tenants in system arrangement  530  (using compute nodes  537 ), where containerized pods (e.g., pods  512 ), functions (e.g., functions  513 , VNFs  522 ,  536 ), and functions-as-a-service instances (e.g., FaaS instance  514 ) are launched within virtual machines (e.g., VMs  534 ,  535  for tenants  532 ,  533 ) specific to respective tenants (aside from the execution of virtualized network functions). This arrangement is further adapted for use in system arrangement  540 , which provides containers  542 ,  543 , or execution of the various functions, applications, and functions on compute nodes  544 , as coordinated by a container-based orchestration system  541 . 
     The system arrangements depicted in  FIG.  5    provide an architecture that treats VMs, Containers, and Functions equally in terms of application composition (and resulting applications are combinations of these three ingredients). Each ingredient may involve the use of one or more accelerator (FPGA, ASIC) components as a local backend. In this manner, applications can be split across multiple edge owners, coordinated by an orchestrator. 
     In the context of  FIG.  5   , the pod controller/container manager, container orchestrator, and individual nodes may provide a security enforcement point. However, tenant isolation may be orchestrated where the resources allocated to a tenant are distinct from resources allocated to a second tenant, but edge owners cooperate to ensure resource allocations are not shared across tenant boundaries. Or, resource allocations could be isolated across tenant boundaries, as tenants could allow “use” via a subscription or transaction/contract basis. In these contexts, virtualization, containerization, enclaves, and hardware partitioning schemes may be used by edge owners to enforce tenancy. Other isolation environments may include bare metal (dedicated) equipment, virtual machines, containers, virtual machines on containers, or combinations thereof. 
     In further examples, aspects of software-defined or controlled silicon hardware, and other configurable hardware, may integrate with the applications, functions, and services of an edge computing system. Software-defined silicon may be used to ensure the ability for some resource or hardware ingredient to fulfill a contract or service level agreement, based on the ingredient’s ability to remediate a portion of itself or the workload (eg., by an upgrade, reconfiguration, or provision of new features within the hardware configuration itself). 
     It should be appreciated that the edge computing systems and arrangements discussed herein may be applicable in various solutions, services, and/or use cases involving mobility. As an example,  FIG.  6    shows a simplified vehicle compute and communication use case involving mobile access to applications in an edge computing system  600  that implements an edge cloud  110 . In this use case, respective client compute nodes  610  may be embodied as in-vehicle compute systems (e.g., in-vehicle navigation and/or infotainment systems) located in corresponding vehicles that communicate with the edge gateway nodes  620  during traversal of a roadway. For instance, the edge gateway nodes  620  may be located in a roadside cabinet or other enclosure built-into a structure having other, separate, mechanical utility, which may be placed along the roadway, at intersections of the roadway, or other locations near the roadway. As respective vehicles traverse along the roadway, the connection between its client compute node  610  and a particular edge gateway device  620  may propagate to maintain a consistent connection and context for the client compute node  610 . Likewise, mobile edge nodes may aggregate at the high priority services or according to the throughput or latency resolution requirements for the underlying service(s) (e.g., in the case of drones) The respective edge gateway devices  620  include an amount of processing and storage capabilities and, as such, some processing and/or storage of data for the client compute nodes  610  may be performed on one or more of the edge gateway devices  620 . 
     The edge gateway devices  620  may communicate with one or more edge resource nodes  640 , which are illustratively embodied as compute servers, appliances, or components located at or in a communication base station  642  (e.g., a base station of a cellular network) As discussed above, the respective edge resource nodes  640  include an amount of processing and storage capabilities, and, as such, some processing and/or storage of data for the client compute nodes  610  may be performed on the edge resource node  640 . For example, the processing of data that is less urgent or important may be performed by the edge resource node  640 , while the processing of data that is of a higher urgency or importance may be performed by the edge gateway devices  620  (depending on, for example, the capabilities of each component, or information in the request indicating urgency or importance). Based on data access, data location, or latency, work may continue on edge resource nodes when the processing priorities change during the processing activity. Likewise, configurable systems or hardware resources themselves can be activated (e.g, through a local orchestrator) to provide additional resources to meet the new demand (e.g., adapt the compute resources to the workload data) 
     The edge resource node(s)  640  also communicates with the core data center  650 , which may include compute servers, appliances, and/or other components located in a central location (e.g., a central office of a cellular communication network). The core data center  650  may provide a gateway to the global network cloud  660  (e.g., the Internet) for the edge cloud  110   operations formed by the edge resource node(s)  640  and the edge gateway devices  620 . Additionally, in some examples, the core data center  650  may include an amount of processing and storage capabilities and, as such, some processing and/or storage of data for the client compute devices may be performed on the core data center  650  (e.g., processing of low urgency or importance, or high complexity). 
     The edge gateway nodes  620  or the edge resource nodes  640  may offer the use of stateful applications  632  and a geographic distributed database  634 . Although the applications  632  and database  634  are illustrated as being horizontally distributed at a layer of the edge cloud  110 , it will be understood that resources, services, or other components of the application may be vertically distributed throughout the edge cloud (including, part of the application executed at the client compute node  610 , other parts at the edge gateway nodes  620  or the edge resource nodes  640 , etc.). Additionally, as stated previously, there can be peer relationships at any level to meet service objectives and obligations. Further, the data for a specific client or application can move from edge to edge based on changing conditions (e.g., based on acceleration resource availability, following the car movement, etc.). For instance, based on the “rate of decay” of access, prediction can be made to identify the next owner to continue, or when the data or computational access will no longer be viable. These and other services may be utilized to complete the work that is needed to keep the transaction compliant and lossless. 
     In further scenarios, a container  636  (or a pod of containers) may be flexibly migrated from an edge node  620  to other edge nodes (e.g.,  620 ,  640 , etc.) such that the container with an application and workload does not need to be reconstituted, re-compiled, re-interpreted for migration to work. However, in such settings, there may be some remedial or “swizzling” translation operations applied. For example, the physical hardware at node  640  may differ from edge gateway node  620  and therefore, the hardware abstraction layer (HAL) that makes up the bottom edge of the container will be re-mapped to the physical layer of the target edge node. This may involve some form of late-binding technique, such as binary translation of the HAL from the container-native format to the physical hardware format, or may involve mapping interfaces and operations. A pod controller may be used to drive the interface mapping as part of the container lifecycle, which includes migration to/from different hardware environments. 
     The scenarios encompassed by  FIG.  6    may utilize various types of mobile edge nodes, such as an edge node hosted in a vehicle (car/truck/tram/train) or other mobile units, as the edge node will move to other geographic locations along the platform hosting it. With vehicle-to-vehicle communications, individual vehicles may even act as network edge nodes for other cars, (e.g., to perform caching, reporting, data aggregation, etc.). Thus, it will be understood that the application components provided in various edge nodes may be distributed in static or mobile settings, including coordination between some functions or operations at individual endpoint devices or the edge gateway nodes  620 , some others at the edge resource node  640 , and others in the core data center  650  or global network cloud  660 . 
     In an example embodiment, the edge cloud  110  in  FIG.  6    utilizes FMF  111  in connection with disclosed techniques. The FMF  111  may be performed by a communication node configured as a federation manager (or another federation management entity) within a federated MEC network as discussed in connection with  FIG.  8 A  -  FIG.  25   . 
     In further configurations, the edge computing system may implement FaaS computing capabilities through the use of respective executable applications and functions. In an example, a developer writes function code (e.g., “computer code” herein) representing one or more computer functions, and the function code is uploaded to a FaaS platform provided by, for example, an edge node or data center. A trigger such as, for example, a service use case or an edge processing event, initiates the execution of the function code with the FaaS platform. 
     In an example of FaaS, a container is used to provide an environment in which function code (e.g., an application that may be provided by a third party) is executed. The container may be any isolated-execution entity such as a process, a Docker or Kubernetes container, a virtual machine, etc. Within the edge computing system, various datacenter, edge, and endpoint (including mobile) devices are used to “spin up” functions (e.g., activate and/or allocate function actions) that are scaled on demand. The function code gets executed on the physical infrastructure (e.g., edge computing node) device and underlying virtualized containers. Finally, the container is “spun down” (e.g., deactivated and/or deallocated) on the infrastructure in response to the execution being completed. 
     Further aspects of FaaS may enable deployment of edge functions in a service fashion, including support of respective functions that support edge computing as a service (Edge-as-a-Service or “EaaS”). Additional features of FaaS may include: a granular billing component that enables customers (e.g., computer code developers) to pay only when their code gets executed; common data storage to store data for reuse by one or more functions; orchestration and management among individual functions; function execution management, parallelism, and consolidation; management of container and function memory spaces; coordination of acceleration resources available for functions; and distribution of functions between containers (including “warm” containers, already deployed or operating, versus “cold” which require initialization, deployment, or configuration). 
     The edge computing system  600  can include or be in communication with an edge provisioning node  644 . The edge provisioning node  644  can distribute software such as the example computer-readable (also referred to as machine-readable) instructions  782  of  FIG.  7 B , to various receiving parties for implementing any of the methods described herein. The example edge provisioning node  644  may be implemented by any computer server, home server, content delivery network, virtual server, software distribution system, central facility, storage device, storage node, data facility, cloud service, etc., capable of storing and/or transmitting software instructions (e.g., code, scripts, executable binaries, containers, packages, compressed files, and/or derivatives thereof) to other computing devices. Component(s) of the example edge provisioning node  644  may be located in a cloud, in a local area network, in an edge network, in a wide area network, on the Internet, and/or any other location communicatively coupled with the receiving party(ies). The receiving parties may be customers, clients, associates, users, etc. of the entity owning and/or operating the edge provisioning node  644 . For example, the entity that owns and/or operates the edge provisioning node  644  may be a developer, a seller, and/or a licensor (or a customer and/or consumer thereof) of software instructions such as the example computer-readable instructions  782  of  FIG.  7 B . The receiving parties may be consumers, service providers, users, retailers, OEMs, etc., who purchase and/or license the software instructions for use and/or re-sale and/or sub-licensing. 
     In an example, the edge provisioning node  644  includes one or more servers and one or more storage devices. The storage devices host computer-readable instructions such as the example computer-readable instructions  782  of  FIG.  7 B , as described below. Similar to edge gateway devices  620  described above, the one or more servers of the edge provisioning node  644  are in communication with a base station  642  or other network communication entity. In some examples, the one or more servers are responsive to requests to transmit the software instructions to a requesting party as part of a commercial transaction. Payment for the delivery, sale, and/or license of the software instructions may be handled by the one or more servers of the software distribution platform and/or via a third party payment entity. The servers enable purchasers and/or licensors to download the computer-readable instructions  782  from the edge provisioning node  644 . For example, the software instructions, which may correspond to the example computer-readable instructions  782  of  FIG.  7 B  may be downloaded to the example processor platform/s, which is to execute the computer-readable instructions  782  to implement the methods described herein. 
     In some examples, the processor platform(s) that execute the computer-readable instructions  782  can be physically located in different geographic locations, legal jurisdictions, etc. In some examples, one or more servers of the edge provisioning node  644  periodically offer, transmit, and/or force updates to the software instructions (e.g., the example computer-readable instructions  782  of  FIG.  7 B ) to ensure improvements, patches, updates, etc. are distributed and applied to the software instructions implemented at the end-user devices. In some examples, different components of the computer-readable instructions  782  can be distributed from different sources and/or to different processor platforms; for example, different libraries, plug-ins, components, and other types of compute modules, whether compiled or interpreted, can be distributed from different sources and/or to different processor platforms. For example, a portion of the software instructions (e.g., a script that is not, in itself, executable) may be distributed from a first source while an interpreter (capable of executing the script) may be distributed from a second source. 
     In further examples, any of the compute nodes or devices discussed with reference to the present edge computing systems and environment may be fulfilled based on the components depicted in  FIGS.  7 A and  7 B . Respective edge compute nodes may be embodied as a type of device, appliance, computer, or other “thing” capable of communicating with other edges, networking, or endpoint components. For example, an edge compute device may be embodied as a personal computer, a server, a smartphone, a mobile compute device, a smart appliance, an in-vehicle compute system (e.g., a navigation system), a self-contained device having an outer case, shell, etc., or other device or system capable of performing the described functions. 
     In the simplified example depicted in  FIG.  7 A , an edge compute node  700  includes a compute engine (also referred to herein as “compute circuitry”)  702 , an input/output (I/O) subsystem  708 , data storage  710 , a communication circuitry subsystem  712 , and, optionally, one or more peripheral devices  714 . In other examples, respective compute devices may include other or additional components, such as those typically found in a computer (e.g., a display, peripheral devices, etc.). Additionally, in some examples, one or more of the illustrative components may be incorporated in, or otherwise form a portion of, another component. 
     The compute node  700  may be embodied as any type of engine, device, or collection of devices capable of performing various compute functions. In some examples, the compute node  700  may be embodied as a single device such as an integrated circuit, an embedded system, a field-programmable gate array (FPGA), a system-on-a-chip (SOC), or other integrated system or device. In the illustrative example, the compute node  700  includes or is embodied as a processor  704  and a memory  706 . The processor  704  may be embodied as any type of processor capable of performing the functions described herein (e.g., executing an application). For example, the processor  704  may be embodied as a multi-core processor(s), a microcontroller, a processing unit, a specialized or special purpose processing unit, or other processor or processing/controlling circuit. 
     In some examples, the processor  704  may be embodied as, include, or be coupled to an FPGA, an application-specific integrated circuit (ASIC), reconfigurable hardware or hardware circuitry, or other specialized hardware to facilitate the performance of the functions described herein. Also in some examples, the processor  704  may be embodied as a specialized x-processing unit (xPU) also known as a data processing unit (DPU), infrastructure processing unit (IPU), or network processing unit (NPU). Such an xPU may be embodied as a standalone circuit or circuit package, integrated within a SOC or integrated with networking circuitry (e.g., in a SmartNIC, or enhanced SmartNIC), acceleration circuitry, storage devices, or AI hardware (e.g., GPUs, programmed FPGAs, Network Processing Units (NPUs), Infrastructure Processing Units (IPUs), Storage Processing Units (SPUs), AI Processors (APUs), Data Processing Unit (DPUs), or other specialized accelerators such as a cryptographic processing unit/accelerator). Such an xPU may be designed to receive programming to process one or more data streams and perform specific tasks and actions for the data streams (such as hosting microservices, performing service management or orchestration, organizing or managing server or data center hardware, managing service meshes, or collecting and distributing telemetry), outside of the CPU or general-purpose processing hardware. However, it will be understood that an xPU, a SOC, a CPU, and other variations of the processor  704  may work in coordination with each other to execute many types of operations and instructions within and on behalf of the compute node  700 . 
     The memory  706  may be embodied as any type of volatile (e.g., dynamic random access memory (DRAM), etc.) or non-volatile memory or data storage capable of performing the functions described herein. Volatile memory may be a storage medium that requires power to maintain the state of data stored by the medium. Non-limiting examples of volatile memory may include various types of random access memory (RAM), such as DRAM or static random access memory (SRAM). One particular type of DRAM that may be used in a memory module is synchronous dynamic random access memory (SDRAM). 
     In an example, the memory device is a block addressable memory device, such as those based on NAND or NOR technologies. A memory device may also include a three-dimensional crosspoint memory device (e.g., Intel® 3D XPoint™ memory), or other byte-addressable write-in-place nonvolatile memory devices. The memory device may refer to the die itself and/or to a packaged memory product. In some examples, 3D crosspoint memory (e.g., Intel® 3D XPoint™ memory) may comprise a transistor-less stackable crosspoint architecture in which memory cells sit at the intersection of word lines and bit lines and are individually addressable and in which bit storage is based on a change in bulk resistance. In some examples, all or a portion of the memory  706  may be integrated into the processor  704 . The memory  706  may store various software and data used during operation such as one or more applications, data operated on by the application(s), libraries, and drivers. 
     The compute circuitry  702  is communicatively coupled to other components of the compute node  700  via the I/O subsystem  708 , which may be embodied as circuitry and/or components to facilitate input/output operations with the compute circuitry  702  (e.g., with the processor  704  and/or the main memory  706 ) and other components of the compute circuitry  702 . For example, the I/O subsystem  708  may be embodied as, or otherwise include memory controller hubs, input/output control hubs, integrated sensor hubs, firmware devices, communication links (e.g., point-to-point links, bus links, wires, cables, light guides, printed circuit board traces, etc.), and/or other components and subsystems to facilitate the input/output operations. In some examples, the I/O subsystem  708  may form a portion of a system-on-a-chip (SoC) and be incorporated, along with one or more of the processor  704 , the memory  706 , and other components of the compute circuitry  702 , into the compute circuitry  702 . 
     The one or more illustrative data storage devices  710  may be embodied as any type of device configured for short-term or long-term storage of data such as, for example, memory devices and circuits, memory cards, hard disk drives, solid-state drives, or other data storage devices. Individual data storage devices  710  may include a system partition that stores data and firmware code for the data storage device  710 . Individual data storage devices  710  may also include one or more operating system partitions that store data files and executables for operating systems depending on, for example, the type of compute node  700 . 
     The communication circuitry  712  may be embodied as any communication circuit, device, or collection thereof, capable of enabling communications over a network between the compute circuitry  702  and another compute device (eg., an edge gateway of an implementing edge computing system). The communication circuitry  712  may be configured to use any one or more communication technology (e.g., wired or wireless communications) and associated protocols (e.g., a cellular networking protocol such a 3GPP 4G or 5G standard, a wireless local area network protocol such as IEEE 802.11/Wi-Fi®, a wireless wide area network protocol, Ethernet, Bluetooth®, Bluetooth Low Energy, an IoT protocol such as IEEE 802.15.4 or ZigBee®, low-power wide-area network (LPWAN) or low-power wide-area (LPWA) protocols, etc.) to effect such communication. 
     The illustrative communication circuitry  712  includes a network interface controller (NIC)  720 , which may also be referred to as a host fabric interface (HFI). The NIC  720  may be embodied as one or more add-in-boards, daughter cards, network interface cards, controller chips, chipsets, or other devices that may be used by the compute node  700  to connect with another compute device (e.g., an edge gateway node). In some examples, the NIC  720  may be embodied as part of a system-on-a-chip (SoC) that includes one or more processors or included on a multichip package that also contains one or more processors. In some examples, the NIC  720  may include a local processor (not shown) and/or a local memory (not shown) that are both local to the NIC  720 . In such examples, the local processor of the NIC  720  may be capable of performing one or more of the functions of the compute circuitry  702  described herein. Additionally, or in such examples, the local memory of the NIC  720  may be integrated into one or more components of the client compute node at the board level, socket level, chip level, and/or other levels. 
     Additionally, in some examples, a respective compute node  700  may include one or more peripheral devices  714 . Such peripheral devices  714  may include any type of peripheral device found in a compute device or server such as audio input devices, a display, other input/output devices, interface devices, and/or other peripheral devices, depending on the particular type of the compute node  700 . In further examples, the compute node  700  may be embodied by a respective edge compute node (whether a client, gateway, or aggregation node) in an edge computing system or like forms of appliances, computers, subsystems, circuitry, or other components. 
     In a more detailed example,  FIG.  7 B  illustrates a block diagram of an example of components that may be present in an edge computing node  750  for implementing the techniques (e.g., operations, processes, methods, and methodologies) described herein. This edge computing node  750  provides a closer view of the respective components of node  700  when implemented as or as part of a computing device (e.g., as a mobile device, a base station, server, gateway, etc.). The edge computing node  750  may include any combinations of the hardware or logical components referenced herein, and it may include or couple with any device usable with an edge communication network or a combination of such networks. The components may be implemented as integrated circuits (ICs), portions thereof, discrete electronic devices, or other modules, instruction sets, programmable logic or algorithms, hardware, hardware accelerators, software, firmware, or a combination thereof adapted in the edge computing node  750 , or as components otherwise incorporated within a chassis of a larger system. 
     The edge computing device  750  may include processing circuitry in the form of a processor  752 , which may be a microprocessor, a multi-core processor, a multithreaded processor, an ultra-low voltage processor, an embedded processor, an xPU/DPU/IPU/NPU, special purpose processing unit, specialized processing unit, or other known processing elements. The processor  752  may be a part of a system on a chip (SoC) in which the processor  752  and other components are formed into a single integrated circuit, or a single package, such as the Edison™ or Galileo™ SoC boards from Intel Corporation, Santa Clara, California. As an example, the processor  752  may include an Intel® Architecture Core™ based CPU processor, such as a Quark™, an Atom™, an i3, an i5, an i7, an i9, or an MCU-class processor, or another such processor available from Intel®. However, any number of other processors may be used, such as available from Advanced Micro Devices, Inc. (AMD®) of Sunnyvale, California, a MIPS®-based design from MIPS Technologies, Inc. of Sunnyvale, California, an ARM®-based design licensed from ARM Holdings, Ltd. or a customer thereof, or their licensees or adopters. The processors may include units such as an A5-A13 processor from Apple® Inc., a Snapdragon™ processor from Qualcomm® Technologies, Inc., or an OMAP™ processor from Texas Instruments, Inc. The processor  752  and accompanying circuitry may be provided in a single socket form factor, multiple socket form factor, or a variety of other formats, including in limited hardware configurations or configurations that include fewer than all elements shown in  FIG.  7 B . 
     The processor  752  may communicate with a system memory  754  over an interconnect  756  (e.g., a bus). Any number of memory devices may be used to provide for a given amount of system memory. As an example, the memory  754  may be random access memory (RAM) per a Joint Electron Devices Engineering Council (JEDEC) design such as the DDR or mobile DDR standards (e.g., LPDDR, LPDDR2, LPDDR3, or LPDDR4) In particular examples, a memory component may comply with a DRAM standard promulgated by JEDEC, such as JESD79F for DDR SDRAM, JESD79-2F for DDR2 SDRAM, JESD79-3F for DDR3 SDRAM, JESD79-4A for DDR4 SDRAM, JESD209 for Low Power DDR (LPDDR), JESD209-2 for LPDDR2, JESD209-3 for LPDDR3, and JESD209-4 for LPDDR4. Such standards (and similar standards) may be referred to as DDR-based standards and communication interfaces of the storage devices that implement such standards may be referred to as DDR-based interfaces. In various implementations, the individual memory devices may be of any number of different package types such as single die package (SDP), dual die package (DDP), or quad die package (Q17P). These devices, in some examples, may be directly soldered onto a motherboard to provide a lower profile solution, while in other examples the devices are configured as one or more memory modules that in turn couple to the motherboard by a given connector. Any number of other memory implementations may be used, such as other types of memory modules, e.g., dual inline memory modules (DIMMs) of different varieties including but not limited to microDIMMs or MiniDIMMs. 
     To provide for persistent storage of information such as data, applications, operating systems, and so forth, a storage  758  may also couple to the processor  752  via the interconnect  756 . In an example, storage  758  may be implemented via a solid-state disk drive (SSDD). Other devices that may be used for the storage  758  include flash memory cards, such as Secure Digital (SD) cards, microSD cards, eXtreme Digital (XD) picture cards, and the like, and Universal Serial Bus (USB) flash drives. In an example, the memory device may be or may include memory devices that use chalcogenide glass, multi-threshold level NAND flash memory, NOR flash memory, single or multi-level Phase Change Memory (PCM), a resistive memory, nanowire memory, ferroelectric transistor random access memory (FeTRAM), anti-ferroelectric memory, magnetoresistive random access memory (MRAM) memory that incorporates memristor technology, resistive memory including the metal oxide base, the oxygen vacancy base and the conductive bridge Random Access Memory (CB-RAM), or spin-transfer torque (STT)-MRAM, a spintronic magnetic junction memory-based device, a magnetic tunneling junction (MTJ) based device, a DW (Domain Wall) and SOT (Spin-Orbit Transfer) based device, a thyristor-based memory device, or a combination of any of the above, or other memory. 
     In low power implementations, the storage  758  may be on-die memory or registers associated with the processor  752 . However, in some examples, the storage  758  may be implemented using a micro hard disk drive (HDD). Further, any number of new technologies may be used for the storage  758  in addition to, or instead of, the technologies described, such resistance change memories, phase change memories, holographic memories, or chemical memories, among others. 
     The components may communicate over the interconnect  756 . The interconnect  756  may include any number of technologies, including industry-standard architecture (ISA), extended ISA (EISA), peripheral component interconnect (PCI), peripheral component interconnect extended (PCIx), PCI express (PCIe), or any number of other technologies. The interconnect  756  may be a proprietary bus, for example, used in an SoC based system. Other bus systems may be included, such as an Inter-Integrated Circuit (I2C) interface, a Serial Peripheral Interface (SPI) interface, point to point interfaces, and a power bus, among others. 
     The interconnect  756  may couple the processor  752  to a transceiver  766 , for communications with the connected edge devices  762 . The transceiver  766  may use any number of frequencies and protocols, such as 2.4 Gigahertz (GHz) transmissions under the IEEE 802.15.4 standard, using the Bluetooth® low energy (BLE) standard, as defined by the Bluetooth® Special Interest Group, or the ZigBee® standard, among others. Any number of radios, configured for a particular wireless communication protocol, may be used for the connections to the connected edge devices  762 . For example, a wireless local area network (WLAN) unit may be used to implement Wi-Fi® communications under the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standard. Also, wireless wide area communications, e.g, according to a cellular or other wireless wide area protocol, may occur via a wireless wide area network (WWAN) unit. 
     The wireless network transceiver  766  (or multiple transceivers) may communicate using multiple standards or radios for communications at a different range. For example, the edge computing node  750  may communicate with close devices, e.g., within about 10 meters, using a local transceiver based on Bluetooth Low Energy (BLE), or another low power radio, to save power. More distant connected edge devices  762 , e.g., within about 50 meters, may be reached over ZigBee® or other intermediate power radios. Both communications techniques may take place over a single radio at different power levels or may take place over separate transceivers, for example, a local transceiver using BLE and a separate mesh transceiver using ZigBee® 
     A wireless network transceiver  766  (e.g., a radio transceiver) may be included to communicate with devices or services in the edge cloud  795  via local or wide area network protocols. The wireless network transceiver  766  may be a low-power wide-area (LPWA) transceiver that follows the IEEE 802.15.4, or IEEE 802.15.4 g standards, among others. The edge computing node  750  may communicate over a wide area using LoRaWAN™ (Long Range Wide Area Network) developed by Semtech and the LoRa Alliance. The techniques described herein are not limited to these technologies but may be used with any number of other cloud transceivers that implement long-range, low bandwidth communications, such as Sigfox, and other technologies. Further, other communications techniques, such as time-slotted channel hopping, described in the IEEE 802.15.4e specification may be used. 
     Any number of other radio communications and protocols may be used in addition to the systems mentioned for the wireless network transceiver  766 , as described herein. For example, the transceiver  766  may include a cellular transceiver that uses spread spectrum (SPA/SAS) communications for implementing high-speed communications. Further, any number of other protocols may be used, such as Wi-Fi® networks for medium speed communications and provision of network communications. The transceiver  766  may include radios that are compatible with any number of 3GPP (Third Generation Partnership Project) specifications, such as Long Term Evolution (LTE) and 5th Generation (5G) communication systems, discussed in further detail at the end of the present disclosure. A network interface controller (NIC)  768  may be included to provide a wired communication to nodes of the edge cloud  795  or other devices, such as the connected edge devices  762  (e.g., operating in a mesh). The wired communication may provide an Ethernet connection or may be based on other types of networks, such as Controller Area Network (CAN), Local Interconnect Network (LIN), DeviceNet, ControlNet, Data Highway+, PROFIBUS, or PROFINET, among many others. An additional NIC  768  may be included to enable connecting to a second network, for example, a first NIC  768  providing communications to the cloud over Ethernet, and a second NIC  768  providing communications to other devices over another type of network. 
     Given the variety of types of applicable communications from the device to another component or network, applicable communications circuitry used by the device may include or be embodied by any one or more of components  764 ,  766 ,  768 , or  770 . Accordingly, in various examples, applicable means for communicating (e.g., receiving, transmitting, etc.) may be embodied by such communications circuitry. 
     The edge computing node  750  may include or be coupled to acceleration circuitry  764 , which may be embodied by one or more artificial intelligence (AI) accelerators, a neural compute stick, neuromorphic hardware, an FPGA, an arrangement of GPUs, an arrangement of xPUs/DPUs/IPU/NPUs, one or more SoCs, one or more CPUs, one or more digital signal processors, dedicated ASICs, or other forms of specialized processors or circuitry designed to accomplish one or more specialized tasks. These tasks may include AI processing (including machine learning, training, inferencing, and classification operations), visual data processing, network data processing, object detection, rule analysis, or the like. These tasks also may include the specific edge computing tasks for service management and service operations discussed elsewhere in this document. 
     The interconnect  756  may couple the processor  752  to a sensor hub or external interface  770  that is used to connect additional devices or subsystems. The devices may include sensors  772 , such as accelerometers, level sensors, flow sensors, optical light sensors, camera sensors, temperature sensors, global navigation system (e.g., GPS) sensors, pressure sensors, barometric pressure sensors, and the like. The hub or interface  770  further may be used to connect the edge computing node  750  to actuators  774 , such as power switches, valve actuators, an audible sound generator, a visual warning device, and the like. 
     In some optional examples, various input/output (I/O) devices may be present within or connected to, the edge computing node  750 . For example, a display or other output device  784  may be included to show information, such as sensor readings or actuator position. An input device  786 , such as a touch screen or keypad may be included to accept input. An output device  784  may include any number of forms of audio or visual display, including simple visual outputs such as binary status indicators (e.g., light-emitting diodes (LEDs)) and multi-character visual outputs, or more complex outputs such as display screens (e.g., liquid crystal display (LCD) screens), with the output of characters, graphics, multimedia objects, and the like being generated or produced from the operation of the edge computing node  750 . A display or console hardware, in the context of the present system, may be used to provide output and receive input of an edge computing system; to manage components or services of an edge computing system; identify a state of an edge computing component or service, or to conduct any other number of management or administration functions or service use cases. 
     A battery  776  may power the edge computing node  750 , although, in examples in which the edge computing node  750  is mounted in a fixed location, it may have a power supply coupled to an electrical grid, or the battery may be used as a backup or for temporary capabilities. The battery  776  may be a lithium-ion battery, or a metal-air battery, such as a zinc-air battery, an aluminum-air battery, a lithium-air battery, and the like. 
     A battery monitor/charger  778  may be included in the edge computing node  750  to track the state of charge (SoCh) of the battery  776 , if included. The battery monitor/charger  778  may be used to monitor other parameters of the battery  776  to provide failure predictions, such as the state of health (SoH) and the state of function (SoF) of the battery  776 . The battery monitor/charger  778  may include a battery monitoring integrated circuit, such as an LTC4020 or an LTC2990 from Linear Technologies, an ADT7488A from ON Semiconductor of Phoenix Arizona, or an IC from the UCD90xxx family from Texas Instruments of Dallas, TX. The battery monitor/charger  778  may communicate the information on the battery  776  to the processor  752  over the interconnect  756 . The battery monitor/charger  778  may also include an analog-to-digital (ADC) converter that enables the processor  752  to directly monitor the voltage of the battery  776  or the current flow from the battery  776 . The battery parameters may be used to determine actions that the edge computing node  750  may perform, such as transmission frequency, mesh network operation, sensing frequency, and the like. 
     A power block  780 , or other power supply coupled to a grid, may be coupled with the battery monitor/charger  778  to charge the battery  776 . In some examples, the power block  780  may be replaced with a wireless power receiver to obtain the power wirelessly, for example, through a loop antenna in the edge computing node  750 . A wireless battery charging circuit, such as an LTC4020 chip from Linear Technologies of Milpitas, California, among others, may be included in the battery monitor/charger  778 . The specific charging circuits may be selected based on the size of the battery  776 , and thus, the current required. The charging may be performed using the Airfuel standard promulgated by the Airfuel Alliance, the Qi wireless charging standard promulgated by the Wireless Power Consortium, or the Rezence charging standard, promulgated by the Alliance for Wireless Power, among others. 
     The storage  758  may include instructions  782  in the form of software, firmware, or hardware commands to implement the techniques described herein. Although such instructions  782  are shown as code blocks included in the memory  754  and the storage  758 , it may be understood that any of the code blocks may be replaced with hardwired circuits, for example, built into an application-specific integrated circuit (ASIC). 
     Also in a specific example, the instructions  782  on the processor  752  (separately, or in combination with the instructions  782  of the machine-readable medium  760 ) may configure execution or operation of a trusted execution environment (TEE)  790 . In an example, the TEE  790  operates as a protected area accessible to the processor  752  for secure execution of instructions and secure access to data. Various implementations of the TEE  790 , and an accompanying secure area in the processor  752  or the memory  754  may be provided, for instance, through the use of Intel® Software Guard Extensions (SGX) or ARM® TrustZone® hardware security extensions, Intel® Management Engine (ME), or Intel® Converged Security Manageability Engine (CSME). Other aspects of security hardening, hardware roots-of-trust, and trusted or protected operations may be implemented in device  750  through the TEE  790  and the processor  752 . 
     In an example, the instructions  782  provided via memory  754 , the storage  758 , or the processor  752  may be embodied as a non-transitory, machine-readable medium  760  including code to direct the processor  752  to perform electronic operations in the edge computing node  750 . The processor  752  may access the non-transitory, machine-readable medium  760  over the interconnect  756 . For instance, the non-transitory, machine-readable medium  760  may be embodied by devices described for the storage  758  or may include specific storage units such as optical disks, flash drives, or any number of other hardware devices. The non-transitory, machine-readable medium  760  may include instructions to direct the processor  752  to perform a specific sequence or flow of actions, for example, as described with respect to the flowchart(s) and block diagram(s) of operations and functionality depicted above. As used herein, the terms “machine-readable medium”, “computer-readable medium”, “machine-readable storage”, and “computer-readable storage” are interchangeable. 
     In further examples, a machine-readable medium also includes any tangible medium that is capable of storing, encoding, or carrying instructions for execution by a machine and that cause the machine to perform any one or more of the methodologies of the present disclosure or that is capable of storing, encoding or carrying data structures utilized by or associated with such instructions. A “machine-readable medium” thus may include but is not limited to, solid-state memories, and optical and magnetic media. Specific examples of machine-readable media include non-volatile memory, including but not limited to, by way of example, semiconductor memory devices (e.g., electrically programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM)) and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The instructions embodied by a machine-readable medium may further be transmitted or received over a communications network using a transmission medium via a network interface device utilizing any one of several transfer protocols (e.g., Hypertext Transfer Protocol (HTTP)). 
     A machine-readable medium may be provided by a storage device or other apparatus which is capable of hosting data in a non-transitory format. In an example, information stored or otherwise provided on a machine-readable medium may be representative of instructions, such as instructions themselves or a format from which the instructions may be derived. This format from which the instructions may be derived may include source code, encoded instructions (e.g., in compressed or encrypted form), packaged instructions (e.g., split into multiple packages), or the like. The information representative of the instructions in the machine-readable medium may be processed by processing circuitry into the instructions to implement any of the operations discussed herein. For example, deriving the instructions from the information (e.g., processing by the processing circuitry) may include: compiling (e.g., from source code, object code, etc.), interpreting, loading, organizing (e.g., dynamically or statically linking), encoding, decoding, encrypting, unencrypting, packaging, unpackaging, or otherwise manipulating the information into the instructions. 
     In an example, the derivation of the instructions may include assembly, compilation, or interpretation of the information (e.g., by the processing circuitry) to create the instructions from some intermediate or preprocessed format provided by the machine-readable medium. The information, when provided in multiple parts, may be combined, unpacked, and modified to create the instructions. For example, the information may be in multiple compressed source code packages (or object code, or binary executable code, etc.) on one or several remote servers The source code packages may be encrypted when in transit over a network and decrypted, uncompressed, assembled (e.g., linked) if necessary, and compiled or interpreted (e.g., into a library, stand-alone executable, etc.) at a local machine, and executed by the local machine. 
       FIG.  7 C  illustrates an example software distribution platform  796  to distribute software, such as the example computer-readable instructions  799 , to one or more devices, such as processor platform(s)  798  and/or example connected edge devices  762  of  FIG.  7 B . The example software distribution platform  796  may be implemented by any computer server, data facility, cloud service, etc., capable of storing and transmitting software to other computing devices (e.g., third parties, the example connected edge devices  762  of  FIG.  7 B ). Example connected edge devices may be customers, clients, managing devices (e.g., servers), third parties (e.g., customers of an entity owning and/or operating the software distribution platform  796 ). Example connected edge devices may operate in commercial and/or home automation environments. In some examples, a third party is a developer, a seller, and/or a licensor of software such as the example computer-readable instructions  799 . The third parties may be consumers, users, retailers, OEMs, etc. that purchase and/or license the software for use and/or re-sale and/or sub-licensing. In some examples, distributed software causes the display of one or more user interfaces (UIs) and/or graphical user interfaces (GUIs) to identify the one or more devices (e.g., connected edge devices) geographically and/or logically separated from each other (e.g., physically separated IoT devices chartered with the responsibility of water distribution control (e.g., pumps), electricity distribution control (e.g., relays), etc). 
     In the illustrated example of  FIG.  7 C , the software distribution platform  796  includes one or more servers and one or more storage devices. The storage devices store the computer-readable instructions  799 , which may correspond to the example computer-readable instructions  782  of  FIG.  7 B , as described above. The one or more servers of the example software distribution platform  796  are in communication with a network  797 , which may correspond to any one or more of the Internet and/or any of the example networks described herein. In some examples, the one or more servers are responsive to requests to transmit the software to a requesting party as part of a commercial transaction. Payment for the delivery, sale, and/or license of the software may be handled by the one or more servers of the software distribution platform and/or via a third-party payment entity. The servers enable purchasers and/or licensors to download the computer-readable instructions  799  from the software distribution platform  796 . For example, the software, which may correspond to the example computer-readable instructions  782  of  FIG.  7 B , may be downloaded to the example processor platform(s)  798  (e.g., example connected edge devices), which is/are to execute the computer-readable instructions  799  to implement the techniques discussed herein. In some examples, one or more servers of the software distribution platform  796  are communicatively connected to one or more security domains and/or security devices through which requests and transmissions of the example computer-readable instructions  799  must pass. In some examples, one or more servers of the software distribution platform  796  periodically offer, transmit, and/or force updates to the software (e.g., the example computer-readable instructions  782  of  FIG.  7 B  which can be the same as the computer-readable instructions  799 ) to ensure improvements, patches, updates, etc. are distributed and applied to the software at the end-user devices. 
     In the illustrated example of  FIG.  7 C , the computer-readable instructions  799  are stored on storage devices of the software distribution platform  796  in a particular format. A format of computer-readable instructions includes, but is not limited to a particular code language (e.g., Java, JavaScript, Python, C, C#, SQL, HTML, etc.), and/or a particular code state (e.g., uncompiled code (e.g., ASCII), interpreted code, linked code, executable code (e.g., a binary), etc.). In some examples, the computer-readable instructions  799  stored in the software distribution platform  796  are in a first format when transmitted to the example processor platform(s)  796 . In some examples, the first format is an executable binary in which particular types of the processor platform(s)  798  can execute. However, in some examples, the first format is uncompiled code that requires one or more preparation tasks to transform the first format to a second format to enable execution on the example processor platform(s)  798 . For instance, the receiving processor platform(s)  798  may need to compile the computer-readable instructions  799  in the first format to generate executable code in a second format that is capable of being executed on the processor platform(s)  798 . In still other examples, the first format is interpreted code that, upon reaching the processor platform(s)  798 , is interpreted by an interpreter to facilitate execution of instructions. 
       FIG.  8 A  illustrates a MEC network architecture  800 A supporting federation management, according to an example embodiment.  FIG.  8 A  specifically illustrates a MEC architecture  800 A with MEC hosts  802  and  804  providing functionalities per one or more ETSI MEC specifications (e.g., ETSI GS MEC-003 and ETSI GR MEC-024 specifications). Specifically, enhancements to the MEO  810  can be used for providing federation management functions within the MEC network architecture  800 A. 
     Referring to  FIG.  8 A , the MEC network architecture  800 A includes MEC hosts  802  and  804 , a virtualization infrastructure manager (VIM)  808 , a MEC platform manager  806 , a Mobile Edge Application Orchestrator (MEAO) (also referred to as a MEC orchestrator or MEO)  810 , an operations support system (OSS)  812 , a user app proxy  814 , a UE app  818  running on LTE  820 , and CFS portal  816 . The MEC host  802  can include a MEC platform  832  with filtering rules control module  840 , a DNS handling module  842 , service registry  838 , and MEC services  836 . The MEC host  804  can include resources used to instantiate MEC apps  805 . The MEC services  836  can include at least one scheduler  837 , which can be used to select resources for instantiating MEC apps (or NFVs)  826  and  828  upon virtualization infrastructure  822  that includes a data plane  824 . The MEC apps  826  and  828  can be configured to provide services  830 / 831 , which can include processing network communications traffic of different types associated with one or more wireless connections. 
     The MEC platform manager  806  can include MEC platform element management module  844 , MEC app rules and requirements management module  846 , and a MEC app lifecycle management module  848 . 
     In some aspects, UE  820  can be configured to communicate to one or more of the core networks  882  via one or more of the network slice instances (NSIs)  880 . In some aspects, the core networks  882  can use slice management functions to dynamically configure NSIs  880 , including dynamically assign a slice to a UE, configure network functions associated with the slice, configure a MEC app for communicating data using the slice, reassign a slice to a UE, dynamically allocate or reallocate resources used by one or more of the NSIs  880 , or other slice related management functions. One or more of the functions performed in connection with slice management can be initiated based on user requests (e.g., via a UE), based on a request by a service provider, or maybe triggered automatically in connection with an existing Service Level Agreement (SLA) specifying slice-related performance objectives. In some aspects, the slice management functions in connection with NSIs  880  can be facilitated by E2E multi-slice support functions for MEC-enabled 5G deployments, provided by the MEC NFV-SCF  434  within the MEC host  802 , the MEC platform manager  806 , or within another MEC entity. 
       FIG.  8 B  illustrates a MEC reference architecture  800 B in a Network Function Virtualization (NFV) environment, according to an example. The MEC architecture  800 B can be configured to provide functionalities according to an ETSI MEC specification, such as the ETSI GR MEC-017 specification. 
     In some aspects, ETSI MEC can be deployed in an NFV environment as illustrated in  FIG.  8 B  which can also utilize federation management functions. In some aspects, the MEC platform is deployed as a virtualized network function (VNF). The MEC applications can appear like VNFs towards the ETSI NFV Management and Orchestration (MANO) components (e.g., VIM  808 , MEAO  810 , and NFVO  835 ). This allows the reuse of ETSI NFV MANO functionality. In some aspects, the full set of MANO functionality may be unused and certain additional functionality may be needed. Such a specific MEC application is denoted by the name “MEC app VNF” (or ME app VNF) as discussed herein. In some aspects, the virtualization infrastructure is deployed as an NFVI and its virtualized resources are managed by the virtualized infrastructure manager (VIM). For that purpose, one or more of the procedures defined by ETSI NFV Infrastructure specifications, i.e. ETSI GS NFV-INF 003, ETSI GS NFV-INF 004, and ETSI GS NFV-INF 005 can be used. 
     In some aspects, the MEC application (or app) VNFs will be managed like individual VNFs, allowing that a MEC-in-NFV deployment can delegate certain orchestration and Life Cycle Management (LCM) tasks to the NFVO and VNFM functional blocks, as defined by ETSI NFV MANO. 
     In some aspects, the Mobile Edge Platform Manager (MEPM)  806  can be transformed into a “Mobile Edge Platform Manager - NFV” (MEPM-V) that delegates the LCM part to one or more virtual network function manager(s) (VNFM(s)). The Mobile Edge Orchestrator (MEO), as defined in the MEC reference architecture ETSI GS MEC-003, can be transformed into a “Mobile Edge Application Orchestrator” (MEAO)  810  that uses the NFVO  835  for resource orchestration, and orchestration of the set of MEC app VNFs as one or more NFV Network Services (NSs). In some embodiments, the MEAO  810  and the MEPM  806  can be configured to perform federation management functions, including communication between MEC systems in a federated MEC network. 
     In some aspects, the Mobile Edge Platform VNF, the MEPM-V, and the VNFM (ME platform LCM) can be deployed as a single package as per the ensemble concept in 3GPP TR 32.842, or that the VNFM is a Generic VNFM as per ETSI GS NFV-IFA 009 and the Mobile Edge Platform VNF and the MEPM-V are provided by a single vendor. 
     In some aspects, the Mp1 reference point between a MEC application and the ME platform can be optional for the MEC application, unless it is an application that provides and/or consumes a ME service. Various MEC-related interfaces and reference points discussed herein are further defined in the following ETSI-related technical specifications: ETSI GS MEC-003 and ETSI GR MEC-024 specifications. 
     The Mp1 reference point is a reference point between the mobile edge platform and the mobile edge applications. The Mp1 reference point provides service registration, service discovery, and communication support for services. It also provides other functionality such as application availability, session state relocation support procedures, traffic rules, and DNS rules activation, access to persistent storage and time of day information, etc. This reference point can be used for consuming and providing service-specific functionality. 
     The Mp2 reference point is a reference point between the mobile edge platform and the data plane of the virtualization infrastructure. The Mp2 reference point is used to instruct the data plane on how to route traffic among applications, networks, services, etc. 
     The Mp3 reference point is a reference point between mobile edge platforms and it is used for control communication between mobile edge platforms. 
     In some aspects, the Mm3 reference point between the MEAO  810  and the MEPM-V  806  is based on the Mm3 reference point, as defined by ETSI GS MEC-003. Changes may be configured to this reference point to cater to the split between MEPM-V and VNFM (MEC applications LCM). 
     In some aspects, the following new reference points (Mv1, Mv2, and Mv3) are introduced between elements of the ETSI MEC architecture and the ETSI NFV architecture to support the management of MEC app VNFs. The following reference points are related to existing NFV reference points, but only a subset of the functionality may be used for ETSI MEC, and extensions may be necessary: Mv1 (this reference point connects the MEAO and the NFVO; it is related to the Os-Ma-nfvo reference point, as defined in ETSI NFV); Mv2 (this reference point connects the VNF Manager that performs the LCM of the MEC app VNFs with the MEPM-V to allow LCM related notifications to be exchanged between these entities; it is related to the Ve-Vnfm-em reference point as defined in ETSI NFV, but may include additions, and might not use all functionality offered by Ve-Vnfm-em); Mv3 (this reference point connects the VNF Manager with the MEC app VNF instance, to allow the exchange of messages e.g. related to MEC application LCM or initial deployment-specific configuration; it is related to the Ve-Vnfm-vnf reference point, as defined in ETSI NFV, but may include additions, and might not use all functionality offered by Ve-Vnfm-vnf. 
     In some aspects, the following reference points are used as they are defined by ETSI NFV: Nf-Vn (this reference point connects each MEC app VNF with the NFVI); Nf-Vi (this reference point connects the NFVI and the VIM); Os-Ma-nfvo (this reference point connects the OSS and the NFVO. It is primarily used to manage NSs, i.e several VNFs connected and orchestrated to deliver a service); Or-Vnfm (this reference point connects the NFVO and the VNFM; it is primarily used for the NFVO to invoke VNF LCM operations); Vi-Vnfm (this reference point connects the VIM and the VNFM; it is primarily used by the VNFM to invoke resource management operations to manage the cloud resources that are needed by the VNF; it is assumed in an NFV-based MEC deployment that this reference point corresponds 1:1 to Mm6); and Or-Vi (this reference point connects the NFVO and the VIM; it is primarily used by the NFVO to manage cloud resources capacity). 
       FIG.  9    illustrates a MEC-enabled 5G communication system  900  and an example of the mapping of MEC entities to some of the 5G system’s components (namely, AF and UPF), according to an example. The MEC-enabled 5G communication system  900  can be configured to provide federation management functions as well as functionalities per one or more ETSI MEC specifications, such as the ETSI GS MEC-003 specification, the ETSI GR MEC-017 specification, and/or the ETSI GS MEC-024 specification. 
     The mapping of MEC entities into a 5G system is depicted in  FIG.  9   . In particular: a MEC platform is implemented as a particular application function (AF) in 3GPP; the Data Plane in the MEC architecture corresponds to a User Plane Function (UPF) in 3GPP, and the MEC apps are mapped to the local DN (Data Network) in 3GPP. 
     As illustrated in  FIG.  9   , UE  902  is coupled to RAN  906  via a remote radio head (RRH)  904 . The RAN  906  communicates with a MEC data plane  910  within NFVI  908 . The MEC data plane  910  within the NFVI  908  is coupled to a local data network  912  of the MEC platform  918  via an N6 reference point. The MEC platform  918  is coupled to the local data network  912  via a MEC reference point Mp1. The MEC platform  918  may be instantiated as a VNF and may include MEC APIs  920  and  922  for communication with MEC apps  914  and  916  instantiated as a VNFs within the local data network  912 . The MEC platform  918  may further include API configuration information  924  (e.g., as provided by the ETSI MEC-009 specification) and application enablement functions  926  (e.g., as provided by the ETSI MEC-011 specification). The MEC platform  918  is coupled to 3GPP network functions such as NEF  930 , PCF  928 , SMF  932 , and UPF  934 . The MEC data plane  910  is coupled to the 3GPP network functions SMF  932  and the UPF  934 . Both the MEC platform  918  and the MEC data plane  910  are coupled to the central data network  936  and the application server  938  via the UPF  934 . 
     In some aspects, the RAN  906  may be fully virtualized (e.g., as a VNF using resources of the MEC system). For In some aspects, the MEC-enabled 5G communication system  900  may use a MEC NFV-SCF to provide E2E multi-slice support, including generating and implementing one or more slice configuration policies based on utility function modeling and evaluation of latency or other characteristics of MEC and non-MEC communication links for a given NSI configured within a MEC-enabled 5G communication network. For example, a QoS flow of the UE  902  may be associated with a network slice instance which includes a virtual RAN  906 , the MEC data plane  910  functioning as a 5G UPF network function, a MEC app such as  914  within the local data network  912 , and the MEC platform VNF  918  functioning as a 5G AF network function. In this regard, a specific NSI associated with a QoS of the UE  902   includes non-MEC reference points (e.g., wireless physical links between the UE  902 , the RRH  904 , and the virtual RAN  906 , as well as the N3 and N6 5G reference points. The NSI may further include MEC reference points such as the Mp1 reference points between the MEC app  914  within the local data network  912  and the MEC platform VNF  918 . 
       FIG.  10    illustrates a V2X multi-stakeholder communication scenario  1000  which can be used in connection with federated management functions, according to an example embodiment. Referring to  FIG.  10   , the illustrated MEC federation scenario of V2X services (i.e. multi-MNO, multi-OEM, multi-MEC) includes MEC providers MNO1  1010  and MNO2  1012 , a road side infrastructure (e.g., smart traffic lights or digital street signs), a third party backend  1002 , OEM backends  1004  and  1006  (associated with MEC providers  1010  and  1012  respectively), and vehicles  1014  and  1016  (associated with MEC providers  1010  and  1012  respectively). 
     In the V2X multi-stakeholder communication scenario  1000 , a V2X application instance may be running on a vehicle  1014  connected to MNO1  1010  which is equipped with a MEC system from vendor 1, and communicating with another V2X application instance, running on a server, or, in general, on a second vehicle  1016  connected to MNO2  1012 , which, in its turn, is equipped with a MEC system from vendor 2. 
       FIG.  11    illustrates a MEC federation reference scenario  1100  for a multi-OEM vehicle use case where both MNOs have MEC platforms with instantiated MEC application Y (“MEC App Y”), according to an example embodiment. Referring to  FIG.  11   , the federation reference scenario  1100  includes communication between MNO  1102  and MNO  1128  as well as vehicles  1124  and  1148 . MNO  1102  includes a MEC host  1108  with a MEC platform  1110  and executing MEC app Y  1116 . The MEC platform  1110  includes a V2X application programming interface (API)  1112  as well as other MEC services  1114 . The MNO  1102  further includes a gateway  1118 , a data network (DN)  1104 , a central user plane function (UPF)  1106 , a local UPF  1120 , and a RAN  1122 . 
     MNO  1128  includes a MEC host  1134  with a MEC platform  1136  and executing MEC app Y  1116  (apps  1116  and  1142  being the same app but executed as separate app instances on different hosts). The MEC platform  1128  includes a V2X API  1138  as well as other MEC services  1140 . The MNO  1102  further includes a gateway  1150 , a DN  1130 , a central UPF  1132 , a local UPF  1144 , and a RAN  1146 . Communication between the MEC hosts  1108  and  1134  takes place via the gateways  1118 ,  1150 , and the IP network  1126 . Communication between the vehicle  1124  and the MEC app  1116  takes place via the RAN  1122  and the local UPF  1120 . Communication between the vehicle  1148  and the MEC app  1142  takes place via the RAN  1146  and the local UPF  1144 . 
     From a network architecture point of view, the federation reference scenario  1100  is similar to the V2X multi-stakeholder communication scenario  1000  in  FIG.  10   . More specifically,  FIG.  11    illustrates a certain V2X service is implemented with two instances of the MEC App Y, each of which communicates with its corresponding client application (or app), i.e., “App Y”, and is also connected with a MEC platform in each respective MEC system (domain). 
       FIG.  12    illustrates an exemplary MEC system deployment scenario  1200  per ETSI MEC reference architecture including a service layer that can be used in connection with federated management functions, according to an example embodiment. Referring to  FIG.  12   , the exemplary MEC system deployment scenario  1200  is associated with communication between MEC system 1 and MEC system 2. MEC system 1 includes an OSS  1204  as part of service layer  1202 , MEO  1208 , and MEC platform manager (MECPM)  1210  coupled to MEC platforms  1212 ,  1214 , and  1216 . MEC system 2 includes an OSS  1206  as part of service layer  1202 , MEO  1218 , and MECPM  1220  coupled to MEC platforms  1222 ,  1224 , and  1226 . The MEC system deployment scenario  1200  further illustrates MEC management reference points and MEC platform reference points used by the MEC systems  1  and  2 . 
     Inter-MEC system communication is impactful to MNOs. ETSI MEC GS 003 specifies three high-level requirements for inter-MEC system communication, along with a hierarchical framework for inter-MEC system discovery and communication described as follows: (a) A MEC platform should be able to discover other MEC platforms that may belong to different MEC systems; (b) A MEC platform should be able to exchange information securely with other MEC platforms that may belong to different MEC systems; (c) A MEC application should be able to exchange information securely with other MEC applications that may belong to different MEC systems. 
     To enable the inter-MEC system communication, the following hierarchical inter-MEC system discovery and communication frameworks are assumed: (a) MEC system-level inter-system discovery and communication; and (b) MEC host-level inter-system communication between the MEC platforms. 
     Driven by the MNOs′ interest to form federated MEC environments, Inter-MEC systems, and MEC-Cloud systems coordination can be considered in connection with federated management functions. The “operator platform” concept, illustrated in  FIG.  13   , may also be considered when configuring federated management functions. For example, the operator platform may be configured to federate multiple operators’ edge computing infrastructure to give application providers access to a global edge cloud to run distributed and low latency services through a set of common APIs 
       FIG.  13    illustrates a high-level GSMA operator platform  1300 , according to an example embodiment. Referring to  FIG.  13   , the operator platform  1300  includes a common framework  1310  for security, charging device management, monitoring, logging, auditing policies, etc. The operator platform  1300  further includes network capabilities  1312  (e.g., cloud networking capabilities, MEC capabilities, network slicing, location APIs, etc.), federation and roaming functions  1314  (e.g., publishing capabilities, discovery, inter-/intra-operator resource management), and operation and management functions  1316 . The operator platform  1300  further includes the following interfaces: a northbound interface  1302  towards application providers, east-westbound interface  1308  towards federated networks, southbound interface  1306  towards network resources, and user network interface  1304  towards user equipment. 
     In this regard, inter-MEC system communication is essential in today’s, as well as the future’s, edge computing industry, and ecosystem. However, to unlock the full potential of federated MEC environments (as the exemplary one in  FIGS.  10 - 11   ), a well-defined signaling framework among MEC system entities may be used, both at the system level and host level. 
     A typical MEC Federation scenario of V2X services (i.e. multi-MNO, multi-OEM, multi-MEC) may be considered. The concept to be resolved is how to structure the needed signaling/messages for secure communication among different MEC systems, possibly owned and operated/managed by different entities (e.g., Mobile Network Operators - MNOs) for the needs of information exchange. Such information exchange refers to either a MEC application in need of consuming a MEC platform service or a MEC application in need of communicating with other (service-producing) MEC applications. 
     In an example embodiment, a hierarchical signaling framework is used for realizing a MEC federation constituting of MEC systems, possibly owned and operated by different parties (e.g., MNOs). This signaling framework may refer to the following hierarchical inter-MEC system communication levels: 
     (a) MEC system (i.e., below business level) discovery, including security (authentication/ authorization, system topology hiding/encryption), charging, identity management, and monitoring aspects as an essential prerequisite to forming a MEC federation; 
     (b) MEC platform discovery, either at high granularity (i.e., MEC platform) or, low granularity (e.g., zone, zone group, NFVI Point-of-Presence, NFVI node if a needed service is deployed as a VNF); and 
     (c) Information exchange at MEC platform level, for the needs of MEC service consumption, or MEC app-to-app communication. 
       FIG.  14    illustrates hierarchical functional levels based on which a MEC federation can be formed, according to an example embodiment. Referring to  FIG.  14   , the hierarchical signaling framework  1400  is formed using network management entities  1402  associated with a first MEC system and network management entities  1410  associated with a second MEC system. The network management entities  1402  include an OSS  1404 , a federation manager  1406 , and MEO  1408 . The network management entities  1402  are coupled to additional MEC entities  1418  including MEPM  1420  coupled to a MEC platform  1424  and MEPM  1422  coupled to a MEC platform  1426 . The network management entities  1410  include an OSS  1414 , a federation manager  1412 , and MEO  1416 . The network management entities  1410  are coupled to additional MEC entities  1428  including MEPM  1430  coupled to a MEC platform  1434  and MEPM  1432  coupled to a MEC platform  1436 . The hierarchical signaling framework  1400  can be configured to perform federation management functions as discussed herein. 
     Existing techniques associated with inter-MEC system communication do not include the disclosed federation management functions associated with communication in MEC federation scenarios for achieving MEC system discovery, MEC platform discovery, and inter-MEC platform information exposure. 
     In comparison, disclosed techniques can be used to configure a hierarchical signaling framework implementing a MEC federation of MEC systems (e.g., possibly owned and operated by different parties such as MNOs). This signaling framework refers to the following hierarchical inter-MEC system communication levels: (a) MEC system (i.e., below business level) discovery, including security (authentication/ authorization, system topology hiding/ encryption), charging, identity management, and monitoring aspects as an essential prerequisite to forming a MEC federation; (b) MEC platform discovery, either at high granularity (i.e., MEC platform) or, low granularity (eg., zone, zone group, NFVI Point-of-Presence, NFVI node if a needed service is deployed as a VNF); and (c) Information exchange at MEC platform level, for the needs of MEC service consumption, or MEC app-to-app communication. Additionally, the disclosed techniques can be used to facilitate the establishment of MEC applications and adoption from stakeholders in interoperable scenarios. Such a development will enable and support the MNOs′ needs to form MEC system federations aiming to enhance service performance (e.g., facilitating V2X service continuity in automotive communication scenarios). 
     In some embodiments, the disclosed techniques associated with federation management functions are used to address the needs of information exchange, for the needs of MEC/edge service consumption, which is related to section (c) in the above list of communication levels. Such information exchange refers to either a MEC application in need of consuming a MEC platform service or a MEC application in need of communicating with others (e.g., service-producing) MEC applications. 
     Information Exchange at MEC Platform Level for MEC Service Consumption or MEC App-to-App Communication 
     The following describes federation management functions (from a MEC application perspective) when an application wants to consume edge services through a MEC system. A description of processing associated with the above sections (a) and (b) follows as well, to clarify how MEC system discovery, including security (authentication/ authorization, system topology hiding/ encryption), charging, identity management and monitoring aspects, and MEC platform discovery are realized. For section (c), edge service consumption in a single MEC system is described, followed by a description of edge service consumption in a federated MEC network. 
     Edge Service Consumption in a Single MEC System 
       FIG.  15    illustrates service consumption options within a single MEC system  1500 , according to an example embodiment. Referring to  FIG.  15   , the MEC system includes MEC hosts  1502 ,  1512 , and  1520 . MEC host  1502  includes a MEC platform  1506  providing service  1508 , a MEC app  1504  executing on top of the MEC platform  1506 , and MEC data plane  1510 . MEC host  1520  includes a MEC platform  1522  providing service  1524  and MEC data plane  1526 . MEC host  1512  includes a MEC platform  1516 , a service producing MEC app  1514  executing on top of the MEC platform  1516 , and MEC data plane  1518 . 
     In a single MEC system  1500 , the MEC app  1504  running on MEC host  1502  consumes MEC services instantiated on another MEC host within the MEC system. The queried services are assumed available in the MEC system, however, such services may run at different localities. In  FIG.  15   , three general cases of edge services consumption are depicted. More specifically, MEC app  1504  can consume service  1508  on the same host  1502  via communication link  1528 . MEC app  1504  can also consume service  1524  and service associated with the service-producing MEC app  1514  via corresponding communication links  1532  and  1530 . For both remote service consumption cases at MEC hosts  1520  and  1512 , the MEC app  1504  can consume the indicated services via the Mp3 reference point  1534  that connects different MEC platforms of the same MEC system. 
     Edge Service Consumption in a MEC Federation 
     The following description relates to a MEC federation scenario that involves multiple MEC systems belonging to different (technical and/or administrative) domains. In a general case, the MEC hosts belong to different MEC systems (i.e., provided by different MEC vendors), potentially running on different MNOs networks, or in different domains. In this context, a MEC application can consume MEC services available by other MEC hosts, belonging to other MEC systems using a federated MEC Mpp-fed reference point connecting inter-system MEC platforms and, hence, allowing edge service consumption in MEC federation scenarios, as illustrated in  FIG.  16    and  FIG.  17   . 
       FIG.  16    illustrates a MEC federation scenario enabling edge service consumption across MEC systems, according to an example embodiment. Referring to  FIG.  16   , the MEC federation  1600  includes the MEC system  1602  and MEC system  1630 . MEC system  1602  includes MEC hosts  1604 ,  1622 , and  1614 . MEC host  1604  includes a MEC platform  1608  providing service  1610 , a MEC app  1606  executing on top of the MEC platform  1608 , and a MEC data plane  1612 . MEC host  1622  includes a MEC platform  1624  providing service  1626  and MEC data plane  1628 . MEC host  1614  includes a MEC platform  1618 , a service producing MEC app  1616  executing on top of the MEC platform  1618 , and a MEC data plane  1620 . 
     MEC host  1632  in MEC system  1630  includes a MEC platform  1636  providing service  1638 , a MEC app  1634  executing on top of the MEC platform  1636 , and a MEC data plane  1640 . 
     As illustrated in  FIG.  16   , MEC app  1606  can consume services within its own MEC system  1602  using the Mp3 reference point  1646  connecting MEC platforms  1608 ,  1618 , and  1624 . In an example embodiment, MEC app  1606  can also consume service in a remote MEC system within the MEC federation  1600  via communication link  1642  which can use a federated MEC Mpp-fed reference point  1644  between MEC platforms  1618  and  1636  in different MEC systems (e.g., MEC system  1602  and MEC system  1630 ). 
       FIG.  17    illustrates a MEC federation scenario including communication between two MEC platforms belonging to two MEC systems of a MEC federation using an Mpp-fed reference point, according to an example embodiment. Referring to  FIG.  17   , there is illustrated a communication scenario in a federated MEC network  1700  which is similar to the communication scenario in  FIG.  16   . More specifically, the federated MEC network  1700  includes a first MEC system  1701  and a second MEC system  1703 . The first MEC system  1701  includes MEC management entities such as MEO  1702  and MEPM  1704 . The MEPM  1704  is coupled to MEC platforms  1708  and  1706  which can be configured within different MEC hosts. The second MEC system  1703  includes MEC management entities such as MEO  1710  and M EPM  1712 . The MEPM  1712  is coupled to MEC platforms  1714  and  1716  which can be configured within different MEC hosts. 
     In some embodiments, MEC service consumption, MEC app-to-app communication, or another type of information exchange within the MEC federation network  1700  can be performed via the federated MEC Mpp-fed reference point  1718  between MEC platforms  1708  and  1714  in different MEC systems  1701  and  1703 . 
     MEC System Discovery (e.g., Security. Charging, Identity Management, and Monitoring) for Forming a MEC Federation 
     The previous description may be considered for defining a reference point that may support information exchange at the MEC platform level, for the needs of MEC service consumption, or MEC app-to-app communication. The communication framework related to MEC system discovery (including security, charging, identity management, and monitoring aspects) and MEC platform discovery may be covered by a hierarchical communication approach as discussed herein. 
     As a prerequisite, before inter-MEC system communication takes place to enable service consumption, the MEC system #1 (and in particular MEO #1) may identify which MEC systems are members of an already established MEC federation or which MEC systems are available to form a new MEC federation. This identification phase of MEC systems can be performed by a federation manager entity (e.g., as discussed in connection with  FIG.  18    and  FIG.  19   ), which is configured to manage the catalog of MEC systems involved in the federation. Furthermore, not only the MEC system identification is made possible by a federation manager, but also further information relevant to security (authentication/ authorization, system topology hiding/ encryption), charging, identity management, and monitoring aspects may be managed by the federation manager as well. In other words, the federation manager deals with all the authentication/authorization/charging policies among the various MEC systems (and in particular the respective MEOs), according to which inter-MEC-system communication is allowed and can be realized. 
     The following use cases may be used to illustrate aspects associated with identifying the MEC systems which are part of a MEC federation before inter-MEC system communication for the needs of edge service consumption. 
     Type-1 Use Case 
     About  FIG.  11   , the client app at car #1  1124  knows only its App ID (i.e., “App Y”) and eventually the service ID to be consumed (or the MEC API, or again the service produced by another MEC App running in another MEC system). In this case, a certain car, with Car ID#1 is unaware of (and potentially even uninterested in) the other cars’ IDs, but simply wants to be admitted to a pool/cluster of cars using a specific App ID (or consuming a certain service with a given ID). 
     A first example is the one of an Intersection Movement Assistant (IMA), provided by a Smart City (or a software company realizing the use case for the urban administration), where different cars have the App Y installed, and the corresponding MEC Apps are instantiated at different MEC systems It should be noted that this is the most general case. Another example is In-Vehicle Entertainment (IVE), which can consist of a generic video streaming service, that car #1 wants to consume, without knowing actually which other cars are consuming it. Another example is one of software/ firmware over-the-air (SOTA/ FOTA) updates. In the above type-1 use cases, the MEC systems hosting the MEC App corresponding to other cars in the pool are not necessarily known. 
     Type-2 Use Cases 
     About  FIG.  11   , the client app at car #1 (with its MEC App instantiated in MEC system #1) knows also the ID of car #2 (with its MEC App instantiated in MEC system #2) target peer for communication. As a first example, car #1 wants to communicate expressly with car #2, as they belong to drivers who are friends traveling together (e.g., in a platooning scenario), or belonging to a “social network” of cars consuming a certain V2X service, and thus knowing by definition their respective IDs. The only information known at car #1 is car ID#2 (i.e., UE#2). As a result, the MEC system hosting the MEC App corresponding to car #2 is not necessarily known. 
     Another example is see-through among cars belonging to different MEC systems. After an initial phase of neighbor discovery (e.g., via PC5), car #1 can get a list of other cars (and their IDs) that could provide the see-through service (i.e., offering their front cameras as a view for car# 1). An on-demand communication between two cars belonging to different MEC systems may be established. In this case, we suppose that after a preliminary phase (due to functions performed by a federation manager), MEO #1 correctly identifies the MEC system #2, concerning car #2 application activity. 
     Thus, in type-2 use cases, MEO #1 may discover the target MEO which is hosting the MEC App corresponding to car #2 (based on the ID of car #2). In a preliminary MEC system discovery phase, made possible by the federation manager (with the catalog of MEC systems involved in the federation), MEO #1 correctly identifies the MEC system #2, concerning car #2 application activity. Consequently, after this phase, MEO #1 and MEO #2 can directly communicate. 
     Type-3 Use Case 
     About  FIG.  11   , the client app at car #1 (concerning MEC system #1) knows the ID of Car #2 (target peer for communication), together with the target MEC system #2, in advance. An example can be any of the previous use cases, where the information about some of the other MEC systems is known in advance, e.g., because of the presence of an “aggregator” between few operators (not necessarily all operators in the federation). In this case, the target MEO #2 can be known, but for sake of generality, the other MEOs in the federation are not known. Thus, still, the role of the federation manager is needed to ensure interoperability and generality (i.e., guarantee a standard approach to MEC federation independent from the particular deployment/agreement among some operators) 
     In some embodiments, after a service communication query is issued by a MEC App instantiated at MEC system #1, the MEO #1 is contacting its corresponding federation manager, as a very first step, before starting the communication with other MEOs (known or not). Consequently, in the context of the present disclosure, the first phase of the communication between MEC systems is made possible with the addition of a federation management reference point Mfm-fed (between the MEO and its corresponding federation manager), as illustrated in  FIG.  18    and  FIG.  19   . 
       FIG.  18    illustrates a MEC federation scenario including communication using an Mfm-fed federation management reference point connecting a MEC system MEO with a federation manager present in each MEC system, according to an example embodiment. Referring to  FIG.  18   , there is illustrated a communication scenario in a federated MEC network  1800  The federated MEC network  1800  includes a first MEC system  1801  and a second MEC system  1803 . Each of the MEC systems is associated with its federation manager within the service layer  1802 . For example, MEC system  1801  is associated with federation manager  1816 , and MEC system  1803  is associated with federation manager  1818 . 
     The first MEC system  1801  includes MEC management entities such as OSS  1804  (within the service layer  1802 ), MEO  1806 , and MEPM  1808 . The MEPM  1808  may be coupled to MEC platforms which can be configured within different MEC hosts. The second MEC system  1803  includes MEC management entities such as OSS  1810  (within the service layer  1802 ), MEO  1812 , and MEPM  1814 . The MEPM  1814  may be coupled to MEC platforms which can be configured within different MEC hosts. 
     In some embodiments, MEC systems discovery including security (authentication/authorization, system topology hiding/encryption), charging, identity management, and monitoring aspects (as well as other federation management functions) are performed by the federation managers  1816  and  1818  using the federated MEC Mfm-fed reference points  1820  (between the MEO  1806  and the federation manager  1816 ) and  1822  (between MEO  1812  and federation manager  1818 ) within the MEC federation network  1800   
     In some embodiments, a federation management entity (eg., a federation manager) is used for each MEC system (e.g., as illustrated in  FIG.  18   ). Optionally, a federation broker may be used, where the federation broker may manage multiple federation managers and configure communications between such managers or perform other federation management functions associated with the corresponding MEC systems associated with the federation managers. In other embodiments, a common federation management entity (e.g., a common federation manager) may be used for the entire federated MEC network (e.g., as illustrated in  FIG.  19   ). 
       FIG.  19    illustrates a MEC federation scenario including communication using an Mfm-fed federation management reference point connecting a MEC system MEO with a common federation manager associated with multiple MEC systems, according to an example embodiment. Referring to  FIG.  19   , there is illustrated a communication scenario in a federated MEC network  1900  (which can also be referred to as a MEC federation or MEC federation network). The federated MEC network  1900  includes a first MEC system  1901  and a second MEC system  1903 . Both MEC systems  1901  and  1903  use a common federation manager  1916  within the service layer  1902 . 
     The first MEC system  1901  includes MEC management entities such as OSS  1904  (within the service layer  1902 ), MEO  1906 , and MEPM  1908 . The MEPM  1908  may be coupled to MEC platforms which can be configured within different MEC hosts. The second MEC system  1903  includes MEC management entities such as OSS  1910  (within the service layer  1902 ), MEO  1912 , and MEPM  1914 . The MEPM  1914  may be coupled to MEC platforms which can be configured within different MEC hosts. 
     In some embodiments, MEC systems discovery including security (authentication/authorization, system topology hiding/encryption), charging, identity management, and monitoring aspects (as well as other federation management functions) are performed by the common federation manager  1916  using the federated MEC Mfm-fed reference points  1918  (between the MEO  1906  and the common federation manager  1916 ) and  1920  (between MEO  1912  and the common federation manager  1916 ) within the MEC federation network  1900 . 
     Independently of the above embodiments associated with  FIG.  18    and  FIG.  19   , in both cases, after addressing security (authentication/authorization, system topology hiding/ encryption), charging, identity management, and monitoring aspects, the MEO receives from the federation manager the IDs of other MEOs that it can communicate with. An example communication sequence is illustrated in  FIG.  20   . 
       FIG.  20    is a message sequence chart between multiple federation managers and MEOs in a federated MEC network, according to an example embodiment. Referring to  FIG.  20   , the communication sequence  2000  takes place between a first MEO  2002  (in a first MEC system), a first federation manager  2004  (of the first MEC system), a second MEO  2008  (of a second MEC system), and a second federation manager  2006  (of the second MEC system) The entities associated with the communication sequence  2000  can be the same as illustrated in  FIG.  18    or  FIG.  19   . 
     At operation  2010 , MEO  2002  requests the MEO ID of the second MEO  2008 . At operation  2012 , federation managers  2004  and  2006  align with respect to security, charging, identity management, and monitoring aspects. At operation  2014 , federation manager  2006  requests the MEO ID from MEO  2008  At operation  2016 , MEO  2008  responds with its MEO ID. At operation  2018 , both federation managers update corresponding lists of MEC federation members, which may include lists of MEO IDs of MEOs in participating MEC systems. At operation  2020 , federation manager  2004  provides the MEO ID of MEO  2008  to MEO  2002 . In the above communication sequence  2000 , communications between the MEC MEOs and the corresponding federation managers takes place using corresponding federated MEC Mfm-fed reference points. 
     MEC Platform Discovery (at High or Low Granularity) 
     In some embodiments, MEC platform discovery can be used as another component of the disclosed federated management functions. More specifically, disclosed techniques may be used by a MEC platform to discover other MEC platforms that may belong to different MEC systems. In some aspects, the MEC platform discovery can be made possible by communication between MEOs, which are aware of their MEC system topologies and all information about the MEC platforms in their respective systems. In an example embodiment, the MEC platform discovery may use a federated MEC Meo-fed reference point among MEOs of a MEC federation, as illustrated in introduced in  FIG.  21   . 
       FIG.  21    illustrates a MEC federation scenario including communication using a Meo-fed federation management reference point connecting MEOs in a federated MEC network, according to an example embodiment Referring to  FIG.  21   , there is illustrated a communication scenario in a federated MEC network  2100  which includes a first MEC system  2101  and a second MEC system  2103 . The first MEC system  2101  includes MEC management entities such as MEO  2102  and MEPM  2104 . The MEPM  2104  is coupled to a MEC platform  2106  which can be configured within a MEC host. The second MEC system  2103  includes MEC management entities such as MEO  2108  and MEPM  2110 . The MEPM  2110  is coupled to MEC platform  2112  which can be configured within a MEC host. 
     In some embodiments, MEC platform discovery and capabilities exposure within the MEC federation network  2100  can be performed via the federated MEC Meo-fed reference point  2114  between the MEO  2102  and the MEO  2108 . For example, MEO  2102  and MEO  2108  use the federated MEC Meo-fed reference point  2114  to exchange information about their MEC platforms, list of shared services, authorization, and access policies, etc. 
       FIG.  22    illustrates a sequence diagram  2200  of signaling for establishing hierarchical inter-MEC system communication for service consumption in a federated MEC network, according to an example embodiment. In the sequence diagram  2200 , the disclosed signaling framework may be used, focusing as an example of type-1 use cases (i.e., car #1 only knows the service and application IDs). The illustrated communication sequence can take place between the following entities: MEC app (or service consumer)  2202 , MEC platform (at a first MEC system)  2204 , a first MEPM  2206 , a first MEO  2208 , a MEC platform  2214  (at a second MEC system), a second MEO  2210 , and a second MEPM  2212 . 
     At operation  2216 , the service consumer  2202  (i.e., a MEC application instantiated in MEC system #1) requests a needed service via the Mpl reference point using its ID. At operation  2218 , the respective MEC platform  2204  in MEC system #1 finds that the requested service is not locally available and forwards the service request (at operation  2220 ) to the MEPM  2206  of the MEC system #1. At operation  2222 , MEPM  2206 , in its turn, forwards the service request to MEO  2208 . 
     MEO  2208 , which has an overview of the topology and available services of MEC system #1 determines (at operation  2224 ) that the requested service is not available across MEC system #1. This triggers the need for out-of-system service consumption. To accomplish that, at operation  2226 , MEC system discovery is performed as a first step of forming a new (or, joining an already established) MEC federation (i.e., the federation manager, following a request by MEO  2208  via the Mfm-fed reference point informs MEO #1 of the MEO #2 ID, as illustrated in  FIG.  20   ). Mutual discovery of MEC systems #1 and #2, including security (authentication/authorization, system topology hiding/ encryption), charging, identity management, and monitoring aspects are performed by the two corresponding federation managers (or a common federation manager). 
     After MEC system discovery, MEO  2208  knows the ID of MEO  2210  and communicates (at operation  2228 ) with MEO  2210  via the Meo-fed reference point, requesting the IDs of the available MEC platforms of MEC system #2, their host capabilities, and available services. At operation  2230 , MEO  2210  replies with the requested information. At operation  2232 , MEO  2208  identifies which MEC platform of MEC system #2 (i.e., its ID) contains the service requested by the service consumer, i.e., the MEC App instantiated at MEC system #1 and shares the request with MEO #2 (at operation  2234 ). At operation  2236 , MEO  2210  requests the needed service from MEPM  2212  via the Mm3 reference point. At operation  2238 , MEPM  2212  requests the needed service from the destined MEC platform  2214  of MEC system #2 via the Mm5 reference point. At operation  2240 , MEC service consumption is carried out using the inter-MEC system platform-to-platform reference point (Mpp-fed), along with the Mp 1 reference point connecting the service consumer with its corresponding MEC platform of MEC system #1. 
     The procedure depicted in  FIG.  22    concerns the case where MEC system #1 and MEC system #2 are, after the needed signaling, part of the same MEC federation (i.e., business agreement), but the UE Apps installed in the cars (belonging to different MEC systems) are not necessarily aware of this MEC federation. Thus, in some embodiments, any upcoming service requests that cannot be satisfied within MEC system #1 will be forwarded to the corresponding MEO which will identify whether the sought service is available anywhere in the MEC federation (e.g. other MEC system #2). 
     The overall set of disclosed MEC federation reference points (Mfm-fed, Meo-fed, and Mpp-fed) introduced by the present disclosure are depicted in  FIG.  23    and  FIG.  24    for both variants/embodiments of having multiple federation managers or a single, overall/common federation manager, respectively. 
       FIG.  23    illustrates MEC federation reference points in a federated MEC network using a separate federation manager per MEC system, according to an example embodiment. Referring to  FIG.  23   , there is illustrated a communication scenario in a federated MEC network  2300 . The federated MEC network  2300  includes a first MEC system  2301  and a second MEC system  2303 . Each of the MEC systems is associated with its federation manager within the service layer  2302 . For example, MEC system  2301  is associated with federation manager  2332 , and MEC system  2303  is associated with federation manager  2334 . 
     The first MEC system  2301  includes MEC management entities such as OSS  2304  (within the service layer  2302 ), MEO  2306 , and MEPM  2308 . The MEPM  2308  may be coupled to MEC platforms  2310  and  2312  which can be configured within different MEC hosts. The second MEC system  2303  includes MEC management entities such as OSS  2314  (within the service layer  2302 ), MEO  2316 , and MEPM  2318 . The MEPM  2318  may be coupled to MEC platforms  2320  and  2322  which can be configured within different MEC hosts. 
     In some embodiments, MEC federation management functions may be performed (as discussed herein) using MEC federation reference points Mfm-fed  2324  and  2326 , Meo-fed  2328  (e.g., for MEC platform discovery and capability exchange), and Mpp-fed  2330  (e.g., for information exchange including service consumption). 
       FIG.  24    illustrates MEC federation reference points in a federated MEC network using a single federation manager, according to an example embodiment. Referring to  FIG.  24   , there is illustrated a communication scenario in a federated MEC network  2400  (which can also be referred to as a MEC federation or MEC federation network). The federated MEC network  2400  includes a first MEC system  2401  and a second MEC system  2403  Both MEC systems  2401  and  2403  use a common federation manager  2432  within the service layer  2402 . 
     The first MEC system  2401  includes MEC management entities such as OSS  2404  (within the service layer  2402 ), MEO  2406 , and MEPM  2408 . The MEPM  2408  may be coupled to MEC platforms  2410  and  2412  which can be configured within different MEC hosts. The second MEC system  2403  includes MEC management entities such as OSS  2414  (within the service layer  2402 ), MEO  2416 , and MEPM  2418 . The MEPM  2418  may be coupled to MEC platforms  2420  and  2422  which can be configured within different MEC hosts. 
     In some embodiments, MEC federation management functions may be performed (as discussed herein) using MEC federation reference points Mfm-fed  2424  and  2426 , Meo-fed  2428  (e.g., for MEC platform discovery and capability exchange), and Mpp-fed  2430  (e.g., for information exchange including service consumption). 
       FIG.  25    illustrates a flowchart of method 2500 for implementing a federation management entity in a federated MEC network, according to an example embodiment. Referring to  FIG.  22    and  FIG.  25   , at operation 2502, a request for a MEC service is detected (e.g., operation  2216  in  FIG.  22   ). The request may originate from a MEC application (e.g., MEC app  2202 ) instantiated on a first MEC host within a first MEC system of the federated MEC network. At operation  2504 , a second MEC system of the federated MEC network is selected, the second MEC system including a second MEC host providing the MEC service. For example, communication exchange (or negotiation) may take place between the federation managers of the two MEC systems and MEO IDs can be exchanged between the two federation managers to indicate MEC systems and hosts that offer the requested service. At operation  2506 , a set of common credentials is determined for secure communication between the first MEC system and the second MEC system. For example, such determination can take place at operation  2216  and can include communication exchanges with the corresponding federation managers via the MEC federation reference points Mfm-fed and Meo-fed. At operation  2508 , a response to the request is generated for communication to the first MEC system via a NIC, the response including the set of common credentials and identification information of a MEC management entity in the second MEC system, the MEC management entity in the second MEC system providing access to the MEC service. For example, communication exchange associated with operations  2224  -  2238  leads to MEC service consumption by the MEC app  2202 . 
     It should be understood that the functional units or capabilities described in this specification may have been referred to or labeled as components, circuits, or modules, to more particularly emphasize their implementation independence. Such components may be embodied by any number of software or hardware forms. For example, a component or module may be implemented as a hardware circuit comprising custom very-large-scale integration (VLSI) circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. A component or module may also be implemented in programmable hardware devices such as field-programmable gate arrays, programmable array logic, programmable logic devices, or the like. Components or modules may also be implemented in software for execution by various types of processors. An identified component or module of executable code may, for instance, comprise one or more physical or logical blocks of computer instructions, which may, for instance, be organized as an object, procedure, or function. Nevertheless, the executables of an identified component or module need not be physically located together but may comprise disparate instructions stored in different locations which, when joined logically together, comprise the component or module and achieve the stated purpose for the component or module. 
     Indeed, a component or module of executable code may be a single instruction, or many instructions, and may even be distributed over several different code segments, among different programs, and across several memory devices or processing systems. In particular, some aspects of the described process (such as code rewriting and code analysis) may take place on a different processing system (e.g., in a computer in a data center) than that in which the code is deployed (e.g., in a computer embedded in a sensor or robot). Similarly, operational data may be identified and illustrated herein within components or modules and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set or may be distributed over different locations including over different storage devices, and may exist, at least partially, merely as electronic signals on a system or network. The components or modules may be passive or active, including agents operable to perform desired functions. 
     Additional examples of the presently described method, system, and device embodiments include the following, non-limiting implementations. Each of the following non-limiting examples may stand on its own or may be combined in any permutation or combination with any one or more of the other examples provided below or throughout the present disclosure. 
     Additional Examples and Aspects 
     Example 1 is a computing node to implement a federation management entity associated with a federated Multi-Access Edge Computing (MEC) network, the node comprising: a network interface card (NIC); and processing circuitry coupled to the NIC, the processing circuitry configured to: detect a request for a MEC service, the request originating from a MEC application instantiated on a first MEC host within a first MEC system of the federated MEC network; select a second MEC system of the federated MEC network, the second MEC system including a second MEC host providing the MEC service; determine a set of common credentials for secure communication between the first MEC system and the second MEC system; and generate a response to the request for communication to the first MEC system via the NIC, the response including the set of common credentials and identification information of a MEC management entity in the second MEC system, the MEC management entity in the second MEC system providing access to the MEC service. 
     In Example 2, the subject matter of Example 1 includes subject matter where the federation management entity is a federation manager of the first MEC system. 
     In Example 3, the subject matter of Example 2 includes subject matter where the processing circuitry is configured to receive the request for the MEC service from a Mobile Edge Orchestrator (MEO) entity of the first MEC system via a first Mfm-fed MEC federation reference point. 
     In Example 4, the subject matter of Example 3 includes subject matter where the federation management entity is a common federation manager of the first MEC system and the second MEC system. 
     In Example 5, the subject matter of Example 4 includes subject matter where the MEC management entity in the second MEC system is an MEO entity of the second MEC system. 
     In Example 6, the subject matter of Example 5 includes subject matter where the processing circuitry is configured to: receive availability information for the MEC service from the MEO entity of the second MEC system via a second Mfm-fed MEC federation reference point. 
     In Example 7, the subject matter of any of Examples 3-6 includes subject matter where the request for the MEC service originates from the MEC application instantiated on the first MEC host and is received by the MEO entity from a MEC platform manager of the first MEC system via an Mm3 MEC reference point. 
     In Example 8, the subject matter of any of Examples 2-7 includes subject matter where the processing circuitry is configured to: encode the request for the MEC service for transmission to a second federation management entity in the federated MEC network. 
     In Example 9, the subject matter of Example 8 includes subject matter where the second federation management entity is a federation manager of the second MEC system. 
     In Example 10, the subject matter of any of Examples 8-9 includes subject matter where the processing circuitry is configured to receive a notification from the second federation management entity, the notification including identification information of one or more other MEC systems within the federated MEC network that offer the MEC service, and select the second MEC system from the one or more other MEC systems for providing the MEC service based on the notification. 
     In Example 11, the subject matter of Example 10 includes subject matter where the notification further includes identification information of Mobile Edge Orchestrator (MEO) entities associated with the one or more other MEC systems that provide the MEC service. 
     In Example 12, the subject matter of Example 11 includes subject matter where the MEC management entity in the second MEC system is one of the MEO entities identified in the notification, and wherein the identification information comprises an MEO identification (ID) of the MEO entity in the second MEC system. 
     In Example 13, the subject matter of any of Examples 8-12 includes subject matter where the processing circuitry is configured to determine the set of common credentials via a communication exchange with the second federation management entity. 
     In Example 14, the subject matter of Example 13 includes subject matter where the set of common credentials further includes service charging credentials and service monitoring credentials associated with accessing the MEC service in the second MEC system. 
     In Example 15, the subject matter of any of Examples 1-14 includes subject matter where the MEC service is a service-producing MEC application instantiated on the second MEC host. 
     In Example 16, the subject matter of any of Examples 1-15 includes subject matter where the MEC service is a service of a MEC platform of the second MEC host. 
     In Example 17, the subject matter of any of Examples 1-16 includes subject matter where the federation management entity is a federation broker entity configured to manage communications between a federation management entity of the first MEC system and a federation management entity of the second MEC system. 
     Example 18 is at least one machine-readable storage medium comprising instructions stored thereupon, which when executed by processing circuitry of a computing node operable to implement a federation management entity in a federated Multi-Access Edge Computing (MEC) network, cause the processing circuitry to perform operations comprising: detecting a request for a MEC service, the request originating from a MEC application instantiated on a first MEC host within a first MEC system of the federated MEC network, selecting a second MEC system of the federated MEC network, the second MEC system including a second MEC host providing the MEC service; determining a set of common credentials for secure communication between the first MEC system and the second MEC system; and generating a response to the request for communication to the first MEC system, the response including the set of common credentials and identification information of a MEC management entity in the second MEC system, the MEC management entity in the second MEC system providing access to the MEC service. 
     In Example 19, the subject matter of Example 18 includes subject matter where the federation management entity is a federation manager of the first MEC system. 
     In Example 20, the subject matter of Example 19 includes subject matter where executing the instructions further cause the processing circuitry to perform operations comprising: receiving the request for the MEC service from a Mobile Edge Orchestrator (MEO) entity of the first MEC system via a first Mfm-fed MEC federation reference point. 
     In Example 21, the subject matter of Example 20 includes subject matter where the federation management entity is a common federation manager of the first MEC system and the second MEC system. 
     In Example 22, the subject matter of Example 21 includes subject matter where the MEC management entity in the second MEC system is an MEO entity of the second MEC system. 
     In Example 23, the subject matter of Example 22 includes subject matter where executing the instructions further cause the processing circuitry to perform operations comprising: receiving availability information for the MEC service from the MEO entity of the second MEC system via a second Mfm-fed MEC federation reference point. 
     In Example 24, the subject matter of any of Examples 20-23 includes subject matter where the request for the MEC service originates from the MEC application instantiated on the first MEC host and is received by the MEO entity from a MEC platform manager of the first MEC system via an Mm3 MEC reference point. 
     In Example 25, the subject matter of any of Examples 19-24 includes subject matter where executing the instructions further cause the processing circuitry to perform operations comprising: encoding the request for the MEC service for transmission to a second federation management entity in the federated MEC network. 
     In Example 26, the subject matter of Example 25 includes subject matter where the second federation management entity is a federation manager of the second MEC system. 
     In Example 27, the subject matter of any of Examples 25-26 includes subject matter where executing the instructions further cause the processing circuitry to perform operations comprising: receiving a notification from the second federation management entity, the notification including identification information of one or more other MEC systems within the federated MEC network that offer the MEC service, and selecting the second MEC system from the one or more other MEC systems for providing the MEC service based on the notification. 
     In Example 28, the subject matter of Example 27 includes subject matter where the notification further includes identification information of Mobile Edge Orchestrator (MEO) entities associated with the one or more other MEC systems that provide the MEC service. 
     In Example 29, the subject matter of Example 28 includes subject matter where the MEC management entity in the second MEC system is one of the MEO entities identified in the notification, and wherein the identification information comprises an MEO identification (ID) of the MEO entity in the second MEC system. 
     In Example 30, the subject matter of any of Examples 25-29 includes subject matter where executing the instructions further cause the processing circuitry to perform operations comprising: determining the set of common credentials via a communication exchange with the second federation management entity. 
     In Example 31, the subject matter of Example 30 includes subject matter where the set of common credentials further includes service charging credentials and service monitoring credentials associated with accessing the MEC service in the second MEC system. 
     In Example 32, the subject matter of any of Examples 18-31 includes subject matter where the MEC service is a service-producing MEC application instantiated on the second MEC host. 
     In Example 33, the subject matter of any of Examples 18-32 includes subject matter where the MEC service is a service of a MEC platform of the second MEC host. 
     In Example 34, the subject matter of any of Examples 18-33 includes subject matter where the federation management entity is a federation broker entity configured to manage communications between a federation management entity of the first MEC system and a federation management entity of the second MEC system. 
     Example 35 is a federation management system comprising: a plurality of hardware components, including a processing circuitry and network communications circuitry, and at least one memory device including instructions embodied thereon, wherein the instructions, which when executed by the processing circuitry, configure the hardware components to perform operations to: detect a request for a Multi-Access Edge Computing (MEC) service, the request originating from a MEC application instantiated on a first MEC host within a first MEC system of a federated MEC network; select a second MEC system of the federated MEC network, the second MEC system including a second MEC host providing the MEC service; determine a set of common credentials for secure communication between the first MEC system and the second MEC system; and generate a response to the request for communication to the first MEC system via the network communications circuitry, the response including the set of common credentials and identification information of a MEC management entity in the second MEC system, the MEC management entity in the second MEC system providing access to the MEC service. 
     In Example 36, the subject matter of Example 35 includes subject matter where the federation management system is a federation manager of the first MEC system. 
     In Example 37, the subject matter of Example 36 includes subject matter where the instructions configure the hardware components to receive the request for the MEC service from a Mobile Edge Orchestrator (MEO) entity of the first MEC system via a first Mfm-fed MEC federation reference point. 
     In Example 38, the subject matter of Example 37 includes subject matter where the federation management system is a common federation manager of the first MEC system and the second MEC system. 
     In Example 39, the subject matter of Example 38 includes subject matter where the MEC management entity in the second MEC system is an MEO entity of the second MEC system. 
     In Example 40, the subject matter of Example 39 includes subject matter where the instructions configure the hardware components to receive availability information for the MEC service from the MEO entity of the second MEC system via a second Mfm-fed MEC federation reference point. 
     In Example 41, the subject matter of any of Examples 37-40 includes subject matter where the request for the MEC service originates from the MEC application instantiated on the first MEC host and is received by the MEO entity from a MEC platform manager of the first MEC system via an Mm3 MEC reference point. 
     In Example 42, the subject matter of any of Examples 36-41 includes subject matter where the instructions configure the hardware components to encode the request for the MEC service for transmission to a second federation management system in the federated MEC network. 
     In Example 43, the subject matter of Example 42 includes subject matter where the second federation management system is a federation manager of the second MEC system. 
     In Example 44, the subject matter of any of Examples 42-43 includes subject matter where the instructions configure the hardware components to receive a notification from the second federation management system, the notification including identification information of one or more other MEC systems within the federated MEC network that offer the MEC service; and select the second MEC system from the one or more other MEC systems for providing the MEC service based on the notification. 
     In Example 45, the subject matter of Example 44 includes subject matter where the notification further includes identification information of Mobile Edge Orchestrator (MEO) entities associated with the one or more other MEC systems that provide the MEC service. 
     In Example 46, the subject matter of Example 45 includes subject matter where the MEC management entity in the second MEC system is one of the MEO entities identified in the notification, and wherein the identification information comprises an MEO identification (ID) of the MEO entity in the second MEC system. 
     In Example 47, the subject matter of any of Examples 42 46 includes subject matter where the instructions configure the hardware components to determine the set of common credentials via a communication exchange with the second federation management system. 
     In Example 48, the subject matter of Example 47 includes subject matter where the set of common credentials further includes service charging credentials and service monitoring credentials associated with accessing the MEC service in the second MEC system. 
     In Example 49, the subject matter of any of Examples 35-48 includes subject matter where the MEC service is a service-producing MEC application instantiated on the second MEC host. 
     In Example 50, the subject matter of any of Examples 35-49 includes subject matter where the MEC service is a service of a MEC platform of the second MEC host. 
     In Example 51, the subject matter of any of Examples 35-50 includes subject matter where the federation management system is a federation broker entity configured to manage communications between a federation management system of the first MEC system and a federation management system of the second MEC system. 
     Example 52 is a computing node implementing a Multi-Access Edge Computing (MEC) management entity associated with a federated MEC network, the node comprising: memory, and processing circuitry coupled to the memory, the processing circuitry configured to: decode a request for a MEC service, the request originating from a MEC application instantiated on a first MEC host within a first MEC system of the federated MEC network and received from a first MEC platform manager of the first MEC system, encode the request for the MEC service for re-transmission to a federation management entity of the federated MEC network via a Mfm-fed MEC federation reference point; and decode a response to the request, the response received from the federation management entity via the Mfm-fed MEC federation reference point and including a set of common credentials for communication with a second MEC system providing access to the MEC service and identification information of a second MEC management entity in the second MEC system; and perform a discovery operation with the second MEC management entity using the set of common credentials. 
     In Example 53, the subject matter of Example 52 includes subject matter where the processing circuitry is further configured to obtain, from the second MEC management entity, identification information of a second MEC host in the second MEC system, the second MEC host providing the MEC service. 
     In Example 54, the subject matter of Example 53 includes subject matter where the processing circuitry is further configured to encode the request for the MEC service for re-transmission to the second MEC host via the second MEC management entity. 
     In Example 55, the subject matter of Example 54 includes subject matter where the MEC management entity is a Mobile Edge Orchestrator (MEO) entity in the first MEC system, and the second MEC management entity is a second MEO entity in the second MEC system. 
     In Example 56, the subject matter of Example 55 includes subject matter where the processing circuitry is further configured to cause re-transmission of the request for the MEC service to the second MEO entity via a Meo-fed MEC federation reference point. 
     In Example 57, the subject matter of any of Examples 55-56 includes subject matter where the processing circuitry is further configured to cause re-transmission of the request for the MEC service to the second MEC host via the second MEO entity and a MEC platform manager of the second MEC host. 
     In Example 58, the subject matter of any of Examples 52-57 includes subject matter where the MEC service is hosted in a second MEC host in the second MEC system. 
     In Example 59, the subject matter of Example 58 includes subject matter where the MEC service is a service-producing MEC application instantiated on the second MEC host. 
     In Example 60, the subject matter of any of Examples 58-59 includes subject matter where the MEC service is a service of a MEC platform of the second MEC host. 
     In Example 61, the subject matter of Example 60 includes subject matter where the MEC service is accessed by the MEC application at least partially via an Mpp-fed MEC federation reference point between a MEC platform of the first MEC host and the MEC platform of the second MEC host. 
     Example 62 is at least one machine-readable storage medium comprising instructions stored thereupon, which when executed by processing circuitry of a computing node operable to implement a Multi-Access Edge Computing (MEC) management entity in a federated MEC network, cause the processing circuitry to perform operations comprising: decoding a request for a MEC service, the request originating from a MEC application instantiated on a first MEC host within a first MEC system of the federated MEC network and received from a first MEC platform manager of the first MEC system; encoding the request for the MEC service for re-transmission to a federation management entity of the federated MEC network via a Mfm-fed MEC federation reference point; and decoding a response to the request, the response received from the federation management entity via the Mfm-fed MEC federation reference point and including a set of common credentials for communication with a second MEC system providing access to the MEC service and identification information of a second MEC management entity in the second MEC system; and performing a discovery operation with the second MEC management entity using the set of common credentials. 
     In Example 63, the subject matter of Example 62 includes subject matter where executing the instructions further cause the processing circuitry to perform operations comprising: obtaining, from the second MEC management entity, identification information of a second MEC host in the second MEC system, the second MEC host providing the MEC service. 
     In Example 64, the subject matter of Example 63 includes subject matter where executing the instructions further cause the processing circuitry to perform operations comprising: encoding the request for the MEC service for re-transmission to the second MEC host via the second MEC management entity 
     In Example 65, the subject matter of Example 64 includes subject matter where the MEC management entity is a Mobile Edge Orchestrator (MEO) entity in the first MEC system, and the second MEC management entity is a second MEO entity in the second MEC system. 
     In Example 66, the subject matter of Example 65 includes subject matter where executing the instructions further cause the processing circuitry to perform operations comprising: causing re-transmission of the request for the MEC service to the second MEO entity via a Meo-fed MEC federation reference point. 
     In Example 67, the subject matter of any of Examples 65-66 includes subject matter where executing the instructions further cause the processing circuitry to perform operations comprising: causing re-transmission of the request for the MEC service to the second MEC host via the second MEO entity and a MEC platform manager of the second MEC host. 
     In Example 68, the subject matter of any of Examples 62-67 includes subject matter where the MEC service is hosted in a second MEC host in the second MEC system. 
     In Example 69, the subject matter of Example 68 includes subject matter where the MEC service is a service-producing MEC application instantiated on the second MEC host 
     In Example 70, the subject matter of any of Examples 68-69 includes subject matter where the MEC service is a service of a MEC platform of the second MEC host. 
     In Example 71, the subject matter of Example 70 includes subject matter where the MEC service is accessed by the MEC application at least partially via an Mpp-fed MEC federation reference point between a MEC platform of the first MEC host and the MEC platform of the second MEC host. 
     Example 72 is a Multi-Access Edge Computing (MEC) management system comprising: a plurality of hardware components, including a processing circuitry and network communications circuitry, and at least one memory device including instructions embodied thereon, wherein the instructions, which when executed by the processing circuitry, configure the hardware components to perform operations to: decode a request for a MEC service, the request originating from a MEC application instantiated on a first MEC host within a first MEC system of a federated MEC network and received from a first MEC platform manager of the first MEC system; encode the request for the MEC service for re-transmission to a federation management entity of the federated MEC network via a Mfm-fed MEC federation reference point, and decode a response to the request, the response received from the federation management entity via the Mfm-fed MEC federation reference point and including a set of common credentials for communication with a second MEC system providing access to the MEC service and identification information of a second MEC management entity in the second MEC system, and perform a discovery operation with the second MEC management entity using the set of common credentials. 
     In Example 73, the subject matter of Example 72 includes subject matter where the instructions configure the hardware components to obtain, from the second MEC management entity, identification information of a second MEC host in the second MEC system, the second MEC host providing the MEC service. 
     In Example 74, the subject matter of Example 73 includes subject matter where the instructions configure the hardware components to encode the request for the MEC service for re-transmission to the second MEC host via the second MEC management entity. 
     In Example 75, the subject matter of Example 74 includes subject matter where the MEC management entity is a Mobile Edge Orchestrator (MEO) entity in the first MEC system, and the second MEC management entity is a second MEO entity in the second MEC system. 
     In Example 76, the subject matter of Example 75 includes subject matter where the instructions configure the hardware components to cause re-transmission of the request for the MEC service to the second MEO entity via a Meo-fed MEC federation reference point. 
     In Example 77, the subject matter of any of Examples 75-76 includes subject matter where the instructions configure the hardware components to cause re-transmission of the request for the MEC service to the second MEC host via the second MEO entity and a MEC platform manager of the second MEC host. 
     In Example 78, the subject matter of any of Examples 72-77 includes subject matter where the MEC service is hosted in a second MEC host in the second MEC system. 
     In Example 79, the subject matter of Example 78 includes subject matter where the MEC service is a service-producing MEC application instantiated on the second MEC host. 
     In Example 80, the subject matter of any of Examples 78-79 includes subject matter where the MEC service is a service of a MEC platform of the second MEC host. 
     In Example 81, the subject matter of Example 80 includes subject matter where the MEC service is accessed by the MEC application at least partially via an Mpp-fed MEC federation reference point between a MEC platform of the first MEC host and the MEC platform of the second MEC host. 
     Example 82 is at least one machine-readable medium including instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations to implement any of Examples 1-81. 
     Example 83 is an apparatus comprising means to implement any of Examples 1-81. 
     Example 84 is a system to implement any of Examples 1-81. 
     Example 85 is a method to implement any of Examples 1-81. 
     Example 86 is a multi-tier edge computing system, comprising a plurality of edge computing nodes provided among on-premise edge, network access edge, or near edge computing settings, the plurality of edge computing nodes configured to perform any of the methods of Examples 1-81. 
     Example 87 is an edge computing system, comprising a plurality of edge computing nodes, each of the plurality of edge computing nodes configured to perform any of the methods of Examples 1-81 
     Example 88 is an edge computing node, operable as a server hosting the service and a plurality of additional services in an edge computing system, configured to perform any of the methods of Examples 1-81. 
     Example 89 is an edge computing node, operable in a layer of an edge computing network as an aggregation node, network hub node, gateway node, or core data processing node, configured to perform any of the methods of Examples 1-81. 
     Example 90 is an edge provisioning, orchestration, or management node, operable in an edge computing system, configured to implement any of the methods of Examples 1-81. 
     Example 91 is an edge computing network, comprising networking and processing components configured to provide or operate a communications network, to enable an edge computing system to implement any of the methods of Examples 1-81. 
     Example 92 is an access point, comprising networking and processing components configured to provide or operate a communications network, to enable an edge computing system to implement any of the methods of Examples 1-81. 
     Example 93 is a base station, comprising networking and processing components configured to provide or operate a communications network, configured as an edge computing system to implement any of the methods of Examples 1-81. 
     Example 94 is a road-side unit, comprising networking components configured to provide or operate a communications network, configured as an edge computing system to implement any of the methods of Examples 1-81. 
     Example 95 is an on-premise server, operable in a private communications network distinct from a public edge computing network, configured as an edge computing system to implement any of the methods of Examples 1-81. 
     Example 96 is a 3GPP 4G/LTE mobile wireless communications system, comprising networking and processing components configured as an edge computing system to implement any of the methods of Examples 1-81. 
     Example 97 is a 5G network mobile wireless communications system, comprising networking and processing components configured as an edge computing system to implement any of the methods of Examples 1-81. 
     Example 98 is an edge computing system configured as an edge mesh, provided with a microservice cluster, a microservice cluster with sidecars, or linked microservice clusters with sidecars, configured to implement any of the methods of Examples 1-81. 
     Example 99 is an edge computing system, comprising circuitry configured to implement services with one or more isolation environments provided among dedicated hardware, virtual machines, containers, or virtual machines on containers, the edge computing system configured to implement any of the methods of Examples 1-81. 
     Example 100 is an edge computing system, comprising networking and processing components to communicate with a user equipment device, client computing device, provisioning device, or management device to implement any of the methods of Examples 1-81. 
     Example 101 is networking hardware with network functions implemented thereupon, operable within an edge computing system, the network functions configured to implement any of the methods of Examples 1-81. 
     Example 102 is acceleration hardware with acceleration functions implemented thereupon, operable in an edge computing system, the acceleration functions configured to implement any of the methods of Examples 1-81 
     Example 103 is storage hardware with storage capabilities implemented thereupon, operable in an edge computing system, the storage hardware configured to implement any of the methods of Examples 1-81 
     Example 104 is computation hardware with compute capabilities implemented thereupon, operable in an edge computing system, the computation hardware configured to implement any of the methods of Examples 1-81. 
     Example 105 is an edge computing system configured to implement services with any of the methods of Examples 1-81, with the services relating to one or more of: compute offload, data caching, video processing, network function virtualization, radio access network management, augmented reality, virtual reality, autonomous driving, vehicle assistance, vehicle communications, industrial automation, retail services, manufacturing operations, smart buildings, energy management, internet of things operations, object detection, speech recognition, healthcare applications, gaming applications, or accelerated content processing. 
     Example 106 is an apparatus of an edge computing system comprising: one or more processors and one or more computer-readable media comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform any of the methods of Examples 1-81. 
     Example 107 is one or more computer-readable storage media comprising instructions to cause an electronic device of an edge computing system, upon execution of the instructions by one or more processors of the electronic device, to perform any of the methods of Examples 1-81. 
     Example 108 is a computer program used in an edge computing system, the computer program comprising instructions, wherein execution of the program by a processing element in the edge computing system is to cause the processing element to perform any of the methods of Examples 1-81. 
     Example 109 is an edge computing appliance device operating as a self-contained processing system, comprising a housing, case, or shell, network communication circuitry, storage memory circuitry, and processor circuitry adapted to perform any of the methods of Examples 1-81. 
     Example 110 is an apparatus of an edge computing system comprising means to perform any of the methods of Examples 1-81. 
     Example 111 is an apparatus of an edge computing system comprising logic, modules, or circuitry to perform any of the methods of Examples 1-81. 
     Example 112 is an edge computing system, including respective edge processing devices and nodes to invoke or perform any of the operations of Examples 1-81, or other subject matter described herein. 
     Example 113 is a client endpoint node, operable to invoke or perform the operations of any of Examples 1-81, or other subject matter described herein. 
     Example 114 is an aggregation node, network hub node, gateway node, or core data processing node, within or coupled to an edge computing system, operable to invoke or perform the operations of any of Examples 1-81, or other subject matter described herein. 
     Example 115 is an access point, base station, road-side unit, street-side unit, or on-premise unit, within or coupled to an edge computing system, operable to invoke or perform the operations of any of Examples 1-81, or other subject matter described herein. 
     Example 116 is an edge provisioning node, service orchestration node, application orchestration node, or multi-tenant management node, within or coupled to an edge computing system, operable to invoke or perform the operations of any of Examples 1-81, or other subject matter described herein. 
     Example 117 is an edge node operating an edge provisioning service, application or service orchestration service, virtual machine deployment, container deployment, function deployment, and compute management, within or coupled to an edge computing system, operable to invoke or perform the operations of any of Examples 1-81, or other subject matter described herein. 
     Example 118 is an edge computing system including aspects of network functions, acceleration functions, acceleration hardware, storage hardware, or computation hardware resources, operable to invoke or perform the use cases discussed herein, with use of any Examples 1-81, or other subject matter described herein. 
     Example 119 is an edge computing system adapted for supporting client mobility, vehicle-to-vehicle (V2V), vehicle-to-everything (V2X), or vehicle-to-infrastructure (V2I) scenarios, and optionally operating according to European Telecommunications Standards Institute (ETSI) Multi-Access Edge Computing (MEC) specifications, operable to invoke or perform the use cases discussed herein, with use of any of Examples 1-81, or other subject matter described herein. 
     Example 120 is an edge computing system adapted for mobile wireless communications, including configurations according to a 3GPP 4G/LTE or 5G network capabilities, operable to invoke or perform the use cases discussed herein, with use of any of Examples 1-81, or other subject matter described herein. 
     Example 121 is an edge computing node, operable in a layer of an edge computing network or edge computing system as an aggregation node, network hub node, gateway node, or core data processing node, operable in a close edge, local edge, enterprise edge, on-premise edge, near edge, middle, edge, or far edge network layer, or operable in a set of nodes having common latency, timing, or distance characteristics, operable to invoke or perform the use cases discussed herein, with use of any of Examples 1-81, or other subject matter described herein. 
     Example 122 is networking hardware, acceleration hardware, storage hardware, or computation hardware, with capabilities implemented thereupon, operable in an edge computing system to invoke or perform the use cases discussed herein, with use of any of Examples 1-81, or other subject matter described herein. 
     Example 123 is an apparatus of an edge computing system comprising: one or more processors and one or more computer-readable media comprising instructions that, when deployed and executed by the one or more processors, cause the one or more processors to invoke or perform the use cases discussed herein, with use of any of Examples 1-81, or other subject matter described herein. 
     Example 124 is one or more computer-readable storage media comprising instructions to cause an electronic device of an edge computing system, upon execution of the instructions by one or more processors of the electronic device, to invoke or perform the use cases discussed herein, with the use of any of Examples 1-81, or other subject matter described herein. 
     Example 125 is an apparatus of an edge computing system comprising means, logic, modules, or circuitry to invoke or perform the use cases discussed herein, with the use of any of Examples 1-81, or other subject matter described herein. 
     Although these implementations have been described with reference to specific exemplary aspects, it will be evident that various modifications and changes may be made to these aspects without departing from the broader scope of the present disclosure. Many of the arrangements and processes described herein can be used in combination or parallel implementations to provide greater bandwidth/throughput and to support edge services selections that can be made available to the edge systems being serviced. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense. The accompanying drawings that form a part hereof show, by way of illustration, and not of limitation, specific aspects in which the subject matter may be practiced. The aspects illustrated are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed herein. Other aspects may be utilized and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. This Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various aspects is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled. 
     Such aspects of the inventive subject matter may be referred to herein, individually and/or collectively, merely for convenience and without intending to voluntarily limit the scope of this application to any single aspect or inventive concept if more than one is disclosed. Thus, although specific aspects have been illustrated and described herein, it should be appreciated that any arrangement calculated to achieve the same purpose may be substituted for the specific aspects shown. This disclosure is intended to cover any adaptations or variations of various aspects. Combinations of the above aspects and other aspects not specifically described herein will be apparent to those of skill in the art upon reviewing the above description.