Draft: draft-hong-t2trg-iot-edge-computing

Commentary: Main change : Merged 2 sections ( IoT Integrated with Edge Computing and architecture section ) into a new " model " section . Updated the architecture diagram into a model diagram including the logical functions proposed by Dirk . Heavily reworded / simplified text from the previous 2 sections - I tried to keep relevant info , but removed what was redundant with the existing challenges section . The architectures ( gateway vs. distributed ) are shortly listed above the figure , but the rest aims to be general . Some renaming for your consideration ( feel free to ignore / change ): new draft title : IoT Edge Computing Challenges , Model and State - of - Art Review challenges section ( " new IoT challenges " could seem a bit general ): Challenges for IoT and Impacts of Edge Computing Minor : edits in abstract 
    , Jungha , and Dirk agreed via e - mail . Since the new version has been sent to the Datatracker , I will merge .
This document describes new challenges such as strict latency, uplink
cost, uninterrupted services, privacy and security, for IoT services
originated from the IoT environmental changes.  In order to address
those new challenges, the integration of Edge computing and IoT has
been emerged as a promising solution.  This document discribes the
concept of IoT integrated with Edge computing as well as the state-
of-the-art of IoT Edge computing.  It also proposes an architecture
of IoT Edge computing.  The direction of Edge computing for IoT
should be discussed in the IETF/IRTF.
This document describes new challenges such as strict latency, uplink
cost, uninterrupted services, privacy and security, for IoT services
originated from the IoT environmental changes.  In order to address
those new challenges, the integration of Edge computing and IoT has
emerged as a promising solution.  This document describes the concept
of IoT integrated with Edge computing as well as the state-of-the-art
of IoT Edge computing.  It also proposes a general model for IoT Edge
computing.  The direction of Edge computing for IoT should be
discussed in the IETF/IRTF.
Many IoT devices such as sensors, data collectors, actuators,
controllers, etc. have very limited hardware resources and cannot
rely solely on their limited resources to meet all their computing
and/or storage needs.  They require reliable, uninterrupted services
to augment their capabilities in order to fulfill their application
tasks.  This is hard and partly impossible to achieve with cloud
services for systems such as vehicles, drones, or oil rigs that have
intermittent network connectivity.
Many IoT devices such as sensors, data collectors, actuators,
controllers, etc. have very limited hardware resources and cannot
rely solely on their limited resources to meet all their computing
and/or storage needs.  They require reliable, uninterrupted services
to augment their capabilities in order to fulfill their application
tasks.  This is hard and partly impossible to achieve with cloud
services for systems such as vehicles, drones, or oil rigs that have
intermittent network connectivity.  Example of related challenges
include support for IoT device and edge computing node mobility, as
well as software instance migration.
As we described at previous sections, the above motivation for IoT
Edge computing could directly be benefits of Edge computing in the
IoT environment.  The above motivation for IoT Edge computing is
mainly related to IoT data and other motivation for IoT Edge
computing can exist as other aspects of networking and communication.
In spite of its benefits, Edge computing in IoT services has
challenges such as programmability, naming, data abstraction, service
management, privacy and security and optimization metrics.
Edge computing can support IoT services independently of Cloud
computing.  However, Edge computing is increasingly connected to
Cloud computing in most IoT systems for processing and storaging
data.  Thus, the relationship of Edge Computing to Cloud Computing is
also another challenge of Edge Computing in IoT ISO_TR.
As an aspect of IoT, Edge computing can provide many capabilities for
IoT services because IoT systems are based on sensors and actuator
devices in edge area and IoT data generated from sensors and actuator
devices are gathered through a gateway ISO_TR.  Besides on IoT data,
other functions such as computing, control and network functions are
also very remarkable to support IoT services.  In this document, we
will first concentrate on IoT data's aspect since the benefit of Edge
computing with IoT data is very big in use cases.
As tremendous IoT sensors, IoT actuators, and IoT devices are
connected to the Internet, IoT data volume from these things are
expected to increase explosively.  And it is expected that much of
this high volume of IoT data is produced and/or consumed within edge/
local networks, not to traverse through cloud networks.  Until now,
most IoT data generated by IoT things is transferred and accumulated
in a remote server and storage of IoT data in a remote server is
expensive in transmission and storage.  To mitigate the cost of
transmission and storage, it is required to divide IoT data into two
types of data; one is stored in edge/local networks and the other is
stored in cloud networks.  The effect of Edge computing is revealed
with the handling IoT data in edge/local networks.
Until now, most network equipment such as routers, gateways, and
switches just forward data delivered from other network devices
without reading or modifying the content.  In end-to-end
communication, data is acknowledged and proceed at a final
corresponding node.  This is a typical usage of cloud computing and a
client-server communication.  But, in the IoT environment, some IoT
data will be transferred to a cloud network and some will be
delivered to an edge node.  The main reason of this separation is to
provide real-time processing and security enhancement in IoT.
Although there are many new technologies to reduce the delay and
transmission time, it is not easy to guarantee real-time processing.
The typical use case of this requirement is industrial Internet and
smart factory.  Even though there are also several solutions to
provide security in IoT, the more basic rule is not to expose the
privacy data to public networks.  If we separate IoT data into
private and non-private data, and keep private data within an edge/
local network not to expose them in a public network, the security
and privacy in IoT cna be addressed by the separation.
If it is possible to separate IoT data in edge/local networks and
cloud networks, Edge computing can do more functions with IoT data in
edge/local networks.  Because Edge computing has the capabilities to
handle IoT data in edge/local networks, it is also possible to
analyze IoT data to provide enhanced IoT services such as
intelligence.  To analyze IoT data in an edge/local network, it is
required to have comparatively processing performance and this
requirement is not obstacle to deploy Edge computing due to the
development of H/W and S/W.
If we consider new challenges of IoT services, not only the big
volume of IoT data but also the massive number of IoT things can be a
critical problem.  Even though, we acknowledge this future problem,
the Internet architecture originally has the capability of
scalability and it will mitigate scalability issue in the IoT
environment.  But, we cannot estimate the number of IoT things in the
future and we cannot guarantee the Internet architecture still
sustain the scalability issue in the IoT environment.  Edge computing
will separate the scalability domain into edge/local networks and
outside network (e.g., cloud networks) and this separation of
scalability domain can provide more efficient way to tackle the
massive number of IoT things.
Because Edge computing can handle IoT data in an edge area and store
the IoT data in an edge node, and proceed IoT data if it is needed,
it can also separate the management domain into two parts.  Edge
Computing can concentrate on management of IoT things in an edge area
and cooperate with the management of other outside networks.
When we consider the implementation and deployment of Edge computing,
it can be mainly referred to an IoT Gateway.  The role of an IoT
Gateway is to provide multiple accesses to the heterogeneous IoT
devices/sensors, handling IoT data and delivering the IoT data to the
final destinations such as cloud networks.  Similar to an IoT
Gateway, an Edge computing architecture as an edge computing node
provides downside connectivity to IoT sensors and devices (southbound
connectivity) and upside connectivity to cloud networks (northbound
connectivity).  Also, the architecture provides the function of data
storage.  Beside these functions, the Edge computing architecture
should provide the computing functions, such as data processing, data
analyzing, and additional function of intelligence.
It is expected that the Edge computing architecture will play an
important role to deploy new IoT services with integration to big
data and AI services.
A single IoT gateway, or a hierarchy of IoT gateways, typically
connected to the cloud (e.g., to extend the traditionally cloud-
based management of IoT devices and data to the edge).  A common
role of an IoT Gateway is to provide access to an heterogeneous
set of IoT devices/sensors; handle IoT data; and deliver IoT data
to its final destination in a cloud network.
A set of distributed computing nodes, e.g. embedded in switches,
routers, edge cloud servers or mobile devices.  In the future,
some IoT end devices may have enough computing capabilities to
participate in such distributed systems.
The edge computing domains is interconnected with IoT end devices
(southbound connectivity) and possibly with a remote/cloud network
(northbound connectivity).  Edge computing nodes provide multiple
logical functions such as finding resources, authentication, storage/
processing and management.
A northbound interface is provided by a gateway component to a remote
network, e.g. a cloud, home or enterprise network.  These components
may not exist in standalone scenarios, where edge computing is
provided locally without a connection to a remote network.  The
northbound interface is a data plane interface.  Nevertheless, the
remote network may also host an edge cloud manager function.
Edge computing domain management includes management of resources and
functions in the edge computing domain.  Management of IoT end
devices and IoT data may be included or may be part of the edge
computing logical functions (OPEN QUESTION).  The management function
can provides SaaS, PaaS, IaaS service APIs to an edge computing
manager.  The edge management role may be taken by an entity in the
cloud, but it may also be a local entity, or even be non-existent
(during normal operation) in autonomic systems.
Management, e.g. of IoT end devices and data.
With regard to the high level challenges listed in sec-challenges,
data storage and processing at the edge is a major aspect of IoT edge
computing.  Data may therefore need to be classified (e.g. in terms
of privacy, importance, validity, etc.).  Data analysis such as
performed in AI/ML tasks performed at the edge may benefit from
specialized hardware support on computing nodes.  IoT edge computing
will face detailed challenges in term of, for example,
programmability, naming, data abstraction and service management.
Furthermore, while edge computing can support IoT services
independently of cloud computing, it is increasingly connected to
cloud computing in most IoT systems: thus, the relationship of IoT
edge Computing to cloud Computing is another potential challenge
ISO_TR.
IoT end devices can be sensors, actuators, or more generally IoT
things.  Not only the big volume of IoT data but also the massive
number of IoT end devices are the cause of a massive scalability
issue in future IoT environments.  To address this challenge edge
computing separates the scalability domain into edge/local networks
and remote network.
Edge computing nodes communicate between themselves and with end
devices over an underlying network.  There is therefore a need for
the edge computing domain to directly or indirectly control those
network functions.