Patent Publication Number: US-2021185127-A1

Title: Logical Observation Sensors For Airborne And Spaceborne Nodes

Description:
RELATED APPLICATIONS 
     This patent application is a continuation of, and claims priority to, U.S. patent application Ser. No. 16/182,921 that was filed on Nov. 7, 2018, and is entitled “LOGICAL OBSERVATION SENSORS FOR AIRBORNE AND SPACEBORNE NODES,” which is hereby incorporated by reference into this patent application. 
    
    
     BACKGROUND 
     Satellites and aircraft can be deployed to provide various task-based operations, such as military and civilian observation operations, communications operations, navigation operations, weather operations, and research operations. Satellites and aircraft can include various sensors and communication equipment that are used to perform these desired tasks. For example, a weather satellite may include one or more cameras or imaging sensors that can be used to take images of Earth, and communication equipment that can be used to communicate the images to a control system on Earth. An aircraft drone might include cameras for imaging portions of the Earth and relaying those images to a control station. Although satellites and aircraft can both be configured to perform specialized operations, this equipment is typically custom-made to the particular tasks and is expensive to create and deploy, especially for organizations that may not be able to justify the use of an entire custom satellite or aircraft. As a result, organizations may avoid the use of this technology, limiting its use. 
     OVERVIEW 
     Systems, methods, and software described herein provide enhancements for the deployment and management of sensor resources across spaceborne, airborne, and ground-based physical nodes. In one implementation, a method includes collecting sensor data from physical sensors distributed over a geographic region, and establishing logical sensors based at least on requirements indicated by data requestors. The method includes allocating selected portions of the sensor data to the logical sensors to form composite sensor data based on locations monitored by the physical sensors that correspond to the requirements, and providing the composite data in one or more data streams to the data requestors as originating from the logical sensors. In some examples, a first physical sensor captures first sensor data corresponding to a first portion of an object of interest, and a second physical sensor captures second sensor data corresponding to a second portion of the object of interest. Resultant composite sensor data can comprise the first sensor data and the second sensor data which is provided to applications or data requestors as originating from a single logical sensor. 
     This Overview is provided to introduce a selection of concepts in a simplified form that are further described below in the Technical Disclosure. The Overview is not intended to identify key features or essential features of the claimed subject matter, nor should it be used to limit the scope of the claimed subject matter. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Many aspects of the disclosure can be better understood with reference to the following drawings. While several implementations are described in connection with these drawings, the disclosure is not limited to the implementations disclosed herein. On the contrary, the intent is to cover all alternatives, modifications, and equivalents. 
         FIG. 1  illustrates a system to manage logical sensor data from physical sensors to an implementation. 
         FIG. 2  illustrates an operation of a system to manage logical sensors according to an implementation. 
         FIG. 3  illustrates an expanded view of a physical node according to an implementation. 
         FIG. 4  illustrates an operational scenario of apportioning sensor data to logical sensors according to an implementation. 
         FIG. 5  illustrates an operational scenario of apportioning sensor data to logical sensors according to an implementation. 
         FIG. 6  illustrates an operational scenario of apportioning sensor data to logical sensors according to an implementation. 
         FIG. 7  illustrates a physical node computing system according to an implementation. 
     
    
    
     DETAILED DESCRIPTION 
       FIG. 1  illustrates a system  100  to manage logical sensor data from physical sensors to an implementation. System  100  includes physical nodes (nodes)  110 - 111  and  130 - 132 , and control system  170 . Physical nodes  110 - 111  are representative of spaceborne nodes that may comprise satellites, shuttles, capsules, or other similar spaceborne entities. Physical nodes  131 - 132  are representative of atmospheric nodes, such as aircraft, airplanes, drones, balloons, or some other similar airborne objects capable of data processing and/or gathering sensor observation data. Physical nodes  131 - 132  may be mobile or tethered. For example, a balloon device might be mobile, tethered, or both. Physical node  130  is representative of a surface-based data observation node. In some examples, physical node  130  may be mobile and comprise a car, truck, ship, vessel, vehicle, train, or other surface or subsurface-going vessel. In other examples, physical node  130  may be stationary and comprise a building, antenna array, tower, or other structure. Any number of satellite nodes, atmospheric nodes, and surface nodes may be employed. 
     In operation, physical nodes  110 - 111 , and  130 - 132  are deployed to provide various operations for different tenants of system  100 . These operations may include military, commercial, government, and civilian observation or monitoring operations, communications operations, navigation operations, weather operations, and research operations. In implementing the operations for the various tenants, control system  170  may provide an interface to the tenants, permitting the tenants to define target requirements and applications for the required operations. In some implementations, the target requirements may comprise processing resource requirements (type of processor, quantity of cores, and the like), storage requirements (quantity of storage, type of storage, and the like), communication requirements (bandwidth, throughput, target frequencies, and the like), sensor requirements (sensor type, sensor quality, and the like), geographic location requirements (defined objects and/or geographic regions of interest), or some other similar requirement. From the target requirements, an application may be developed that uses the target requirements to provide the desired functionality. This application may be deployed as a virtual machine, container, or some other virtualized endpoint that can execute on one or more physical nodes. These logical nodes may be allocated processing resources, memory resources, storage resources, communication resources, and sensor resources, wherein the sensor resources that are made available to the logical node may comprise one or more logical sensors that provide the required data for processing by the application. As an example, a tenant may generate an application that requires at least a minimum quality or types of imaging sensors, at least a minimum quantity of processing resources, and at least a minimum amount of storage. An example application may be used to monitor vehicular traffic within a defined geographic region, where the application may use the imaging data to identify particular traits in the traffic and report the information to control system  170 . 
     In some implementations, when the applications are deployed in system  100 , the applications may be allocated logical sensors rather than physical sensors. These logical sensors may be allocated data from one or more physical sensors based on the requirements for the application. As an example, in system  100 , physical sensor  162  may collect sensor data, wherein the sensor data may correspond imaging data, motion data, light data, or some other similar type of sensor data. As the data is collected, physical node  111 , or some other physical node in system  100 , may apportion the sensor data to logical sensors  164 . Once apportioned, physical node  111  may provide one or more data streams to data requestors as originating from logical sensors  164 . As an example, an application operating in a first logical node (container, virtual machine, or some other logical node executed by one or more physical nodes) may be allocated a first logical sensor in logical sensors  164 , while a second application operating in a second logical node may be allocated a second logical sensor in logical sensors  164 . As a result, rather than obtaining data directly from the physical node, a management platform operating on the physical nodes of system  100  may allocate data from the physical sensors to various logical sensors, permitting logical nodes executing in system  100  to obtain data from specific logical sensors allocated to the logical nodes. 
     In some implementations, the logical sensors may be provided with a portion of the sensor data that is collected from physical sensor  162 . As an example, a logical node may be interested in object of interest  141  and none of the other data collected from physical sensor  162 . To accommodate the requirements of the logical node, the management platform of physical node  111  may identify pertinent portions of sensor data for physical sensor  162  and allocate the portions to a logical sensor for the logical node. Once allocated or apportioned to the logical sensor, the associated logical node may obtain the data via a data stream associated with the particular logical sensor. Thus, if physical sensor  162  represented an imaging sensor, physical node  111  may identify portions of the imaging data from the imaging sensor that correspond to object of interest  141  and allocate the portions to the logical sensor associated with the logical node. 
     In some examples, logical sensors may be apportioned composite data from multiple physical sensors as a single logical sensor. As an example from system  100 , node  111  and node  132  may obtain sensor data related to object of interest  141 . Rather than providing the data as separate sensors, one or more of the physical nodes of system  100  may process the sensor data from multiple sensors to generate composite sensor data that can be provided as a single logical sensor to a particular application. Thus, if an application operating in a logical node required a sensor that provides imaging data for all of object of interest  141 , imaging data from multiple physical sensors may be required to support the single image. Thus, if physical node  110  included an imaging sensor that collected imaging data for a first portion of object of interest  141  and physical node  111  included a second imaging sensor that collected imaging data for a second portion of object of interest  141 , the management platform may be used to process the imaging data from the two sensors to generate composite data. When the composite imaging data is generated, the composite imaging data may be allocated to a logical sensor, wherein the application can access data from the logical sensor in the same manner as a physical sensor. Accordingly, although a single sensor may be incapable of providing the required data for a logical node, a management platform may provide a logical sensor capable of providing the required sensor data. 
     In some implementations, prior to apportioning the data to the logical sensors  164 , the management platform of physical node  111  may process the data to provide specific data. This processing of the data may include modifying the format of the data from a first format to a second format, may comprise selecting portions of the sensor data, may comprise compiling data from multiple physical sensors into a composite data, or some other similar processing of the data prior to apportioning the data to a logical sensor. As an example, an imaging sensor may collect data in a first format, but a logical node may require a second format to provide required operations. To generate the sensor data in the second format, the management platform, which may comprise its own applications and logical nodes, may obtain the data from the physical sensor, execute processes to convert the data from the first format to the second format, and apportion the data to at least one logical sensor. After the data is apportioned to the logical sensor, any requestor associated with the at least one logical sensor, such as a logical node or other application, may request and obtain the data from the logical sensor. 
     In some examples, the physical sensors that are associated with the logical sensors may change over time. In particular, while a logical node may be assigned a logical sensor to provide sensor operations on particular objects of interest, the physical nodes in system  100  may be mobile requiring a change to the physical nodes that support the particular object of interest. As an example, physical node  110  may initially provide the physical sensor data required for a logical sensor, however, due to the orbit of physical node  110 , the physical sensor data required for the logical sensor may be transitioned to physical node  111 . In the transition, the management platform provided in system  100  may identify the transition event and determine one or more alternative physical sensors capable of supporting the data for the logical sensor. 
       FIG. 2  illustrates an operation  200  of a system to manage logical sensors according to an implementation. The processes of operation  200  are referenced parenthetically in the paragraphs that follow with reference to elements of system  100  of  FIG. 1 . Operation  200  is described as executing in physical node  111 , however, other physical nodes in system  100  may provide similar operations and may provide the operations as a single entity in some examples. 
     As depicted operation  200  includes collecting ( 201 ) sensor data from at least one physical sensor. The at least one physical sensor may comprise one or more motion sensors, imaging sensors, heat and/or thermal sensors, electromagnetic spectrum sensors, laser sensors, lidar or radar sensors, proximity sensors, seismic sensors, meteorological sensors, chemical/radiation/nuclear/electronic/signal sensors, or some other similar sensors. As the data is collected from the at least one physical sensor, operation  200  further apportions ( 202 ) the sensor data among one or more logical sensors associated with the at least one physical sensor. Referring to the example of system  100 , physical node  111  obtains sensor data from physical sensor  162 . As the sensor data is obtained, physical node  111  and a management platform operating thereon may determine one or more logical sensors that are associated with the physical sensor. Once identified, the data may be apportioned to each of the logical sensors as required. In some implementations, each of the logical sensors may obtain the same data, such as the same image. In other implementations, one or more of the logical sensors may obtain different portions of the sensor data, such as different portions of the images from one or more imaging sensors. 
     In some implementations, prior to apportioning the sensor data to the various logical sensors, physical node  111  or another physical node in system  100  may process the data from the at least one sensor prior to allocating the data to the logical sensors. This processing may include identifying a subset of the sensor data that is relevant to the logical sensor, generating composite data from multiple physical sensors, converting a format of the data from the physical sensor to a format associated with the logical sensor, or some other similar operation associated with the data from the physical sensor. Once the sensor data is processed, in some examples using different pre-processing operations for each of the logical sensors, the processed sensor data may be apportioned to logical sensors  164 . As an example, a logical sensor in logical sensors  164  may require a data format that is different than the format that is provided by physical sensor  162 . Consequently, physical node  162  may process the data obtained from physical sensor  162  to generate second data for the logical sensor and may allocate the second data as the sensor data for the logical sensor. 
     Once the sensor data is apportioned to logical sensors  164 , operation  200  further provides ( 203 ) one or more data streams to data requestors as originating from the logical sensors. In some implementations, the data requestors may comprise applications that are deployed in system  100 , wherein the applications may execute in logical nodes each allocated processing resources, storage resources, communication resources, and sensor resources. In the present implementation, the sensor resources that are allocated to each of the logical nodes include at least one logical sensor that is used to provide data for processing and/or storage by the application. The logical node may comprise a container, a virtual machine, or another virtual computing element that can be executed using resources from one or more physical nodes. In obtaining data for the application in the logical node, the application may generate requests for the at least one logical sensor that is allocated to the logical node and system  100  may provide a data stream with the required data to the requesting application. 
     As an example, a container executing on physical node  111  may generate a request to obtain data from a logical sensor of logical sensors  164  that corresponds to the container. In response to the request, a data stream with the apportioned data for the logical sensor may provide data for the requesting application. In this manner, a single physical sensor may provide data to multiple logical sensors or, likewise, multiple physical sensors may be used to provide data to a single logical sensor. 
     In at least one implementation, in apportioning the sensor data to the various logical sensors, physical node  111  may persist (store or cache) a portion of the sensor data, such that the sensor data may be time-shifted for the logical node associated with the logical sensor. In caching the data, applications that do not require real-time processing of the data may access the data later. Thus, while a logical node may not currently be executing when the data is obtained, the logical node may process the persistent sensor data from the logical sensor in a similar manner to the real-time processing applications. 
     In some examples, similar to persisting the data for a logical sensor, the physical nodes of the system may store the raw sensor data such that it can be made available as an application as a logical sensor at a later time. This sensor data may be stored locally at the collecting physical node, may be stored on another physical node, or may be stored on a ground storage system for the collecting sensors. As an illustrative example, an application that is either currently executing or executing at a future time, may provide a request for data that was gathered during an earlier period. Rather than processing the data directly from storage, a logical sensor may be generated or allocated to the application, such that the application may process the data as though the data is obtained in real-time. Thus, although data may be stored from an earlier period, various applications may request access to the data, and be provided with the data via a logical sensor as though the data is collected in real-time. In providing the stored data to the requesting application, the management platform may process the data prior to providing the data to the application. This processing of the data may include modifying a format of the data for the logical sensor, identifying objects of interest in the data and providing sensor data associated with the objects of interest, generating composite data from multiple sensors, or providing some other similar processing operation on the data prior to apportioning the data to the allocated logical sensor. 
     In some implementations, a first logical node may provide operations on sensor data prior to providing the data to a second logical node. For example, a first logical node associated with a first logical sensor may obtain data from the first logical sensor using a first data stream. The first logical node may then process the sensor data and generate second sensor data that can be apportioned to one or more additional logical sensors. In processing the data, the first logical node may convert the data from a first format to a second format, identify relevant portions of interest in the sensor data to be provided as the second data, or provide some other similar operation with respect to the data. As an example, first imaging sensor data may be obtained from physical sensor  111  and apportioned to a first logical node and sensor, where the first logical node may process the imaging data to generate second imaging data. This second imaging data may comprise the imaging data in a different format, a particular portion of the imaging data that is pertinent as second imaging data, or some other similar processing of the imaging data, including combinations thereof. As the second imaging data is generated, the first logical node may apportion the data to one or more secondary logical sensors that are associated with secondary logical nodes. Advantageously, the secondary logical nodes may be provided with preprocessed data, but may interact with and request the data as though the data were a sensor. In one example, this could permit multiple logical nodes that each expect a different portion or subset of the original data to obtain the required data through operations of another logical node. 
       FIG. 3  illustrates an expanded view  300  of physical node  111  of  FIG. 1  according to an implementation. Physical node  111  can be an example of any of nodes  110 - 111  and  130 - 132  of  FIG. 1 , although variations are possible. Physical node  111  includes data processing segment  301 , control segment  302 , and interface segment  303 . Data processing segment includes processing system  330  and storage system  332  that stores applications  341 - 344  that execute via management platform  346 . Control segment includes flight control system  311  and propulsion navigation  310 . Interface segment  303  includes sensors  320  and communication interface  321 . 
     As described herein, physical nodes in an observation system may provide a platform for various tenants to deploy and execute applications that provide various operations. These operations may include military and civilian observation operations, communications operations, navigation operations, weather operations, and research operations. As depicted in expanded view  300 , data processing system  301  includes processing system  330  and storage system  332 , where storage system  332  stores management platform  346  (operating system, hypervisor, or the like), and applications  341 - 344 . Applications  341 - 344  execute on top of management platform  346  and may operate inside of one or more logical nodes, where the logical nodes may comprise containers, virtual machines, or some other similar virtualized element. In some examples, applications  341 - 344  may use logical sensors to obtain required sensor data for the applications. In particular, the logical nodes that support applications  341 - 344  may each be allocated one or more logical sensors that can provide imaging sensor data, motion sensor data, seismological sensor data, or some other similar sensor data. 
     In allocating the sensor data to each of the logical sensors, management platform  346  may be used to obtain data from at least one physical sensor of sensors  320  and/or other physical sensors from other physical nodes of system  100 . As the data is received, management platform  346  may apportion the sensor data among one or more logical sensors associated with the at least one physical sensor. A logical sensor may be apportioned all of the data from the at least one physical sensor, may be apportioned a subset of the data from the at least one physical sensor, may be apportioned processed data from the at least one physical sensor, or may be apportioned any other portion of the data from the at least one physical sensor. The allocation of the sensor data to each of the logical sensors may be based on the requirements and/or preferences of each of the applications associated with the logical sensors. These requirements may comprise objects or geographic areas of interest, imaging or other data formats, or some other similar requirement for the application. As a result, a first portion of the sensor data may be allocated to a first logical sensor, while a second portion of the sensor data may be allocated to a second logical sensor. 
     In some implementations, when the sensor data is obtained from the at least one physical sensor, management platform  346  may be responsible for identifying the logical sensors that correspond to the obtained data. This determination may be based on the activity states of the logical nodes and applications (e.g., executing, paused, etc.), may be based on the geolocation from which the data was gathered, may be based on a quality of service associated with the logical nodes, or may be based on any other similar factor. As an example, when data is obtained from an imaging sensor, management platform  346  may determine the current geographic region associated with the imaging data and determine any logical sensors that correspond to the geographic region of interest. Once the logical sensors are identified, sensor data may be apportioned to the corresponding sensors. 
     Although the previous example identified logical sensors based on the geolocation associated with the data, management platform  346  may provide further operations on (or processing of) the sensor data from the physical sensors prior to apportioning the data to the corresponding logical sensors. These operations may include generating composite data from two or more sensors, modifying the format of the sensor data to a second format associated with a logical sensor, or providing some other similar process on the data to provide the required data to the corresponding logical sensor. 
     In addition to the data processing operations provided in data processing segment  301 , physical node  111  further includes control segment  302 . Control segment  302 , which may be communicatively linked to data processing segment  301  and interface segment  303 , is responsible for logistical control elements of physical node  111 . The operations may include managing the deployment of solar panels on a satellite, managing the positioning of a satellite with regards to the Earth or the sun, providing a spaceborne sensor pointing and control, autonomously managing target decks or tasking priorities, or any other similar operation. When physical node  111  comprises an aircraft or atmospheric node, then control elements can include flight control systems, power systems, navigation systems, sensor pointing and control, autonomously managing target decks or tasking priorities, among other elements. When physical node  111  comprises a surface node, then control elements can include propulsion elements, power systems, powertrains, navigation systems, and the like. A flight control system might not be employed in all node types, such as stationary surface nodes. 
     In at least one example, flight control system  311  may monitor for requests from data processing segment  301  and determine whether the node can accommodate the request. As an example, application  344  may require movement of a satellite, aircraft, or vehicle to provide an operation with respect to a sensor of sensors  320 . Control segment  302  may determine whether the movement is permitted and implement the required action if permitted. The determination of whether an action is permitted by control segment  302  may be determined based on other applications executing on the node, based on flight requirements of the node, or based on some other similar mechanism. 
     Also depicted in expanded view  300  is interface segment  303  with sensors  320  and communication interface  321 . Interface segment  303  may be communicatively coupled to data processing segment  301  and control segment  302 . Sensors  320  may comprise imaging sensors, heat sensors, proximity sensors, light sensors, or some other similar type of sensor. Sensors  320  may be accessible to applications  341 - 344  executing in data processing segment  301  and may further be accessible to one or more other applications executing on other nodes of the system. In at least one implementation, each of the sensors may be allocated to one or more logical nodes, where the logical nodes may each access the senor during defined time periods, may jointly obtain data derived from the sensor at the same time (e.g. all logical nodes can access the same imaging data), or may be provided access to sensors at some other interval. In other implementations, sensor data from sensors  320  may be apportioned to logical sensors associated with applications  341 - 344 , wherein the logical sensors may be provided data based on preferences or requirements of the specific application. In addition to sensors  320 , interface segment  303  further includes communication interface  321  that may be used to communicate with other physical nodes and/or management systems for system  100 . In some examples, communication interface  321  may work with management platform  346  to control the application communications. Thus, if application  341  required a communication with another physical node to obtain sensor data from the physical node, communication interface  321  may forward the communication to the appropriate node and obtain the data from the node. 
     While demonstrated in the example of expanded view  300  using a satellite node, physical nodes may be represented in a variety of forms. These physical nodes may comprise airplanes, drones, balloons, land vehicles (cars, trucks, trains, and the like), water vehicles, or some other similar physical node. These physical nodes may include a data processing segment capable of providing a platform for the applications executing thereon, may comprise a communication interface to communicate with other physical nodes and/or control systems, and may further comprise one or more sensors capable of gathering required data for the applications executing thereon. 
       FIG. 4  illustrates an operational scenario  400  of apportioning sensor data to logical sensors according to an implementation. Operational scenario  400  includes physical nodes  410 - 411  with corresponding physical sensors  420 - 421 , logical sensors  430 - 434 , and applications  440 - 443 . Applications  440 - 444  may execute on one or more of physical nodes  410 - 411  or some other node in a deployed physical node system. The physical nodes of the system may comprise airborne nodes, spaceborne nodes, land vehicles, water vehicles, or some other similar physical node. 
     As described herein, physical nodes  410 - 411  collect sensor data from corresponding sensors  420 - 421 . As the sensor data is obtained, a management service executing on one or more of physical nodes  410 - 411  is used to apportion the data to logical sensors  430 - 434  associated with physical sensors  420 - 421 . Here, at least a portion of the data from physical sensor  420  is apportioned to logical sensors  430 - 431 , while at least a portion of the data from physical sensor  421  is apportioned to logical sensors  431 - 433 . In some implementations, in apportioning the data to each of the logical sensors, the management platform may identify relevant portions of the data for the logical sensor based on the parameters of the application associated with the logical sensor. For example, physical sensor  420  may represent an imaging sensor that gathers imaging data for a first geographic region. As the data is gathered from the physical sensor, the management service executing on the one or more physical nodes may identify that the data is relevant to logical sensor  430  and determine a portion of the data to be supplied to logical sensor  430 . Thus, if logical sensor  430  required data about a geographic region of interest that represented a portion of the first geographic region, the management service may identify the portion of the raw data from the logical sensor and provide that data that corresponds to the geographic region of interest. Other operations in apportioning the sensor data to the logical sensors may include converting the format of the data from the physical sensor to a format that is expected by the application associated with the sensor, converting the resolution of the data from a first resolution to a second resolution, or some other similar process with relation to the sensor data. 
     As further demonstrated in  FIG. 4 , some of the logical sensors may include data obtained from multiple physical sensors. In some implementations, the management platform may process the sensor data prior to apportioning the data to the logical sensor. This processing may include identifying portions of the data that are relevant for the logical sensor, determining composite data for the logical sensor, or providing some other processing operation with respect to the data from the physical sensors. Using the example of logical sensor  431 , physical sensors  420 - 421  may correspond to imaging sensors capable of gathering images related to an object of interest. From the raw data obtained from the physical sensors, the management platform may identify relevant portions of the imaging data that correspond to an object of interest for application  441  and logical sensor  431 . Once the relevant portions are identified and the composite data is generated from physical sensors  420 - 421 , the composite data may be apportioned to the logical sensor. Application  441  may then request and receive data from a data stream corresponding to the logical sensor to provide the required operations. 
     In some implementations, the logical sensors that are allocated to a logical node may be dynamic based on the movement of the physical sensors. As a satellite system example, physical sensor  420  may initially perform sensor gathering operations for a logical sensor, but due to the orbit of physical node  410  may be unable to perform the required operations. Consequently, the data gathering operations may be transitioned to a second physical node, such as physical node  411  to provide the desired operations. In transitioning between physical nodes, the management platform may dynamically modify the physical sensor resources that correspond to each of the logical sensors. Thus, while the application may request and obtain data from the same data stream and logical sensor, the physical resources that provide the data to the logical sensor may change based on the movement of the physical nodes in the system. 
     In some implementations, in managing the data that is apportioned to each of the logical sensors, the data may be encrypted to prevent access to the data from other applications and processes. In particular, as the data is allocated to each of the logical sensors, the management platform may encrypt the data that is provided in the data stream to the application. Referring to an example in operational scenario  400 , the management platform for node  411  may encrypt the data that is provided to logical sensor  433  using first encryption parameters. As a result, when application  443  requests data from the logical sensor, application  443  may include encryption parameters to decrypt the data provided in the data stream for processing by the application. This encryption may prevent other applications that address the logical sensor from obtaining and processing data associated with the logical sensor. 
     In some implementations, when multiple applications share the same logical sensor, such as the example with application  443  and application  444 , the data apportioned to the sensor may be stored in separate encrypted data pools. These separate encrypted data pools ensure that a first application accessing the sensor is incapable of obtaining and processing improper data that was obtained from the sensor by another application. As a result, when then data is encrypted for each of the pools, each of the pools may be associated with different encryption parameters. Once a request is generated from the application to the logical sensor, the logical sensor may identify the source of the request and provide data as a data stream from the storage pool associated with the request. Once received by the application, the application may decrypt the data using the encryption parameters and process the data as required. 
       FIG. 5  illustrates an operational scenario  500  of apportioning sensor data to logical sensors according to an implementation. Operational scenario  500  includes physical nodes  510 - 511  with corresponding physical sensors  520 - 521 , logical sensors  530 - 536 , applications  540 - 544  and data store  550 . Applications  540 - 544  may execute on one or more of physical nodes  510 - 511  or some other node in a deployed physical node system. The physical nodes of the system may comprise airborne nodes, spaceborne nodes, land vehicles, water vehicles, or some other similar physical node. 
     In operation, physical nodes  510 - 511  provide a platform for the execution of applications  540 - 544 , wherein applications  540 - 544  may execute in a virtual machine, container, or some other logical or virtual endpoint. In providing the required operations for applications  540 - 543 , physical nodes  510 - 513  include physical sensors  520 - 521  capable of gather various data for the applications. Here, rather than permitting the applications to individually communicate with and obtain data from physical sensors  520 - 521 , a management platform may be used that can obtain data from the physical sensors and apportion the data to the corresponding logical sensors. In the example of operational scenario  500 , physical nodes  510 - 511  provide data from physical sensor  520  to logical sensors  530 - 531  and data from physical sensor  521  to logical sensors  531 - 533 . In apportioning the data to each of the logical sensors, the management platform of the physical nodes may provide various processing operations on the data. This processing may include identifying relevant portions of the data for each of the logical sensors, converting formats of the data from a first format to a second format, generating composite data from multiple sensors, or providing some other similar operation with respect to the sensor data. In some implementations, the apportioning of the data may be based on the requirements of the application (logical node), wherein the requirements may comprise quality requirements, format requirements, objects or regions of interest, or some other similar requirement that may be defined when the application is deployed. Once the data is apportioned to each of the logical sensors, data requestors, which in this example include applications  540 - 543 , may request and obtain data from each of the logical sensors using data streams associated with each of the logical sensors. 
     In some implementations, rather than obtaining data in real-time from the logical sensors, data may be persisted or cached for future use by the application. For example, application  540  may not require real-time processing of data obtained from physical sensor  510 . Instead, application  540  may be allocated a lower quality of service that permits application  540  to process the data at a later time. Accordingly, if the logical node supporting application  540  were initiated at a later time, application  540  may generate requests of logical sensor  530  and process the data from the data stream as though the data had been obtained in real-time. 
     As further demonstrated in operational scenario  500 , at least a portion of the applications may be used to process sensor data and apportion the processed sensor data to one or more secondary logical sensors. In the example of application  543 , application  543  requests data from a data stream that corresponds to logical sensor  533 . This sensor data may comprise imaging data, heat data, seismic or motion activity data, or some other similar data. As the data is obtained, application  543  may process the data to identify portions of interest for logical sensors  534 - 535 , convert the format of the data, or provide some other similar operation with respect to the data. Once the operations are performed on the data, application  543  may apportion the processed data among logical sensors  434 - 535  associated with application  543 , which permits one or more other applications to access the processed data as data streams from logical sensors  534 - 535 . 
     In some implementations, rather than directly apportioning the data to a logical sensor, the data may be cached or stored in a data store, such as data store  550 . In particular, as the data is collected from a physical sensor, such as physical sensor  521 , the data may be cached in data store  550 , which may be located on physical node  511 , on another physical node of the system, or on a ground storage system accessible to the physical nodes. As the data is stored, applications may generate requirements to access and process the data. Consequently, the management platform for the application may allocate or generate a new logical sensor  536  for the requesting application. Once the logical sensor is allocated, data from data store  550  may be apportioned to logical sensor  536 , permitting the application  544  to obtain and process the data as though the data were being received in real-time. Further, in some implementations, prior to apportioning the data, the system may process the data to provide required data associated with the application. This processing may include modifying a format of the data for the logical sensor, identifying objects of interest in the data and providing sensor data associated with the objects of interest, generating composite data from multiple sensors, or providing some other similar processing operation on the data prior to apportioning the data to the allocated logical sensor. 
       FIG. 6  illustrates an operational scenario  600  of apportioning sensor data to logical sensors according to an implementation. Operational scenario  600  includes satellites  610 - 614 , object of interest  641 , and logical sensor  670 . Satellites  611 - 613  include sensing elements  661 - 663  that may comprise one or more physical sensors. 
     As depicted in operational scenario  600 , satellite  611 , at step  1 , may obtain sensing data regarding object of interest  641  and allocate at least a portion of the sensing data to logical sensor  670 . In some implementations, when applications are deployed in a sensing system, the applications may use logical sensors that are allocated to the applications to provide the required operations. These logical sensors may be allocated as part of the logical node in some examples, wherein the sensor data provided to each of the logical sensors may be determined based on requirements of the associated application. For instance, a container that executes an application may be provided with addressing information that permits the container to address logical sensor  670  as though logical sensor  670  were a physical sensor available to the application. In apportioning the data to logical sensor  670 , a management service that can be located on one or more of satellites  610 - 614  may obtain the required data from the one or more physical sensors and apportion any required data to logical sensor  670 . As a result, during step  1 , the management service may identify relevant data for logical sensor  670  that corresponds to object of interest  641  and may apportion the relevant data to logical sensor  670 . Once apportioned, the application associated with logical sensor  670  may request and obtain the apportioned data as a data stream to provide the required operations. 
     In some implementations, when the management platform determines what data should be provided to a logical sensor, the management platform may provide various operations on the data prior to providing the data. These processes or operations on the data may include identifying a subset of the data that is relevant for the for the logical sensor, generating composite data from multiple sensors, converting a format of the data from the physical sensor to a format for the logical sensor, or some other similar operation. For instance, when satellite  611  obtains data from sensing elements  661 , the sensor data may provide sensor data for object of interest  641  as well as other objects that are not of interest to logical sensor  670 . As an example, an imaging sensor may obtain imaging data for object of interest  641  (geographic area of interest) as well as other geographic regions. Consequently, to provide the required data for logical sensor  670 , satellite  611  or some other physical node in the system may process the sensor data to extract the portion of data that is relevant to logical sensor  670 . Once extracted, the extracted sensor data may be provided as the sensor data to logical sensor  670 , permitting applications to access the required data via a data stream from the logical sensor. 
     As demonstrated in  FIG. 6 , satellites in an observation system may comprise mobile physical nodes capable of providing sensor data for various periods of time. In particular, due to the orbit of satellite  611 , the physical sensing elements  661  of satellite  611  may only provide relevant sensor data for logical sensor  670  during a portion of its orbit. Consequently, satellite  611  may handoff the gathering of data from the physical sensors to satellite  612  and satellite  612  may obtain second data, at step  2 , via sensing elements  662  for logical sensor  670 . In some implementations, the handoff to satellite  612  may comprise a complete handoff to the sensors located on satellite  612 . In other implementations, the data from sensing element  661  and sensing elements  662  may be used to generate composite data, wherein data from satellite  611  may be combined with data from satellite  612  to generate the required data for logical sensor  670 . Similar operations may also be provided, at step  3 , when satellite  612  initiates a handoff to satellite  613 , permitting sensing elements  663  to provide the required sensor data for logical sensor  670 . In this manner, although an application may request and obtain data from the same logical sensor, the satellite platform may modify the physical sensors that are used to provide the required data. These modifications may be defined by the administrator at the time of deploying an application and logical node, may be defined during the operation of the logical node (e.g., identifying and object of interest during the operation of the application), or may be defined using any other similar operation. Thus, rather than changing the configuration of the physical nodes, the management service may be used to transition a logical sensor from a first set of one or more physical sensors to a second set of one or more physical sensors. 
     Although demonstrated in the example of  FIG. 6  using satellites for physical nodes, other systems may employ various airborne, spaceborne, and ground-based systems to provide the sensor data gathering operations. In some implementations, the various physical nodes may further include processing systems, storage systems, and communication resources to support logical nodes and corresponding applications. As a result, while a first physical node may obtain the required sensor data, the management platform that operates on the physical nodes may forward the data to any of the physical nodes that are executing the application. This allows an application for a logical node to execute on a first physical node, while other resources, including physical sensors that provide data to the application may be located on one or more other physical nodes. 
       FIG. 7  illustrates a physical node computing system  700  according to an implementation. Computing system  700  is representative of any computing system or systems with which the various operational architectures, processes, scenarios, and sequences disclosed herein for a physical node may be implemented. Computing system  700  is an example of physical nodes  110 - 111  and  130 - 132  in  FIG. 1 , although other examples can be employed. Computing system  700  comprises communication interface  701 , sensors  702 , and processing system  703 . Processing system  703  is linked to communication interface  701  and sensors  702 . Sensors  702  may comprise imaging sensors, heat sensors, proximity sensors, acoustic sensors, vibration sensors, light sensors, or some other similar type of sensor. Processing system  703  includes processing circuitry  705  and memory device  706  that stores operating software  707 . Computing system  700  may include other components such as a power system, photovoltaic solar panels, battery, and enclosure that are not shown for clarity. 
     Communication interface  701  comprises components that communicate over communication links, such as network cards, ports, radio frequency (RF), processing circuitry and software, or some other communication devices. Communication interface  701  may be configured to communicate over conductive, wireless, or optical links. Communication interface  701  may be configured to use Time Division Multiplex (TDM), Code Division Multiplex (CDM), Internet Protocol (IP), Ethernet, optical networking, wireless protocols, communication signaling, or some other communication format, including combinations thereof. In at least one implementation, communication interface  701  may be used to communicate with a control system and one or more other physical nodes in a converged system, where the physical nodes may comprise mobile or stationary devices, such as satellites, drones, airplanes, or balloons, land and water vehicles, stationary surface or sub-surface nodes, or some other devices. 
     Processing circuitry  705  comprises microprocessor and other circuitry that retrieves and executes operating software  707  from memory device  706 . Memory device  706  may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data. Memory device  706  may be implemented as a single storage device, but may also be implemented across multiple storage devices or sub-systems. Memory device  706  may comprise additional elements, such as a controller to read operating software  707 . Examples of storage media include random access memory, read only memory, magnetic disks, optical disks, and flash memory, as well as any combination or variation thereof, or any other type of storage media. In some implementations, the storage media may be a non-transitory storage media. In some instances, at least a portion of the storage media may be transitory. 
     Processing circuitry  705  is typically mounted on a circuit board that may also hold memory device  706  and portions of communication interface  701  and user interface  702 . Operating software  707  comprises computer programs, firmware, or some other form of machine-readable program instructions. Operating software  707  includes platform module  709  and applications  710 , although any number of software modules may provide a similar operation. Operating software  707  may further include an operating system, utilities, drivers, network interfaces, applications, or some other type of software. When executed by processing circuitry  705 , operating software  707  directs processing system  703  to operate computing system  700  as described herein. 
     In one implementation, platform module  709  directs processing system  703  to provide a platform for the execution of applications  710 , wherein applications  710  may execute as logical nodes in some examples. The logical nodes may comprise virtual machines, containers, or some other virtualized endpoint that may execute using physical resources from one or more physical nodes. These physical resources may comprise storage resources, communication resources, sensor resources, or some other similar resource. In providing sensor resources to applications  710 , platform module  709  may be used to apportion sensor data to logical sensors associated with each of the applications. In particular, platform module  709  may obtain sensor data from sensors  702  (or physical sensors on other physical nodes) and apportion the sensor data among logical sensors associated with the physical sensors. Once apportioned, applications  710  may request and be provided with data streams associated with the logical sensors. 
     In some implementations, in apportioning the data to the logical sensors, platform module  709  may process the data prior to apportioning the data. For example, platform module  709  may identify a subset of the sensor data that is relevant to an application associated with a logical sensor, may modify a format of the data from a first format to a second format, may generate composite data from multiple sensors and allocate that data as a single sensor, or may provide any other similar processing operation. Further, in apportioning the data to the logical sensors, at least a portion of the logical sensors may have the sensor data cached (or persisted) for later processing by an application. This caching may be based on a quality of service associated with the applications, permitting applications with a lower quality of service to process data from any associated logical sensors at a later time, reserving resources for other applications. 
     The included descriptions and figures depict specific implementations to teach those skilled in the art how to make and use the best option. For the purpose of teaching inventive principles, some conventional aspects have been simplified or omitted. Those skilled in the art will appreciate variations from these implementations that fall within the scope of the invention. Those skilled in the art will also appreciate that the features described above can be combined in various ways to form multiple implementations. As a result, the invention is not limited to the specific implementations described above, but only by the claims and their equivalents.