Systems and methods for allocating and managing resources in an internet of things environment using location based focus of attention
A system for managing clouds of edge devices as an Infrastructure as a Service clouds includes an application server, a location based situational awareness subsystem and a cloud management subsystem. The cloud management subsystem includes a first API through which the application server makes request to the location based situational awareness subsystem and a conductor that searches for the optimal deployment of cloud resources that meet a set of constraints. A second API for managing and deploying applications on a selected set of the plurality of network connected devices. The system also includes a compute node that can interact with the selected set of the plurality of network connected devices to launch and manage containers on the selected set of the plurality of network connected devices.
1. A method comprising:
receiving, via an Application Programming Interface (API) by a processing system including a processor, a request to build an awareness picture of an area of interest;
sending, by the processing system, a geographically addressed message to a set of edge devices in a geocast region defined by the area of interest, wherein the geographically addressed message contains a set of requirements of a desired resource;
obtaining, by the processing system, responses that satisfy the set of requirements;
determining, by the processing system, a first list of edge devices that satisfy the set of requirements from the responses;
obtaining, by the processing system, a second list of edge devices having capabilities and resource availability to satisfy the set of requirements, wherein the second list of edge devices is derived from filtering of the first list of edge devices using a constraint solving algorithm; and
sending, by the processing system, the second list of edge devices to an end user device, wherein a selection at the end user device of an edge device from the second list of edge devices facilitates a download of an application at the edge device.
2. The method of claim 1 , wherein the second list of edge devices are displayed on a map interface of the end user device.
3. The method of claim 1 , wherein the obtaining the second list of edge devices is from a cloud computing platform executing the constraint solving algorithm, and further comprising sending, by the processing system, the first list of edge devices to the cloud computing platform.
4. The method of claim 1 , wherein the second list of edge devices is based on traditional cloud resource metrics.
5. The method of claim 1 , wherein the set of edge compute devices is a set of vehicles.
6. The method of claim 1 , wherein the download of the application at the edge device is managed by a compute node that launches and manages containers on edge devices.
7. The method of claim 1 , wherein the constraint solving algorithm searches for optimal deployment of cloud resources that meets a given set of constraints and service owner requirements.
8. A non-transitory computer-readable storage medium having a tangible physical structure, the computer-readable storage medium comprising executable instructions that when executed by a processor cause the processor to perform operations comprising:
receiving a request to build an awareness picture of an area of interest;
sending a geographically addressed message to a set of edge devices in a geocast region defined by the area of interest, wherein the geographically addressed message contains a set of requirements of a desired resource;
obtaining responses that satisfy the set of requirements;
determining a first list of edge devices that satisfy the set of requirements from the responses;
obtaining a second list of edge devices having capabilities and resource availability to satisfy the set of requirements, wherein the second list of edge devices is derived from filtering of the first list of edge devices using a constraint solving algorithm; and
sending the second list of edge devices to an end user device to facilitate a download of an application at an edge device selected from among the second list of edge devices, wherein the download is managed by a compute node that launches and manages containers on edge devices.
9. The non-transitory computer-readable storage medium of claim 8 , wherein the second list of edge devices are displayed on a map interface on the end user device.
10. The non-transitory computer-readable storage medium of claim 8 , wherein a selection at the end user device of an edge device from the second list of edge devices facilitates the download of the application at the edge device.
11. The non-transitory computer-readable storage medium of claim 8 , wherein the second list of edge devices is based on traditional cloud resource metrics.
12. The non-transitory computer-readable storage medium of claim 8 , wherein the set of edge compute devices is a set of vehicles.
13. The non-transitory computer-readable storage medium of claim 8 , wherein the obtaining the second list of edge devices is from a cloud computing platform executing the constraint solving algorithm, and wherein the operations further comprise sending the first list of edge devices to the cloud computing platform.
14. The non-transitory computer-readable storage medium of claim 8 , wherein the constraint solving algorithm searches for optimal deployment of cloud resources that meets a given set of constraints and service owner requirements.
15. A device comprising:
a processing system including a processor; and
a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising:
receiving a request from an end user device to build an awareness picture of an area of interest;
sending the request to a location based situational awareness subsystem (LSA) to cause the LSA to obtain a second list of edge devices having capabilities and resource availability to satisfy a set of requirements, wherein the second list of edge devices is derived from filtering of a first list of edge devices using a constraint solving algorithm, wherein the first list of edge devices is determined based on satisfying the set of requirements from responses obtained to a geographically addressed message sent to a set of edge compute devices in a geocast region defined by the area of interest, wherein the geographically addressed message contains the set of requirements of a desired resource;
receiving, from the end user device, a selection of an edge device from the second list of edge devices that is provided to the end user device by the LSA; and
sending the selection of the edge device to a cloud computing platform to facilitate a download of an application at the edge device.
16. The device of claim 15 , wherein the second list of edge devices are displayed on a map interface on the end user device.
17. The device of claim 15 , wherein the second list of edge devices is based on traditional cloud resource metrics.
18. The device of claim 15 , wherein the set of edge compute devices is a set of vehicles.
19. The device of claim 15 , wherein the obtaining the second list of edge devices is from a cloud computing platform executing the constraint solving algorithm, and wherein the LSA sends the first list of edge devices to the cloud computing platform.
20. The device of claim 15 , wherein the constraint solving algorithm searches for optimal deployment of cloud resources that meets a given set of constraints and service owner requirements.