Distributed computing of vehicle data by selecting a computation resource of a remote server that satisfies a selection policy for meeting resource requirements according to capability information

• US 10,855,753 B2
• Filed: 02/23/2018
• Issued: 12/01/2020
• Est. Priority Date: 02/23/2018
• Status: Active Grant

• Current Assignee: Standard Cognition Corp.
• Original Assignee: Standard Cognition Corp.
• Inventors: Kallakuri, Nagasrikanth, Goel, Akshay, Dadlani, Tushar
• Primary Examiner(s): Murray, Daniel C.
• Application Number:
  US15/904,277
• Publication Number:
  US 20190268402A1
• Time in Patent Office: 1,012 Days
• CPC Class Codes: G06F 2209/509 Offload
• CPC Class Codes: G06F 9/5027 the resource being a machine, e.g. CPUs, Servers, Terminals
• CPC Class Codes: H04L 67/101 based on network conditions
• CPC Class Codes: H04L 67/125 involving control of end-device applications over a network
• CPC Class Codes: H04L 67/289 Intermediate processing functionally located close to the data consumer application, e.g. in same machine, in same home or in same sub-network
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 69/24 Negotiation of communication capabilities
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/44 for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]

Abstract

The technology disclosed allows for remote distributed computing and storage of vehicle data obtained from one or more vehicles. Specifically, the technology disclosed is capable of determining, at a vehicle, resource requirements for a software application. The technology disclosed is also capable of selecting a computation resource from a plurality of computation resources based on one or more selection policies for meeting the resource requirements, sending the vehicle data from the vehicle to the selected computation resource, receiving at the vehicle data from the selected computation resource and utilizing the data obtained from the computation resource and data in the vehicle in the software application.

Claims

1. A system comprising:

a vehicle computing system including one or more processors; and

logic encoded in one or more non-transitory computer-readable storage media for execution by the one or more processors and when executed operable to perform operations comprising;

determining, at the vehicle computing system of a vehicle, resource requirements for a software application;

requesting from each remote server of a plurality of remote servers, capability information corresponding to one or more selection policies for meeting the resource requirements, wherein the resource requirements are associated with computational requirements of the remote servers and wherein the capability information is requested by the vehicle computing system of the vehicle;

identifying two or more remote servers, of the plurality of remote servers, that satisfy the one or more selection policies for meeting the resource requirements according to the capability information received from each remote server;

selecting a computation resource of a remote server, of the identified two or more remote servers, that is optimal according to the capability information;

sending vehicle data from the vehicle computing system to the selected computation resource of the remote server for processing;

receiving, at the vehicle computing system, data from the selected computation resource; and

utilizing the data obtained from the selected computation resource and data in the vehicle in the software application.

2. The system of claim 1, wherein the resource requirements include storage requirements of the remote servers.

3. The system of claim 1, wherein the vehicle data includes location data, and wherein the software application is a map application.

4. The system of claim 1, wherein the vehicle data includes sensor information, and wherein the software application is an autonomous vehicle application.

5. The system of claim 1, wherein the vehicle data includes sensor information, and wherein the sensor information is used to avoid traffic collisions.

6. The system of claim 1, wherein at least one selection policy is to select a computation resource that meets the resource requirements for the software application and has a closest virtual distance to the vehicle, wherein the virtual distance is based on a number of network hops.

7. The system of claim 1, wherein at least one selection policy is to select a computation resource that meets the resource requirements for the software application and that has a closest physical distance to the vehicle.

8. The system of claim 1, wherein at least one selection policy is to select a computation resource that meets the resource requirements for the software application and that is located within a selected geographic boundary.

9. The system of claim 1, wherein the computation resource is not in a same physical location as the vehicle.

10. The system of claim 1, wherein the computation resource of the remote server is selected based on two or more selection policies for meeting the resource requirements and data information associated with data received from at least one data source, wherein the two or more selection policies are associated with two or more of location constraints related to the remote servers, time constraints associated with the data received from the at least one data source, and data type constraints related to the remote servers.

11. The system of claim 1, the operations further comprising:

receiving a notification that the selected computation resource of the selected computational resource of the remote server is running low on storage capacity or is becoming overloaded with computational demands;

selecting another computation resource of another remote server, of the plurality of remote servers, that satisfies the one or more selection policies for meeting the resource requirements according to the capability information; and

sending at least a portion of the vehicle data from the vehicle computing system to the other selected computation resource.

12. A non-transitory computer-readable storage medium with program instructions stored thereon, the instructions when executed by one or more processors cause the one or more processors to perform operations comprising:

determining, at a vehicle computing system of a vehicle, resource requirements for a software application;

requesting, from each remote server of a plurality of remote servers, capability information corresponding to one or more selection policies for meeting the resource requirements, wherein the resource requirements are associated with computational requirements of the remote servers and wherein the capability information is requested by the vehicle computing system of the vehicle;

identifying two or more remote servers, of the plurality of remote servers, that satisfy the one or more selection policies for meeting the resource requirements according to the capability information received from each remote server;

selecting a computation resource of a remote server, of the identified two or more remote servers, that is optimal according to the capability information;

sending vehicle data from the vehicle computing system to the selected computation resource of the remote server for processing;

receiving, at the vehicle computing system, data from the selected computation resource; and

utilizing the data obtained from the selected computation resource and data in the vehicle in the software application.

13. The non-transitory computer-readable storage medium of claim 12, wherein the resource requirements include storage requirements of the remote servers.

14. The non-transitory computer-readable storage medium of claim 12, wherein the vehicle data includes location data, and wherein the software application is a map application.

15. The non-transitory computer-readable storage medium of claim 12, wherein the vehicle data includes sensor information, and wherein the software application is an autonomous vehicle application.

16. The non-transitory computer-readable storage medium of claim 12, wherein at least one selection policy is to select a computation resource that meets the resource requirements for the software application and has a closest virtual distance to the vehicle, and wherein the virtual distance is based on a number of network hops.

17. The non-transitory computer-readable storage medium of claim 12, wherein at least one selection policy is to select a computation resource that meets the resource requirements for the software application and that is located within a selected geographic boundary.

18. A computer-implemented method for processing vehicle data, the method comprising:

determining, at a vehicle computing system of a vehicle, resource requirements for a software application;

requesting, from each remote server of a plurality of remote servers, capability information corresponding to one or more selection policies for meeting the resource requirements, wherein the resource requirements are associated with computational requirements of the remote servers and wherein the capability information is requested by the vehicle computing system of the vehicle;

identifying two or more remote servers, of the plurality of remote servers, that satisfy the one or more selection policies for meeting the resource requirements according to the capability information received from each remote server;

selecting a computation resource of a remote server, of the identified two or more remote servers, that is optimal according to the capability information;

sending vehicle data from the vehicle computing system to the selected computation resource of the remote server for processing;

receiving, at the vehicle computing system, data from the selected computation resource; and

utilizing the data obtained from the selected computation resource and data in the vehicle in the software application.

19. The computer-implemented method of claim 18, wherein the resource requirements include storage requirements of the remote servers.

20. The computer implemented method of claim 18, wherein the vehicle data includes location data, and wherein the software application is a map application.

21. The computer implemented method of claim 18, wherein the vehicle data includes sensor information, and wherein the software application is an autonomous vehicle application.