IP Library › Granted Patent US 10,601,907
Granted Patent B2
US 10,601,907 · App. 15/712,703 · Granted Mar 24, 2020

System and method for platform to securely distribute compute workload to web capable devices

Inventors: Simon Adrian Bermudez Hernandez (Toronto, CA); Henning Dekant (Toronto, CA); Scott Horlacher (Toronto, CA)
Assignee: Artiste QB Net Inc.
H04L67/1008G06F9/4881G06F9/505G06F9/5083G06F11/3428H04L9/0662H04L9/12H04L9/3236H04L9/3247H04L63/1458H04L67/1029H04L2209/38H04L2209/56
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Quick Facts
Patent No.
US 10,601,907
App. No.
15/712,703
Granted
Mar 24, 2020
Kind
B2
Abstract

A method is disclosed for distributed computing using a plurality of web-enabled swarm devices. The method comprises: receiving, by a server platform, a workload request originating from a requestor, which workload request is associated with a workload; receiving, by the server platform, the workload associated with the workload request; splitting, by the server platform, the received workload into a group of subtasks; distributing the group of subtasks to the plurality of swarm devices; collecting, by the server platform, one or more result sets from the plurality of swarm devices based on performing of the group of subtasks by the swarm devices; assembling the one or more result sets into a computational result; and providing the requestor with the computational result.

Claims (67)

1. A method for distributed computing using a plurality of swarm devices,

wherein said plurality of swarm devices is web-enabled;

said method further comprising:

receiving, by a server platform, a workload request originating from a requestor, wherein said workload request is associated with a workload;

receiving, by the server platform, the workload associated with the workload request;

splitting, by said server platform, the received workload into a group of subtasks;

distributing said group of subtasks to the plurality of swarm devices;

collecting, by said server platform, one or more result sets from the plurality of swarm devices based on performing of said group of subtasks by said swarm devices;

assembling said one or more result sets into a computational result; and

providing, by said server platform, said requestor with the computational result.

2. The method of claim 1 , further comprising performing preprocessing on said group of subtasks prior to said distributing,

said preprocessing performed to enable hardware accelerated execution by either browsers or applications running on said plurality of swarm devices.

3. The method of claim 1 , further comprising:

receiving, by said server platform, a Uniform Resource Identifier (URI) from the requestor;

storing, by said server platform, a record based on said URI using a distributed ledger; and

wherein said receiving of workload is performed using said URI.

4. The method of claim 1 , wherein

said server platform is scalable; and

said server platform comprises requestor microservices created when said requestor connects to said server.

5. The method of claim 4 , further comprising swarm microservices created based on a number of said plurality of swarm devices connected to the server.

6. The method of claim 1 , wherein

said splitting is implemented using one or more task splitting algorithms; and

said splitting is specific to the workload.

7. The method of claim 4 , wherein

said server platform is an elastic server; and

said method further comprising creating a benchmark for each of the plurality of swarm devices, wherein said creating of the benchmark comprises recording an execution time of a test job.

8. The method of claim 7 , wherein said test job comprises a subtask randomly selected from said group of subtasks.

9. The method of claim 7 further comprising

monitoring a subtask execution time for each of the plurality of the swarm devices; and

adjusting the benchmark for each of said plurality of swarm devices using data obtained from said monitoring.

10. The method of claim 1 , further comprising restricting a connectivity of at least one of said plurality of swarm devices to mitigate the risk of malicious denial of service (DoS) attacks.

11. The method of claim 1 , wherein one or more digital signatures are used to sign traffic sent from the plurality of swarm devices to the server platform to mitigate the risk of man-in-the middle attacks.

12. The method of claim 11 , further comprising either

obtaining a key from a smart charger; or

downloading a public key.

13. A server platform for distributed computing, wherein

said server platform is coupled to a requestor and a plurality of swarm devices via a network,

further wherein said plurality of swarm devices is web-enabled; and

further wherein said server platform

receives a workload request originating from the requestor, wherein said workload request is associated with a workload,

receives the workload associated with the workload request,

splits the received workload into a group of subtasks,

distributes the group of subtasks to the plurality of swarm devices,

collects one or more result sets from the swarm of web-enabled devices based on performing of said group of subtasks by the swarm of web-enabled devices,

assembles said one or more result sets into a computational result, and

provides said requestor with the computational result.

14. The server platform of claim 13 , further wherein the server platform performs preprocessing on said group of subtasks prior to said distributing,

said preprocessing performed to enable hardware accelerated execution by either browsers or applications running on said plurality of swarm devices.

15. The server platform of claim 13 , further wherein said server platform

receives a URI from the requestor;

stores a record based on said URI using a distributed ledger; and

wherein said receiving of workload is performed using said URI.

16. The server platform of claim 13 , wherein

said server platform is scalable, and

said server platform comprises requestor microservices created when said requestor connects to said server platform.

17. The server platform of claim 16 , further wherein said server platform comprises swarm microservices created based on a number of said plurality of swarm devices connected to the server at any point in time.

18. The server platform of claim 13 , wherein said server platform implements said splitting using one or more task splitting algorithms, and said splitting is specific to the workload.

19. The server platform of claim 16 , wherein said server platform is an elastic server; and

said server platform creates a benchmark for each of the plurality of swarm devices, wherein said creating of the benchmark comprises recording an execution time of a test job.

20. The server platform of claim 19 , wherein said test job comprises a subtask randomly selected from said group of subtasks.

21. The server platform of claim 19 , further wherein

said server platform monitors a subtask execution time for each of said plurality of swarm devices; and

said server platform adjusts the benchmark for each of said plurality of swarm devices using data obtained from said monitoring.

22. The server platform of claim 13 , further wherein a connectivity of at least one of said plurality of swarm devices is restricted to mitigate the risk of malicious denial of service (DoS) attacks.

23. The server platform of claim 13 , wherein one or more digital signatures are used to sign traffic sent from the plurality of swarm devices to the server platform to mitigate the risk of man-in-the middle attacks.

24. The server platform of claim 23 , further wherein at least one of said plurality of swarm devices either obtains a key from a smart charger; or

downloads a public key.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 24, 2020
From: DEKANT, HENNING; HORLACHER, SCOTT; BERMUDEZ, SIMON
To: ARTISTE QB NET INC.
Reel/Frame 052200/0261 →
Continuity (1)
Related Publication 20190098080A1 · Mar 28, 2019
Cited By (2)
US 12,254,435 US 12,450,100