IP Library Granted Patent US 10,375,161
Granted Patent B1
US 10,375,161 · App. 14/249,098 · Granted Aug 6, 2019

Distributed computing task management system and method

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Quick Facts
Patent No.
US 10,375,161
App. No.
14/249,098
Granted
Aug 6, 2019
Kind
B1
Abstract

A distributed computing task management system includes an application for monitoring a processing load of multiple resources that are used to execute a distributed computing task. The resources include at least one hardware resource and one or more virtual objects executed on the hardware resources in a virtual computing environment. Using the monitored processing load, the application adjusts a performance of the resources to compensate for changes in the processing load incurred by the resources due to execution of the distributed computing task.

Claims (36)

1. A distributed computing task management method comprising:

monitoring, using an application stored in a non-transitory medium and executed on at least one processor, a processing load of a plurality of resources executing a map-reduce process comprising a plurality of splitter tasks, a plurality of mapper tasks, and a plurality of reducer tasks, the plurality of resources comprising at least one of a plurality of hardware resources and a plurality of virtual objects executed on the hardware resources in a virtual computing environment, wherein each of the plurality of splitter tasks, the plurality of mapper tasks, and the plurality of reducer tasks are executed on individual ones of the virtual objects in the virtual computing environment;

determining, while the map-reduce process continues to execute on the plurality of resources, performance characteristics of the plurality of resources, the performance characteristics comprising one or more of:

a type of processing load being executed by the plurality of resources; and

a change in the processing load being incurred by the plurality of resources; and

adjusting, using the application executed by the processor and while the map-reduce process continues to execute, a quantity of the plurality of resources used to execute the map-reduce process, the adjusting based on the performance characteristics of the plurality of resources.

2. The method of claim 1 , wherein the type of processing load being executed comprises at least one of a memory usage of the plurality of resources, a computational loading level of the plurality of resources, and an inter-resource communication loading level of the plurality of resources.

3. The method of claim 1 , further comprising monitoring at least one of a job completion time of the map-reduce process executed on each resource, a processing load level of a processor unit used by the plurality of resources, and a memory usage level of a memory unit used by each of the plurality of resources.

4. The method of claim 1 , further comprising adjusting a performance of the plurality of resources by instantiating one or more additional virtual objects when the processing load meets a specified first level or deleting one or more of the plurality of virtual objects when the processing load meets a specified second level, the virtual objects comprising the at least one or more of the plurality of resources.

5. The method of claim 1 , further comprising adjusting the quantity of the plurality of resources by enhancing one or more performance characteristics of at least one of the plurality of resources when the processing load of the at least one resource meets a specified first level or reducing the one or more performance characteristics of the at least one resource when the processing load meets a specified second level.

6. The method of claim 5 , wherein the one or more performance characteristics comprise at least one of a number of processors allocated to at least one of the plurality of resources and an amount of memory allocated to at least one of the plurality of resources.

7. The method of claim 1 , further comprising adjusting the quantity of the plurality of resources by allocating one or more additional hardware resources when the processing load meets a specified first level and de-allocating one or more previously allocated hardware resources when the processing load meets a specified second level, the hardware resources comprising the plurality of resources.

8. The method of claim 1 , wherein the virtual computing environment includes at least one of a converged infrastructure and a cloud computing environment.

9. A distributed computing task management system comprising:

a computing system comprising at least one processor and at least one memory to store an application that is executed by the at least one processor to:

monitor a processing load of a plurality of resources executing a map-reduce process comprising a plurality of splitter tasks, a plurality of mapper tasks, and a plurality of reducer tasks, the resources comprising at least one of a plurality of hardware resources and a plurality of virtual objects executed on the hardware resources in a virtual computing environment, wherein each of the plurality of splitter tasks, the plurality of mapper tasks, and the plurality of reducer tasks are executed on individual ones of the virtual objects in the virtual computing environment;

determine, while the map-reduce process continues to execute on the plurality of resources, performance characteristics of the plurality of resources, the performance characteristics comprising one or more of:

a type of processing load being executed by the plurality of resources; and

a change in the processing load being incurred by the plurality of resources; and

adjust, while the map-reduce process continues to execute, a quantity of the resources used to execute the map-reduce process, the adjusting based on the performance characteristics of the plurality of resources.

10. The distributed computing task management system of claim 9 , wherein the type of processing load being executed comprises at least one of a memory usage of the plurality of resources, a computational loading level of the plurality of resources, and an inter-resource communication loading level of the plurality of resources.

11. The distributed computing task management system of claim 9 , wherein the application is further executed to monitor at least one of a job completion time of the map-reduce process executed on each of the plurality of resources, a processing load level of a processor unit used by the plurality of resources, and a memory usage level of a memory unit used by each of the plurality of resources.

12. The distributed computing task management system of claim 9 , wherein the application is further executed to adjust a performance of the plurality of resources by instantiating one or more additional virtual objects when the processing load meets a specified first level or deleting one or more of the existing virtual objects when the processing load meets a specified second level, the virtual objects comprising the plurality of resources.

13. The distributed computing task management system of claim 9 , wherein the application is further executed to adjust a performance of the plurality of resources by enhancing one or more performance characteristics of at least one of the plurality of resources when the processing load of the at least one resource meets a specified first level or reducing the one or more performance characteristics of the at least one resource when the processing load meets a specified second level.

14. The distributed computing task management system of claim 13 , wherein the one or more performance characteristics comprise at least one of a number of processors allocated to at least one of the plurality of resources and an amount of memory allocated to the at least one resource.

15. The distributed computing task management system of claim 9 , wherein the application is further executed to adjust the quantity of the plurality of resources by allocating one or more additional hardware resources when the processing load meets a specified first level and de-allocating one or more previously allocated hardware resources when the processing load meets a specified second level, the hardware resources comprising the plurality of resources.

16. The distributed computing task management system of claim 9 , wherein the virtual computing environment includes at least one of a converged infrastructure and a cloud computing environment.

17. A non-transitory, computer readable medium including computer executable instructions that when executed by at least one processor are operable to:

monitor a processing load of a plurality of resources executing a map-reduce process comprising a plurality of splitter tasks, a plurality of mapper tasks, and a plurality of reducer tasks, the plurality of resources comprising at least one of a plurality of hardware resources and a plurality of virtual objects executed on the hardware resources in a virtual computing environment, wherein each of the plurality of splitter tasks, the plurality of mapper tasks, and the plurality of reducer tasks are executed on individual ones of the virtual objects in the virtual computing environment;

determine, while the map-reduce process continues to execute on the plurality of resources, performance characteristics of the plurality of resources, the performance characteristics comprising one or more of:

a type of processing load being executed by the plurality of resources; and

a change in the processing load being incurred by the plurality of resources; and

adjust, while the map-reduce process continues to execute, a quantity of the resources used to execute the map-reduce process, the adjusting based on the performance characteristics of the plurality of resources.

18. The non-transitory computer readable medium of claim 17 , the computer executable instructions further operable to perform monitoring at least one of a job completion time of the map-reduce process executed on each resource of the plurality of resources, a processing load level of a processor unit used by the resource, and a memory usage level of a memory unit used by the resource.

19. The non-transitory computer readable medium of claim 17 , the computer executable instructions further operable to perform adjusting a performance of the plurality of resources by instantiating one or more additional virtual objects when the processing load meets a specified first level or deleting one or more of the existing virtual objects when the processing load meets a specified second level, the virtual objects comprising the resources.

20. The non-transitory computer readable medium of claim 17 , the computer executable instructions further operable to perform adjusting a performance of the plurality of resources by enhancing one or more performance characteristics of at least one of the plurality of resources when the processing load of the at least one resource meets a specified first level or reducing the one or more performance characteristics of the at least one resource when the processing load meets a specified second level.

Assignments (11)
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (051302/0528) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC; DELL MARKETING CORPORATION (SUCCESSOR-IN-INTEREST TO WYSE TECHNOLOGY L.L.C.); SECUREWORKS CORP.
Reel/Frame 060438/0593 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (053546/0001) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL MARKETING L.P. (ON BEHALF OF ITSELF AND AS SUCCESSOR-IN-INTEREST TO CREDANT TECHNOLOGIES, INC.); DELL INTERNATIONAL L.L.C.; DELL PRODUCTS L.P.; DELL USA L.P.; EMC CORPORATION; DELL MARKETING CORPORATION (SUCCESSOR-IN-INTEREST TO FORCE10 NETWORKS, INC. AND WYSE TECHNOLOGY L.L.C.); EMC IP HOLDING COMPANY LLC
Reel/Frame 071642/0001 →
RELEASE OF SECURITY INTEREST AT REEL 051449 FRAME 0728 Recorded Nov 2, 2021
From: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC; WYSE TECHNOLOGY L.L.C.; SECUREWORKS CORP.; EMC CORPORATION
Reel/Frame 058002/0010 →
SECURITY AGREEMENT Recorded Apr 22, 2020
From: CREDANT TECHNOLOGIES INC.; DELL INTERNATIONAL L.L.C.; DELL MARKETING L.P.; DELL PRODUCTS L.P.; DELL USA L.P.; EMC CORPORATION; FORCE10 NETWORKS, INC.; WYSE TECHNOLOGY L.L.C.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A.
Reel/Frame 053546/0001 →
MERGER Recorded Apr 14, 2020
From: VCE IP HOLDING COMPANY LLC
To: EMC IP HOLDING COMPANY LLC
Reel/Frame 052398/0413 →
SECURITY AGREEMENT Recorded Dec 31, 2019
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC; WYSE TECHNOLOGY L.L.C.; SECUREWORKS CORP.; EMC CORPORATION
To: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
Reel/Frame 051449/0728 →
PATENT SECURITY AGREEMENT (NOTES) Recorded Dec 16, 2019
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC; WYSE TECHNOLOGY L.L.C.; SECUREWORKS CORP.
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS COLLATERAL AGENT
Reel/Frame 051302/0528 →
SECURITY AGREEMENT Recorded Mar 21, 2019
From: CREDANT TECHNOLOGIES, INC.; DELL INTERNATIONAL L.L.C.; DELL MARKETING L.P.; DELL PRODUCTS L.P.; DELL USA L.P.; EMC CORPORATION; FORCE10 NETWORKS, INC.; WYSE TECHNOLOGY L.L.C.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A.
Reel/Frame 049452/0223 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 8, 2016
From: VCE COMPANY, LLC
To: VCE IP HOLDING COMPANY LLC
Reel/Frame 040576/0161 →
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE PREVIOUSLY RECORDED ON REEL 032638 FRAME 0625. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT OF THE ENTIRE INTEREST (SEE DOCUMENT FOR DETAILS). Recorded Apr 11, 2014
From: TAN, MICHAEL; MAHAPATRA, AKSHAYA
To: VCE COMPANY, LLC
Reel/Frame 032662/0567 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 9, 2014
From: TAN, MICHAEL; MAHAPATRA, AKSHAYA
To: LEVEL 3 COMMUNICATIONS, LLC
Reel/Frame 032638/0625 →