Weight adjusted dynamic task propagation

• US 10,146,584 B2
• Filed: 01/28/2016
• Issued: 12/04/2018
• Est. Priority Date: 01/28/2016
• Status: Active Grant

• Current Assignee: CA, Inc. (d/b/a CA Technologies) (Broadcom, Inc.)
• Original Assignee: CA, Inc. (d/b/a CA Technologies) (Broadcom, Inc.)
• Inventors: Raj, Apurv
• Primary Examiner(s): Bullock, Jr., Lewis A
• Assistant Examiner(s): Ashley, Bruce S
• Application Number:
  US15/008,509
• Publication Number:
  US 20170220382A1
• Time in Patent Office: 1,041 Days
• Field of Search: None
• CPC Class Codes: G06F 2209/5019 Workload prediction
• CPC Class Codes: G06F 2209/502 Proximity
• CPC Class Codes: G06F 2209/5022 Workload threshold
• CPC Class Codes: G06F 9/505 considering the load
• CPC Class Codes: H04L 67/1004 Server selection for load balancing
• CPC Class Codes: H04L 67/1008 based on parameters of servers, e.g. available memory or workload monitoring of computer activity G06F11/30
• CPC Class Codes: H04L 67/34 involving the movement of software or configuration parameters network booting or remote initial program loading [RIPL] G06F9/4416

Abstract

A method of assigning data processing tasks to workload agents includes receiving workload parameters that relate to available capacities of a plurality of workload agents, identifying a primary workload agent based on at least one of the workload parameters; identifying a plurality of candidate secondary workload agents; identifying a secondary workload agent based on the plurality of workload parameters; and transmitting a job message that contains a command for the primary workload agent to perform a data processing task. The job message includes a forwarding map that identifies the secondary workload agent, and contains a command for the primary workload agent to perform the data processing task using resources of the secondary workload agent.

Claims

1. A method, comprising:

performing operations as follows on a processor of a workload scheduling computing device;

receiving, via a communication network, a plurality of workload parameters from a plurality of workload agents in communication with the workload scheduling computing device, wherein the workload parameters relate to available capacities of the plurality of workload agents and wherein the workload agents comprise computing nodes configured to perform data processing tasks;

identifying a primary workload agent from the plurality of workload agents based on at least one of the plurality of workload parameters;

identifying a plurality of candidate secondary workload agents from among the plurality of workload agents, wherein identifying the candidate secondary workload agents comprises identifying workload agents for which each of the workload parameters is greater than a respective threshold level;

identifying a secondary workload agent from among the plurality of candidate secondary workload agents based on the plurality of workload parameters that are greater than the respective threshold level and an evaluation of a selection function that mathematically evaluates the plurality of workload parameters to select a workload agent from among the candidate secondary workload agents; and

transmitting, via the communication network, a job message that contains a command for the primary workload agent to perform a data processing task, wherein the job message includes a forwarding map that identifies the secondary workload agent and that enables the primary workload agent to perform the data processing task using resources of the secondary workload agent without disrupting future operations of the workload scheduling computing device;

wherein the selection function comprises a weight adjusted function based on a root mean square of a weighted mean of the plurality workload parameters, wherein weights of the weighted mean are assigned to each of the respective workload parameters.

2. The method of claim 1, wherein the plurality of workload parameters comprises a workload capacity, and wherein identifying the primary workload agent from among the plurality of workload agents comprises determining which of the plurality of workload agents has a lowest workload capacity.

3. The method of claim 1, wherein identifying the plurality of candidate secondary workload agents comprises determining path lengths from the primary workload agent to the plurality of workload agents based on a number of communication nodes between the primary workload agent and each of the plurality of workload agents, and selecting workload agents having a path length to the primary workload agent that is less than a threshold path length as the candidate secondary workload agents.

4. The method of claim 3, wherein identifying the plurality of candidate secondary workload agents further comprises receiving job workload information relating to the data processing task to be assigned to the primary workload agent, and selecting the candidate secondary workload agents in response to the job workload information.

5. The method of claim 4, wherein the job workload information characterizes a level of resources required by the data processing task that is to be assigned to the primary workload agent.

6. The method of claim 5, wherein identifying the candidate secondary workload agents comprises selecting only those workload agents of the plurality of workload agents that have sufficient resources to perform the data processing task that is to be assigned to the primary workload agent.

7. The method of claim 1, wherein the plurality of workload parameters comprise an available CPU metric, an available memory metric, an available workload capacity metric, and/or an available throughput metric.

8. The method of claim 1, wherein the selection function maximizes a weight adjust factor (WAF) output by a function based on:

9. The method of claim 8, wherein identifying the candidate secondary workload agents comprises identifying workload agents for which Mn>

Mn,t for each of N workload parameters, where Mn is the value of the nth workload parameter of the workload agent, and Mn,t is the threshold level for the nth workload parameter.

10. The method of claim 1, further comprising:

identifying a plurality of candidate tertiary workload agents from among the plurality of workload agents; and

identifying a tertiary workload agent from among the plurality of candidate tertiary workload agents based on the plurality of workload parameters;

wherein the forwarding map identifies the secondary workload agent and the tertiary workload agent, and wherein the job message contains a command for the primary workload agent to perform the data processing task using resources of the secondary workload agent and the tertiary workload agent.

11. A workload scheduling computer system, comprising:

a processor; and

a memory coupled to the processor, the memory comprising computer readable program code embodied therein that, when executed by the processor, causes the processor to perform operations comprising;

receiving, via a communication network, a plurality of workload parameters from a plurality of workload agents in communication with the workload scheduling computing device, wherein the workload parameters relate to available capacities of the plurality of workload agents and wherein the workload agents comprise computing nodes configured to perform data processing tasks;

identifying a primary workload agent from the plurality of workload agents based on at least one of the plurality of workload parameters;

identifying a plurality of candidate secondary workload agents from among the plurality of workload agents, wherein identifying the candidate secondary workload agents comprises identifying workload agents for which each of the workload parameters is greater than a respective threshold level;

identifying a secondary workload agent from among the plurality of candidate secondary workload agents based on the plurality of workload parameters that are greater than the respective threshold level and an evaluation of a selection function that mathematically evaluates the plurality of workload parameters to select a workload agent from among the candidate secondary workload agents; and

transmitting, via the communication network, a job message that contains a command for the primary workload agent to perform a data processing task, wherein the job message includes a forwarding map that identifies the secondary workload agent and that enables the primary workload agent to perform the data processing task using resources of the secondary workload agent without disrupting future operations of the workload scheduling computing device;

wherein the selection function comprises a weight adjusted function based on a root mean square of a weighted mean of the plurality workload parameters, wherein weights of the weighted mean are assigned to each of the respective workload parameters.

12. A method of assigning data processing tasks to workload agents, comprising:

performing operations as follows on a processor of a workload scheduling computing device;

receiving, via a communication network, a plurality of workload parameters from a plurality of workload agents in communication with the workload scheduling computing device, wherein the workload parameters relate to available capacities of the plurality of workload agents;

identifying a primary workload agent from the plurality of workload agents based on at least one of the plurality of workload parameters, wherein the plurality of workload parameters comprises a workload capacity, and wherein identifying the primary workload agent comprises determining which of the plurality of workload agents has a lowest workload capacity;

identifying a plurality of candidate secondary workload agents from among the plurality of workload agents by determining path lengths from the primary workload agent to the plurality of workload agents based on a number of communication nodes between the primary workload agent and each of the plurality of workload agents and selecting workload agents having a path length to the primary workload agent that is less than a threshold path length as the candidate secondary workload agents;

identifying a secondary workload agent from among the plurality of candidate secondary workload agents by evaluating a selection function based on;

13. The method of claim 12, wherein the plurality of workload parameters comprise an available CPU metric, an available memory metric, and/or an available throughput metric.

14. The method of claim 12, wherein identifying candidate secondary workload agents comprises identifying workload agents for which each of the workload parameters is greater than a respective threshold level.

15. The method of claim 12, wherein identifying the primary workload agent comprises identifying one of the plurality of workload agents that has a lowest workload capacity.

16. The method of claim 15, wherein the job workload information characterizes a level of resources required by the data processing task that is to be assigned to the primary workload agent;

and

wherein selecting the candidate secondary workload agents comprises selecting only those workload agents of the plurality of workload agents that have sufficient resources to perform the data processing task that is to be assigned to the primary workload agent.