Identifying multiple resources to perform a service request

• US 10,169,096 B2
• Filed: 10/23/2014
• Issued: 01/01/2019
• Est. Priority Date: 07/30/2014
• Status: Active Grant

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Zeng, Jun, Bhattacharya, Sushant, Dispoto, Gary Joseph, Allen, William James, Sandfort, Patrick O'Neil, Oblea Ramirez, Francisco Jose, Simske, Steven John
• Primary Examiner(s): Kessler, Gregory A
• Application Number:
  US15/500,510
• Publication Number:
  US 20170212788A1
• Time in Patent Office: 1,531 Days
• Field of Search: None
• CPC Class Codes: G06F 2209/501 Performance criteria
• CPC Class Codes: G06F 3/121 Facilitating exception or error detection and recovery, e.g. fault, media or consumables depleted
• CPC Class Codes: G06F 3/1231 Device related settings, e.g. IP address, Name, Identification
• CPC Class Codes: G06F 9/4881 Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
• CPC Class Codes: G06F 9/505 considering the load

Abstract

Examples herein disclose receiving a service request including a latency associated with a publication of a result of the service request. The examples disclose computing a workload for the service request and identifying multiple resources which are to perform the service request by applying the latency to the multiple resources.

Claims

1. A method for scheduling a service request, the method comprising:

receiving the service request including a latency associated with a publication of a result of the service request;

retrieving heterogeneous data upon the receipt of the service request;

filtering the heterogeneous data to obtain data relevant to the service request;

determining an amount of relevant data prior to computing a workload for the service request;

computing the workload for the service request;

identifying multiple resources, based on the latency and the workload, to perform the service request;

distributing the workload to the identified multiple resources; and

publishing the results of the service request in accordance with the latency.

2. The method of claim 1 wherein computing the workload comprises:

identifying the data relevant to the service request; and

determining the amount of the relevant data.

3. The method of claim 1 wherein identifying the multiple resources, based on the latency and the workload, to perform the service request comprises:

representing the workload as a vector;

obtaining a resource profile of the multiple resources for the workload; and

applying the latency to the resource profile to identify the multiple resources for performing the service request.

4. The method of claim 1 wherein identifying the multiple resources, based on the latency and the workload, to perform the service request comprises

mapping the workload to multiple resources;

and

applying the latency to the multiple resources for identifying the multiple resources to perform the service request.

5. The method of claim of claim 1 wherein identified multiple resources include multiple virtual machines with different computing capabilities.

6. A system comprising a processor to:

receive a service request including a latency associated with a publication of a result of the service request;

retrieve heterogeneous data;

filter the heterogeneous data for obtaining data relevant to a service request;

compute a workload for the service request;

determine a workload capability for each of multiple resources; and

identify the multiple resources that are to perform the service request by applying the latency to the multiple resources, wherein the relevant data is represented as the workload for identifying the multiple resources.

7. The system of claim 6, wherein the processor is to publish results of the service results in accordance with the latency.

8. The system of claim 6, wherein the processor is to distribute the workload to the identified multiple resources, the distribution of the workload is different for each of the identified multiple resources.

9. The system of claim 6 comprising:

a data storage to maintain heterogeneous data for retrieval by the scheduling module for computing the workload.

10. A non-transitory machine-readable storage medium comprising instructions that when executed by a processing resource cause a computing device to:

retrieve heterogeneous data;

filter the heterogeneous data for obtaining data relevant to a service request;

compute a workload for the service request, wherein the service request includes a latency associated with a publication of result of the service request;

identify multiple resources, based on the latency and the workload, to perform the service request, wherein the relevant data is represented as the workload for identifying the multiple resources;

distribute the workload to the identified multiple resources, wherein the distribution of the workload is different for each of the identified multiple resources; and

publish the results of the service request in accordance with the latency.

11. The non-transitory machine-readable storage medium of claim 10 comprising instructions that when executed by the processing resource cause the computing device to:

receive the service request.

12. The non-transitory machine-readable storage medium of claim 10 wherein computing the workload is comprising instructions that when executed by the processing resource causes the computing device to:

identify the data relevant to the service request;

determine an amount of the relevant data; and

express the relevant data as a vector of the workload; and

determine a number of the multiple resources to perform the workload.

13. The non-transitory machine-readable storage medium of claim 10 wherein identifying the multiple resources, based on the latency and the workload, to perform the service request is comprising instructions that when executed by the processing resource causes the computing device to:

obtain a resource profile for workload, the resource profile includes the multiple resources; and

determine a combination of the multiple resources for identifying the multiple resources to perform the service request based on the latency.