Distributed load processing using clusters of interdependent internet of things devices

Patent metadata

Field	Value
Publication number	US-9990234-B2
Application number	US-201615041252-A
Country	US
Kind code	B2
Filing date	Feb 11, 2016
Priority date	Feb 11, 2016
Publication date	Jun 5, 2018
Grant date	Jun 5, 2018

Abstract

For distributed processing using clustering of interdependent Internet of Things (IoT) devices, at a central device, a data source to be used for processing a workload is determined. A set is selected of devices operating within a threshold distance from the data source at a first time. A first subset of the set of devices is selected. Each device in the first subset satisfies a clustering condition. A first device in the subset is instructed to configure a lightweight application to participate in the cluster and process the workload. The processing of the workload is halted on a second device, where the first device has a processing dependency on the second device in processing the workload. A preserved current state of processing the workload is transferred from the first device to a third device. The processing of the workload is continued using the second device and the third device.

First claim

What is claimed is:

1. A method for distributed processing using clustering of interdependent Internet of Things (IoT) devices, the method comprising:
determining, using a processor and a memory at a central IoT device, a data source that is to be used for processing a workload;
selecting a set of IoT devices that are operating within a threshold distance from the data source at a first time;
selecting, at the central IoT device, to form a cluster of IoT devices, a first subset of the set of IoT devices, wherein each IoT device in the first subset satisfies a clustering condition;
configuring, by instructing a processor at a first IoT device to configure a lightweight application at the first IoT device, the lightweight application enabling the first IoT device to participate in the cluster and process the workload;
halting a processing of the workload on a second IoT device responsive to determining that the first IoT device is to be replaced, wherein the first IoT device has a processing dependency on the second IoT device in processing the workload;
transferring a preserved current state of processing the workload from the first IoT device to a third IoT device;
continuing processing the workload using the second IoT device and the third IoT device;
dropping, responsive to determining at a second time that the first IoT device has moved to a distance greater than the threshold distance from the data source;
joining a fourth IoT device to the cluster, wherein the fourth IoT device has moved within the threshold distance from the data source at the second time, and wherein the fourth IoT device satisfies the clustering condition; and
transferring the processing of the workload from the first IoT device to the fourth IoT device.

2. The method of claim 1 , further comprising:
preserving, responsive to the determining that the first IoT device is to be replaced, the current state of processing of the workload in the first IoT device.

3. The method of claim 1 , further comprising:
removing the first IoT device from the primary-redundant configuration; and
configuring the third IoT device in the processing dependency configuration with the second IoT device in the cluster.

4. The method of claim 1 , further comprising:
configuring the first IoT device in a high-availability configuration with the second IoT device in the cluster.

5. The method of claim 1 , further comprising:
determining that the first IoT device satisfies the clustering condition by determining that the first IoT device has a particular amount of a particular computing resource available and unused over a duration during which the workload has to be processed.

6. The method of claim 1 , further comprising:
determining that the first IoT device satisfies the clustering condition by determining that the first IoT device has a permission to make a particular computing resource available over a duration during which the workload has to be processed.

7. The method of claim 1 , further comprising:
determining that the first IoT device satisfies the clustering condition by determining that the first IoT device produces a response to a benchmark workload where a recall of the response exceeds a threshold.

8. The method of claim 1 , further comprising:
determining that the first IoT device satisfies the clustering condition by determining that the first IoT device produces a response to a benchmark workload where a precision of the response exceeds a threshold.

9. The method of claim 1 , further comprising:
determining that the first IoT device satisfies the clustering condition by determining that the first IoT device produces a response to a benchmark workload within a threshold amount of time.

10. The method of claim 1 , further comprising:
decomposing the workload into a set of workload components, wherein a first workload component is at the threshold distance from the data source and a second workload component is at a second threshold distance from a second data source, and wherein assigning the workload to the cluster comprises assigning the first workload component to the cluster.

11. The method of claim 1 , wherein the threshold distance comprises a geographical distance on a geographical map, and wherein the threshold distance defines a shaped area on the geographical map.

12. The method of claim 1 , wherein the threshold distance comprises a number of hops in a data network.

13. The method of claim 1 , further comprising:
determining, using publications from the set of IoT devices on a social media platform, the locations of the IoT devices in the set of IoT devices; and
determining that each of the locations is within the threshold distance from the data source at the first time.

14. The method of claim 1 , wherein the method is embodied in a computer program product comprising one or more computer-readable storage devices and computer-readable program instructions which are stored on the one or more computer-readable tangible storage devices and executed by one or more processors.

15. The method of claim 1 , wherein the method is embodied in a computer system comprising one or more processors, one or more computer-readable memories, one or more computer-readable storage devices and program instructions which are stored on the one or more computer-readable storage devices for execution by the one or more processors via the one or more memories and executed by the one or more processors.

16. A computer program product for distributed processing using clustering of interdependent Internet of Things (IoT) devices, the computer program product comprising one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices, the stored program instructions comprising:
program instructions to determine, using a processor and a memory at a central IoT device, a data source that is to be used for processing a workload;
program instructions to select a set of IoT devices that are operating within a threshold distance from the data source at a first time;
program instructions to select, at the central IoT device, to form a cluster of IoT devices, a first subset of the set of IoT devices, wherein each IoT device in the first subset satisfies a clustering condition;
program instructions to configure, by instructing a processor at a first IoT device to configure a lightweight application at the first IoT device, the lightweight application enabling the first IoT device to participate in the cluster and process the workload;
program instructions to halt a processing of the workload on a second IoT device responsive to determining that the first IoT device is to be replaced, wherein the first IoT device has a processing dependency on the second IoT device in processing the workload;
program instructions to transfer a preserved current state of processing the workload from the first IoT device to a third IoT device;
program instructions to continue processing the workload using the second IoT device and the third IoT device;
program instructions to drop, responsive to determining at a second time that the first IoT device has moved to a distance greater than the threshold distance from the data source;
program instructions to join a fourth IoT device to the cluster, wherein the fourth IoT device has moved within the threshold distance from the data source at the second time, and wherein the fourth IoT device satisfies the clustering condition; and
program instructions to transfer the processing of the workload from the first IoT device to the

Assignees

• IBM

Inventors

• Baughman Aaron K
• Harrison Thomas Benjamin
• O'Connell Brian M
• Pearthree Herbert D

Classifications

• H04W4/70

  Services for machine-to-machine communication [M2M] or machine type communication [MTC] · CPC title

• H04L67/10

  in which an application is distributed across nodes in the network (software deployment G06F8/60; multiprogramming arrangements G06F9/46) · CPC title

• G06F9/5088

  involving task migration · CPC title

• G06F9/4856

  resumption being on a different machine, e.g. task migration, virtual machine migration (G06F9/5088 takes precedence) · CPC title

• G06F9/505 Primary

  considering the load · CPC title