Mobile edge computing device eligibility determination

{
  "publication_number": "US10827033B1",
  "country": "US",
  "kind": "B1",
  "title": "Mobile edge computing device eligibility determination",
  "abstract": "Disclosed embodiments provide techniques for determining mobile device edge computing participation eligibility. Multiple mobile devices are identified for potential participation in an edge computing network. An eligibility score is computed for each mobile device of the plurality of mobile devices based on an estimated likelihood that the mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time. One or more mobile devices are selected for participation in the edge computing network based on their respective eligibility scores.",
  "claims": [
    "1. A computer-implemented method for determining mobile device edge computing participation eligibility, comprising: identifying a plurality of mobile devices for potential participation in an edge computing network; computing an eligibility score for each mobile device of the plurality of mobile devices based on an estimated likelihood that the mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time; and selecting one or more mobile devices of the plurality of mobile devices for participation in the edge computing network based on their respective eligibility scores.",
    "2. The computer-implemented method of claim 1, wherein computing an eligibility score for each mobile device of the plurality of mobile devices further includes performing an evaluation of available resources of each mobile device of the plurality of mobile devices.",
    "3. The computer-implemented method of claim 1, further comprising computing the estimated likelihood that the mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time based on a directional vector of the mobile device with respect to the local edge process server.",
    "4. The computer-implemented method of claim 1, further comprising computing the estimated likelihood that the mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time based on one or more calendar entries associated with the mobile device.",
    "5. The computer-implemented method of claim 1, further comprising computing the estimated likelihood that the mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time based on application activity associated with the mobile device.",
    "6. The computer-implemented method of claim 5, further comprising computing the estimated likelihood that the mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time based on rideshare application activity associated with the mobile device.",
    "7. The computer-implemented method of claim 1, further comprising computing the estimated likelihood that the mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time based on distance between the mobile device and the local edge process server.",
    "8. The computer-implemented method of claim 1, further comprising computing the estimated likelihood that the mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time based on a received signal strength indication of the mobile device.",
    "9. The computer-implemented method of claim 1, further comprising computing the estimated likelihood that the mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time based on a historical record of activity of the mobile device.",
    "10. The computer-implemented method of claim 1, further comprising computing the estimated likelihood that the mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time by: correlating the mobile device to a second mobile device to form a mobile device group; and applying an estimated likelihood that the second mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time, to the mobile device.",
    "11. The computer-implemented method of claim 1, further comprising computing the estimated likelihood that the mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time based on a speech utterance received by the mobile device.",
    "12. The computer-implemented method of claim 2, wherein performing an evaluation of available resources of each mobile device of the plurality of mobile devices includes obtaining an amount of available memory on the mobile device.",
    "13. The computer-implemented method of claim 11, wherein performing an evaluation of available resources of each mobile device of the plurality of mobile devices includes obtaining a processor type for the mobile device.",
    "14. The computer-implemented method of claim 12, wherein performing an evaluation of available resources of each mobile device of the plurality of mobile devices includes obtaining a processor speed for the mobile device.",
    "15. An electronic computation device comprising: a processor; a memory coupled to the processor, the memory containing instructions, that when executed by the processor, cause the electronic computation device to: identify a plurality of mobile devices for potential participation in an edge computing network; compute an eligibility score for each mobile device of the plurality of mobile devices based on an estimated likelihood that the mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time; and select one or more mobile devices of the plurality of mobile devices for participation in the edge computing network based on their respective eligibility scores.",
    "16. The electronic computation device of claim 15 wherein the memory further comprises instructions, that when executed by the processor, cause the electronic computation device to perform an evaluation of available resources of each mobile device of the plurality of mobile devices.",
    "17. The electronic computation device of claim 15 wherein the memory further comprises instructions, that when executed by the processor, cause the electronic computation device to: correlate the mobile device to a second mobile device to form a mobile device group; and associate an estimated likelihood that the second mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time, to the mobile device.",
    "18. A computer program product for an electronic computation device comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the electronic computation device to: identify a plurality of mobile devices for potential participation in an edge computing network; compute an eligibility score for each mobile device of the plurality of mobile devices based on an estimated likelihood that the mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time; and select one or more mobile devices of the plurality of mobile devices for participation in the edge computing network based on their respective eligibility scores.",
    "19. The computer program product of claim 18, wherein the computer readable storage medium includes program instructions executable by the processor to cause the electronic computation device to perform an evaluation of available resources of each mobile device of the plurality of mobile devices.",
    "20. The computer program product of claim 18, wherein the computer readable storage medium includes program instructions executable by the processor to cause the electronic computation device to: correlate the mobile device to a second mobile device to form a mobile device group; and associate an estimated likelihood that the second mobile device will remain within a predetermined distance of a local edge process server of an edge computing network for a duration exceeding a job time, to the mobile device."
  ],
  "description_excerpt": "The present invention relates generally to computer networks and, more particularly, to mobile edge computing device eligibility determination.\n\nEdge computing brings memory and computing power closer to the location where it is needed. It is a distributed computing paradigm in which computation is largely or completely performed on distributed device nodes. Edge computing pushes applications, data, and computing power away from centralized points to locations closer to the user. Mobile devices such as smartphones and tablet computers can use their own hardware and software as local services for processing the data collected from edge sensors, such as IoT (Internet of Things) sensors. To reduce costs and power requirements, the edge sensors may not have available memory or processing capability to process the data generated by the edge sensors. However, each generation of mobile devices has increased processing power over previous generations, and thus, some mobile devices present in proximity to the edge sensors can participate in processing of the data.",
  "cpc": [
    "H04L 67/63",
    "G06F 9/5027",
    "G06F 9/5061",
    "G06F 9/5072",
    "H04L 67/10",
    "H04L 67/1021",
    "H04L 67/12",
    "H04L 67/18",
    "H04L 67/327",
    "H04L 67/52",
    "H04W 52/0225",
    "Y02D 30/70"
  ],
  "ipc": [
    "G06F 15/16",
    "G06F 9/50",
    "H04L 29/08",
    "H04W 52/02"
  ],
  "assignees": [
    "International Business Machines Corp"
  ],
  "inventors": [
    "Swaminathan Balasubramanian",
    "Sarbajit K. Rakshit",
    "Ravi P. Bansal",
    "Pierre C. Berlandier"
  ],
  "filing_date": "2019-09-05",
  "publication_date": "2020-11-03",
  "grant_date": "2020-11-03",
  "priority_date": "2019-09-05",
  "application_number": "US-201916561119-A",
  "family_id": "73019859",
  "cited_by_count": 13,
  "citations": [
    "US20120158991A1",
    "US9467839B1",
    "WO2018082709A1",
    "US20190020657A1",
    "US20190158606A1"
  ]
}