Efficient Mobile Edge Computing for Mobile Internet of Thing in 5G Networks

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dc.contributor.authorZhu, Yi
dc.contributor.authorChevalier, Kevin
dc.contributor.authorWang, Xi
dc.contributor.authorWang, Nannan
dc.date.accessioned2020-01-04T08:29:38Z
dc.date.available2020-01-04T08:29:38Z
dc.date.issued2020-01-07
dc.description.abstractWe study the off-line efficient mobile edge computing (EMEC) problem for a joint computing to process a task both locally and remotely with the objective of minimizing the finishing time. When computing remotely, the time will include the communication and computing time. We first describe the time model, formulate EMEC, prove NP-completeness of EMEC, and show the lower bound. We then provide an integer linear programming (ILP) based algorithm to achieve the optimal solution and give results for small-scale cases. A fully polynomial-time approximation scheme (FPTAS), named Approximation Partition (AP), is provided through converting ILP to the subset sum problem. Numerical results show that both the total data length and the movement have great impact on the time for mobile edge computing. Numerical results also demonstrate that our AP algorithm obtain the finishing time, which is close to the optimal solution.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2020.772
dc.identifier.isbn978-0-9981331-3-3
dc.identifier.urihttp://hdl.handle.net/10125/64514
dc.language.isoeng
dc.relation.ispartofProceedings of the 53rd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCellular and Wireless Networks
dc.subject5g networks
dc.subjectfully polynomial-time scheme
dc.subjectinteger linear programming
dc.subjectinternet of things
dc.subjectmobile edge computing
dc.titleEfficient Mobile Edge Computing for Mobile Internet of Thing in 5G Networks
dc.typeConference Paper
dc.type.dcmiText

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