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Efficient Mobile Edge Computing for Mobile Internet of Thing in 5G Networks
Item Summary
Title: | Efficient Mobile Edge Computing for Mobile Internet of Thing in 5G Networks |
Authors: | Zhu, Yi Chevalier, Kevin Wang, Xi Wang, Nannan |
Keywords: | Cellular and Wireless Networks 5g networks fully polynomial-time scheme integer linear programming internet of things show 1 moremobile edge computing show less |
Date Issued: | 07 Jan 2020 |
Abstract: | We 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. |
Pages/Duration: | 10 pages |
URI: | http://hdl.handle.net/10125/64514 |
ISBN: | 978-0-9981331-3-3 |
DOI: | 10.24251/HICSS.2020.772 |
Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International https://creativecommons.org/licenses/by-nc-nd/4.0/ |
Appears in Collections: |
Cellular and Wireless Networks |
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