Power Efficient User Cooperative Computation to Maximize Completed Tasks in MEC Networks

Yijin Pan, Cunhua Pan, Kezhi Wang, Huiling Zhu, Jiangzhou Wang

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Abstract

In this paper, the user cooperative task computation is explored by sharing the computing capability of the user equipments (UEs) so as to enhance the performance of mobile edge computing (MEC) networks. The number of completed tasks is maximized while minimizing the total power consumption of the UEs by jointly optimizing the user task offloading decision, the computational speed for the offloaded task and the transmit power for task offloading. An iterative algorithm based on the linear programming relaxation is proposed to solve the formulated mixed integer non-linear problem. The simulation results show that the proposed user cooperative computation scheme can achieve a higher completed tasks ratio than the noncooperative scheme.
Original languageEnglish
Title of host publicationProceedings of the 2019 2019 IEEE Global Communications Conference (GLOBECOM), December 9 – 13, in Waikoloa, Hawaii, USA
Place of PublicationPiscataway, NJ
PublisherIEEE
ISBN (Electronic)9781728109626
ISBN (Print)9781728109633
DOIs
Publication statusPublished - Dec 2019
Event2019 IEEE Global Communications Conference - Waikoloa, Big Island, Hawaii, United States
Duration: 9 Dec 201913 Dec 2019
https://globecom2019.ieee-globecom.org/

Conference

Conference2019 IEEE Global Communications Conference
Abbreviated titleGLOBECOM 2019
CountryUnited States
Period9/12/1913/12/19
Internet address

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