AuthorsK. Zhang, Y. Mao, S. Leng, Q. Zhao, L. Li, X. Peng, L. Pan, G. Zhang, S. Maharjan and Y. Zhang
TitleEnergy-efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks
AfilliationCommunication Systems
Project(s)The Center for Resilient Networks and Applications
StatusPublished
Publication TypeJournal Article
Year of Publication2016
JournalIEEE Access
Volume4
Pagination5896-5907
PublisherIEEE
Abstract

Mobile Edge Computing (MEC) is a promising paradigm to provide cloud-computing capabilities in close proximity to mobile devices in fifth-generation (5G) networks. In this paper, we study energy-efficient computation offloading mechanisms for MEC in 5G heterogenous networks. We formulate an optimization problem to minimize the energy consumption of the offloading system, where the energy cost of both task computing and file transmission are taken into consideration. Incorporating the multi-access characteristics of the 5G heterogenous network, we then design an Energy-Efficient Computation Offloading (EECO) scheme, which jointly optimizes offloading and radio resource allocation to obtain the minimal energy consumption under the latency constraints. Numerical results demonstrate energy efficiency improvement of our proposed EECO scheme.

DOI10.1109/ACCESS.2016.2597169
Citation Key24611