A Multiobjective Computation Offloading Algorithm for Mobile Edge Computing

Impact Factor:9.471

DOI number:10.1109/JIOT.2020.2996762

Affiliation of Author(s):Southwest Jiaotong Univ, Sch Informat Sci & Technol

Journal:IEEE Internet of Things Journal

Key Words:Task analysis,Energy consumption,Heuristic algorithms,ServersDelays,Cloud computing,Optimization,Computation offloading,dynamic voltage and frequency scaling (DVFS),mobile-edge computing (MEC),multiobjective evolutionary algorithm (MOEA)

Abstract:In mobile-edge computing (MEC), smart mobile devices (SMDs) with limited computation resources and battery lifetime can offload their computing-intensive tasks to MEC servers, thus to enhance the computing capability and reduce the energy consumption of SMDs. Nevertheless, offloading tasks to the edge incurs additional transmission time and thus higher execution delay. This article studies the tradeoff between the completion time of applications and the energy consumption of SMDs in MEC networks. The problem is formulated as a multiobjective computation offloading problem (MCOP), where the task precedence, i.e., ordering of tasks in SMD applications, is introduced as a new constraint in the MCOP. An improved multiobjective evolutionary algorithm based on decomposition (MOEA/D) with two performance enhancing schemes is proposed: 1) the problem-specific population initialization scheme uses a latency-based execution location (EL) initialization method to initialize the EL (i.e., either local SMD or MEC server) for each task and 2) the dynamic voltage and frequency scaling-based energy conservation scheme helps to decrease the energy consumption without increasing the completion time of applications. The simulation results clearly demonstrate that the proposed algorithm outperforms a number of state-of-the-art heuristics and metaheuristics in terms of the convergence and diversity of the obtained nondominated solutions.

Co-author:Fuhong Song,Huanlai Xing*,Shouxi Luo,Dawei Zhan,Penglin Dai,Rong Qu

Document Code:10.1109/JIOT.2020.2996762

Volume:7

Issue:9

Page Number:8780-8799

ISSN No.:2327-4662

Translation or Not:no

Date of Publication:2020-10-06

Included Journals:SCI