Task Offloading Scheduling in Mobile Edge Computing Networks

被引：11
|
作者：
Wang, Zhonglun [1 ,2 ]
Li, Peifeng [2 ]
Shen, Shuai [2 ]
Yang, Kun [1 ,3 ]
机构：
[1] Univ Elect Sci & Technol China, Quzhou Res Inst, Quzhou, Zhejiang, Peoples R China
[2] Univ Elect Sci & Technol China, Chengdu 611731, Peoples R China
[3] Univ Essex, Sch Comp Sci & Elect Engn, Colchester CO4 3SQ, Essex, England
来源：
12TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 4TH INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS | 2021年 / 184卷
基金：
欧盟地平线“2020”;
关键词：
Energy minimization; offloading number maximization; mobile edge computing; load balancing; ant colony optimization algorithm; POWER-CONTROL;
D O I：
10.1016/j.procs.2021.03.041
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, we investigate the task scheduling in resource-limited mobile edge computing (MEC) network, where multiple base stations (BSs), each equipped with a MEC server, assist multiple latency-sensitive user equipments (UEs) in computing. We aim to jointly minimize the system energy consumption and maximize the number of offloaded tasks by optimizing the task scheduling between UEs and BSs. A multiple-objective and mix-integer problem is formulated, which is difficult to solve. To tackle the problem, we combine the ant colony optimization (ACO) algorithm with load balancing, and propose an efficient algorithm. The simulation demonstrates the effectiveness of the proposed algorithm. (C) 2021 The Authors. Published by Elsevier B.V.
引用
收藏
页码：322 / 329
页数：8
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