Joint Cotask-Aware Offloading and Scheduling in Mobile Edge Computing Systems

被引:13
|
作者
Chiang, Yi-Han [1 ]
Zhang, Tianyu [1 ,2 ]
Ji, Yusheng [1 ,2 ]
机构
[1] Natl Inst Informat, Informat Syst Architecture Res Div, Tokyo 1018430, Japan
[2] SOKENDAI, Dept Informat, Tokyo 1018430, Japan
来源
IEEE ACCESS | 2019年 / 7卷
基金
日本学术振兴会;
关键词
Cotask; mixed integer non-linear program; mobile edge computing system; task offloading; task scheduling; INTERNET; CLOUD;
D O I
10.1109/ACCESS.2019.2931336
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Mobile edge computing (MEC) systems provide mobile devices (MDs) with low-latency cloud services by deploying edge servers (ESs) in the vicinity. In fact, various mobile applications may generate cotasks, each of which is completed only if all its constituent tasks are finished. Existing works have been devoted to the design of MEC offloading and scheduling, but none of them exploits the cotask feature to better utilize the networked computing resources. In this paper, we investigate the problem of joint cotask-aware offloading and scheduling in MEC systems (Cool-Edge), and we formulate it as a mixed integer non-linear program (MINLP), the objective of which is to minimize average cotask completion time (ACCT). To cope with the Cool-Edge problem, we propose two low-complexity algorithms to offload cotasks based on an LP rounding technique and schedule them according to an earliest-cotask-arrival-first rule, respectively, and we further prove the approximation factor jointly achieved by the two algorithms. Finally, we conduct testbed experiments and simulations to demonstrate the effectiveness of our proposed solution, and we also show how ACCT varies with the network environment.
引用
下载
收藏
页码:105008 / 105018
页数:11
相关论文
共 50 条
  • [31] Location-aware Task Offloading in Mobile Edge Computing
    Gao, Yongqiang
    Li, Jixiao
    2022 IEEE INTL CONF ON PARALLEL & DISTRIBUTED PROCESSING WITH APPLICATIONS, BIG DATA & CLOUD COMPUTING, SUSTAINABLE COMPUTING & COMMUNICATIONS, SOCIAL COMPUTING & NETWORKING, ISPA/BDCLOUD/SOCIALCOM/SUSTAINCOM, 2022, : 660 - 667
  • [32] Contact Ratio Aware Mobile Edge Computing for Content Offloading
    Yuan, Peiyan
    Cai, Yunyun
    2019 IEEE 25TH INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED SYSTEMS (ICPADS), 2019, : 520 - 524
  • [33] Context-aware computation offloading for mobile edge computing
    Farahbakhsh, Fariba
    Shahidinejad, Ali
    Ghobaei-Arani, Mostafa
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2021, 14 (5) : 5123 - 5135
  • [34] Privacy-Aware Offloading in Mobile-Edge Computing
    He, Xiaofan
    Liu, Juan
    Jin, Richeng
    Dai, Huaiyu
    GLOBECOM 2017 - 2017 IEEE GLOBAL COMMUNICATIONS CONFERENCE, 2017,
  • [35] Latency-Aware Offloading for Mobile Edge Computing Networks
    Feng, Wei
    Liu, Hao
    Yao, Yingbiao
    Cao, Diqiu
    Zhao, Mingxiong
    IEEE COMMUNICATIONS LETTERS, 2021, 25 (08) : 2673 - 2677
  • [36] Age Based Task Scheduling and Computation Offloading in Mobile-Edge Computing Systems
    Song, Xianxin
    Qin, Xiaoqi
    Tao, Yunzheng
    Liu, Baoling
    Zhang, Ping
    2019 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE WORKSHOP (WCNCW), 2019,
  • [37] Stochastic Computation Offloading and Scheduling Based on Mobile Edge Computing
    Zheng, Xiao
    Li, Mingchu
    Tahir, Muhammad
    Chen, Yuanfang
    Alam, Muhammad
    IEEE ACCESS, 2019, 7 : 72247 - 72256
  • [38] Computation Offloading Scheduling for Periodic Tasks in Mobile Edge Computing
    Josilo, Sladana
    Dan, Gyorgy
    IEEE-ACM TRANSACTIONS ON NETWORKING, 2020, 28 (02) : 667 - 680
  • [39] Decentralized Scheduling for Offloading of Periodic Tasks in Mobile Edge Computing
    Josilo, Sladana
    Dan, Gyorgy
    2018 IFIP NETWORKING CONFERENCE (IFIP NETWORKING) AND WORKSHOPS, 2018, : 469 - 477
  • [40] Joint Service Caching, Computation Offloading and Resource Allocation in Mobile Edge Computing Systems
    Zhang, Guanglin
    Zhang, Shun
    Zhang, Wenqian
    Shen, Zhirong
    Wang, Lin
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2021, 20 (08) : 5288 - 5300