CoOMO: Cost-efficient Computation Outsourcing with Multi-site Offloading for Mobile-Edge Services

被引:1
|
作者
Meng, Tianhui [1 ]
Wu, Huaming [2 ]
Shang, Zhihao [3 ]
Zhao, Yubin [1 ]
Xu, Cheng-Zhong [4 ,5 ]
机构
[1] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China
[2] Tianjin Univ, Tianjin, Peoples R China
[3] Free Univ Berlin, Berlin, Germany
[4] Univ Macau, State Key Lab IoTSC, Macau, Peoples R China
[5] Univ Macau, Dept Comp & Informat Sci, Macau, Peoples R China
来源
2020 16TH INTERNATIONAL CONFERENCE ON MOBILITY, SENSING AND NETWORKING (MSN 2020) | 2020年
关键词
Computation outsourcing; Multi-site offloading; Mobile-edge computing; Queueing networks; DECISION;
D O I
10.1109/MSN50589.2020.00033
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 phones and tablets are becoming the primary platform of choice. However, these systems still suffer from limited battery and computation resources. A popular technique in mobile edge systems is computing outsourcing that augments the capabilities of mobile systems by migrating heavy workloads to resourceful clouds located at the edges of cellular networks. In the multi-site scenario, it is possible for mobile devices to save more time and energy by offloading to several cloud service providers. One of the most important challenges is how to choose servers to offload the jobs. In this paper, we consider a multi-site decision problem. We present a scheme to determine the proper assignment probabilities in a two-site mobile-edge computing system. We propose an open queueing network model for an offloading system with two servers and put forward performance metrics used for evaluating the system. Then in the specific scenario of a mobile chess game, where the data transmission is small but the computation jobs are relatively heavy, we conduct offloading experiments to obtain the model parameters. Given the parameters as arrival rates and service rates, we calculate the optimal probability to assign jobs to offload or locally execute and the optimal probabilities to choose different cloud servers. The analysis results confirm that our multi-site offloading scheme is beneficial in terms of response time and energy usage. In addition, sensitivity analysis has been conducted with respect to the system arrival rate to investigate wider implications of the change of parameter values.
引用
收藏
页码:113 / 120
页数:8
相关论文
共 50 条
  • [31] Online Computation Offloading and Resource Scheduling in Mobile-Edge Computing
    Liu, Tong
    Zhang, Yameng
    Zhu, Yanmin
    Tong, Weiqin
    Yang, Yuanyuan
    IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (08) : 6649 - 6664
  • [32] Multi-Persona Mobility: Joint Cost-Effective and Resource-Aware Mobile-Edge Computation Offloading
    Tout, Hanine
    Mourad, Azzam
    Kara, Nadjia
    Talhi, Chamseddine
    IEEE-ACM TRANSACTIONS ON NETWORKING, 2021, 29 (03) : 1408 - 1421
  • [33] Joint Trajectory Optimization and Mobile-Edge Computation Offloading for Multi-UAV-Connected System
    Li, Yang
    Ye, Liang
    Meng, WeiXiao
    Li, Cheng
    ICC 2023-IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 2023, : 5432 - 5437
  • [34] Mobile-Edge Computation Offloading and Resource Allocation in Heterogeneous Wireless Networks
    Lan, Yanwen
    Wang, Xiaoxiang
    Wang, Dongyu
    Zhang, Yibo
    Wang, Wei
    2019 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2019,
  • [35] Computation Offloading for Mobile-Edge Computing with Maximum Flow Minimum Cut
    Dong, Luobing
    Wang, Fei
    Shan, Junyuan
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND APPLICATION ENGINEERING (CSAE2018), 2018,
  • [36] Cooperative Resource Allocation for Computation Offloading in Mobile-Edge Computing Networks
    Li, Qun
    Shao, Hanqin
    2021 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2021,
  • [37] Collaborative Computation Offloading in Wireless Powered Mobile-Edge Computing Systems
    He, Binqi
    Bi, Suzhi
    Xing, Hong
    Lin, Xiaohui
    2019 IEEE GLOBECOM WORKSHOPS (GC WKSHPS), 2019,
  • [38] Dynamic Computation Offloading for Mobile-Edge Computing With Energy Harvesting Devices
    Mao, Yuyi
    Zhang, Jun
    Letaief, Khaled B.
    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2016, 34 (12) : 3590 - 3605
  • [39] Computation Rate Maximization for Wireless Powered Mobile-Edge Computing With Binary Computation Offloading
    Bi, Suzhi
    Zhang, Ying Jun
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2018, 17 (06) : 4177 - 4190
  • [40] Cost-Efficient Task Offloading in Mobile Edge Computing With Layered Unmanned Aerial Vehicles
    Yuan, Haitao
    Wang, Meijia
    Bi, Jing
    Shi, Shuyuan
    Yang, Jinhong
    Zhang, Jia
    Zhou, MengChu
    Buyya, Rajkumar
    IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (19): : 30496 - 30509