Profit Maximization Incentive Mechanism for Resource Providers in Mobile Edge Computing

被引:71
|
作者
Wang, Quyuan [1 ]
Guo, Songtao [2 ,3 ]
Liu, Jiadi [1 ]
Pan, Chengsheng [4 ]
Yang, Li [4 ]
机构
[1] Southwest Univ, Coll Elect & Informat Engn, Chongqing Key Lab Nonlinear Circuits & Intelligen, Chongqing 400715, Peoples R China
[2] Chongiqng Univ, Coll Comp Sci, Chongqing 400044, Peoples R China
[3] Southwest Univ, Coll Elect & Informat Engn, Chongqing 400715, Peoples R China
[4] Dalian Univ, Coll Informat Engn, Dalian 116622, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Mobile edge computing; incentive mechanism; convex optimization; auction mechanism; AUCTIONS; FRAMEWORK;
D O I
10.1109/TSC.2019.2924002
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) has become a promising technique to accommodate demands of resource-constrained mobile devices by offloading the task onto edge clouds nearby. However, most existing works only focus on whether to offload or where to offload the task but ignore the motivations of edge clouds to offer service. To stimulate service provisioning by edge clouds, it is essential to design an incentive mechanism that charges mobile devices and rewards edge clouds. In this paper, we first propose an incentive mechanism in a non-competitive environment. We utilize market-based profit maximization pricing model to establish the relationship between the resources provided by edge clouds and the price charged to mobile devices. By solving the optimization problem, we provide a reasonable pricing strategy to not only ensure the profit of resource providers but guarantee the quality of experience (QoE) of mobile devices. Furthermore, we design an online profit maximization multi-round auction (PMMRA) mechanism for the resource trading between edge clouds as sellers and mobile devices as buyers in a competitive environment. The mechanism can effectively determine the price paid by buyers to use the resources provided by sellers and make the corresponding match between edge clouds and mobile devices. Finally, numerical results show that proposed mechanism outperforms other existing algorithms in maximizing the profit of edge clouds.
引用
收藏
页码:138 / 149
页数:12
相关论文
共 50 条
  • [1] Incentive Mechanism for Edge Cloud Profit Maximization in Mobile Edge Computing
    Wang, Quyuan
    Guo, Songtao
    Wang, Ying
    Yang, Yuanyuan
    [J]. ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2019,
  • [2] PRIMAL: PRofIt Maximization Avatar pLacement for Mobile Edge Computing
    Sun, Xiang
    Ansari, Nirwan
    [J]. 2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2016,
  • [3] Platform Profit Maximization on Service Provisioning in Mobile Edge Computing
    Huang, Xiaoyao
    Zhang, Baoxian
    Li, Cheng
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 70 (12) : 13364 - 13376
  • [4] Scalable Profit Optimized Incentive Mechanism for Resources in Cloudlet Based Mobile Edge Computing Framework
    Yadav, Santosh Kumar
    Kumar, Rakesh
    [J]. WIRELESS PERSONAL COMMUNICATIONS, 2022, 125 (01) : 159 - 207
  • [5] Scalable Profit Optimized Incentive Mechanism for Resources in Cloudlet Based Mobile Edge Computing Framework
    Santosh Kumar Yadav
    Rakesh Kumar
    [J]. Wireless Personal Communications, 2022, 125 : 159 - 207
  • [6] Game Theoretical Task Offloading for Profit Maximization in Mobile Edge Computing
    Teng, Haojun
    Li, Zhetao
    Cao, Kun
    Long, Saiqin
    Guo, Song
    Liu, Anfeng
    [J]. IEEE TRANSACTIONS ON MOBILE COMPUTING, 2023, 22 (09) : 5313 - 5329
  • [7] Auction-based profit maximization offloading in mobile edge computing
    Ruyan Wang
    Chunyan Zang
    Peng He
    Yaping Cui
    Dapeng Wu
    [J]. Digital Communications and Networks, 2023, 9 (02) : 545 - 556
  • [8] Auction-based profit maximization offloading in mobile edge computing
    Wang, Ruyan
    Zang, Chunyan
    He, Peng
    Cui, Yaping
    Wu, Dapeng
    [J]. DIGITAL COMMUNICATIONS AND NETWORKS, 2023, 9 (02) : 545 - 556
  • [9] Gamified incentive sharing mechanism of edge computing among edge service providers
    Du, Helen S.
    Lin, Yixun
    Zhang, Fenghua
    Zhang, Depeng
    [J]. JOURNAL OF CLEANER PRODUCTION, 2022, 376
  • [10] Profit Maximization for Cache-Enabled Vehicular Mobile Edge Computing Networks
    Zhou, Wenqi
    Xia, Junjuan
    Zhou, Fasheng
    Fan, Lisheng
    Lei, Xianfu
    Nallanathan, Arumugam
    Karagiannidis, George K.
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2023, 72 (10) : 13793 - 13798