Matching IoT Devices to the Fog Service Providers: A Mechanism Design Perspective†

被引:5
作者
Bandyopadhyay, Anjan [1 ,2 ]
Singh, Vikash Kumar [3 ]
Mukhopadhyay, Sajal [1 ]
Rai, Ujjwal [1 ]
Xhafa, Fatos [4 ]
Krause, Paul [5 ]
机构
[1] Natl Inst Technol Durgapur, Dept Comp Sci & Engn, Durgapur 713209, W Bengal, India
[2] Amity Univ, Amity Sch Engn & Technol Kolkata, Kolkata 700157, W Bengal, India
[3] VIT AP Univ, Sch Comp Sci & Engn, Amaravati 522237, Andhra Pradesh, India
[4] Univ Politecn Cataluna, Dept Comp Sci, Barcelona 08034, Spain
[5] Univ Surrey, Dept Comp Sci, Guildford GU2 7XH, Surrey, England
关键词
Fog computing; matching; mechanism design; IoT devices; truthful; Pareto optimal; truthful mechanism; ALLOCATION; STABILITY; AUCTION;
D O I
10.3390/s20236761
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
In the Internet of Things (IoT) + Fog + Cloud architecture, with the unprecedented growth of IoT devices, one of the challenging issues that needs to be tackled is to allocate Fog service providers (FSPs) to IoT devices, especially in a game-theoretic environment. Here, the issue of allocation of FSPs to the IoT devices is sifted with game-theoretic idea so that utility maximizing agents may be benign. In this scenario, we have multiple IoT devices and multiple FSPs, and the IoT devices give preference ordering over the subset of FSPs. Given such a scenario, the goal is to allocate at most one FSP to each of the IoT devices. We propose mechanisms based on the theory of mechanism design without money to allocate FSPs to the IoT devices. The proposed mechanisms have been designed in a flexible manner to address the long and short duration access of the FSPs to the IoT devices. For analytical results, we have proved the economic robustness, and probabilistic analyses have been carried out for allocation of IoT devices to the FSPs. In simulation, mechanism efficiency is laid out under different scenarios with an implementation in Python.
引用
收藏
页码:1 / 32
页数:32
相关论文
共 39 条
  • [11] Bonomi F., P 1 ED MCC WORKSH MO, P13, DOI 10.1145/2342509.2342513
  • [12] QoS-Aware Deployment of IoT Applications Through the Fog
    Brogi, Antonio
    Forti, Stefano
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2017, 4 (05): : 1185 - 1192
  • [13] Stability of Service under Time-of-Use Pricing
    Chawla, Shuchi
    Devanur, Nikhil R.
    Holroyd, Alexander E.
    Karlin, Anna R.
    Martin, James B.
    Sivan, Balasubramanian
    [J]. STOC'17: PROCEEDINGS OF THE 49TH ANNUAL ACM SIGACT SYMPOSIUM ON THEORY OF COMPUTING, 2017, : 184 - 197
  • [14] Cost-Aware Streaming Workflow Allocation on Geo-Distributed Data Centers
    Chen, Wuhui
    Paik, Incheon
    Li, Zhenni
    [J]. IEEE TRANSACTIONS ON COMPUTERS, 2017, 66 (02) : 256 - 271
  • [15] Cormen Thomas H., 2009, J OPER RES SOC, V3rd
  • [16] Fawcett Lyndon, 2016, 2016 Fifth European Workshop on Software-Defined Networks (EWSDN). Proceedings, P62, DOI 10.1109/EWSDN.2016.16
  • [17] COLLEGE ADMISSIONS AND STABILITY OF MARRIAGE
    GALE, D
    SHAPLEY, LS
    [J]. AMERICAN MATHEMATICAL MONTHLY, 1962, 69 (01) : 9 - &
  • [18] Joint Radio and Computational Resource Allocation in IoT Fog Computing
    Gu, Yunan
    Chang, Zheng
    Pan, Miao
    Song, Lingyang
    Han, Zhu
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2018, 67 (08) : 7475 - 7484
  • [19] Survey on fog computing: architecture, key technologies, applications and open issues
    Hu, Pengfei
    Dhelim, Sahraoui
    Ning, Huansheng
    Qiu, Tie
    [J]. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2017, 98 : 27 - 42
  • [20] A Task Scheduling Algorithm Based on Classification Mining in Fog Computing Environment
    Liu, Lindong
    Qi, Deyu
    Zhou, Naqin
    Wu, Yilin
    [J]. WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2018,