An Request Offloading and Scheduling Approach Base on Particle Swarm Optimization Algorithm in IoT-Fog Networks

被引:5
作者
Ju, Chengen [1 ,2 ,3 ]
Ma, Yue [1 ,3 ]
Yin, Zhenyu [1 ,3 ]
Zhang, Feiqing [1 ,2 ,3 ]
机构
[1] Chinese Acad Sci, Shenyang Inst Comp Technol, Beijing, Peoples R China
[2] Univ Chinese Acad Sci, Beijing, Peoples R China
[3] Liaoning Key Lab Domest Ind Control Platform Tech, Shenyang 110168, Peoples R China
来源
2021 13TH INTERNATIONAL CONFERENCE ON COMMUNICATION SOFTWARE AND NETWORKS (ICCSN 2021) | 2021年
关键词
industrial internet of things; fog computing network; request offloading and scheduling; particle swarm optimization;
D O I
10.1109/ICCSN52437.2021.9463602
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In Industrial Internet of Things environment, the requests from the terminal devices are usually processed by the fog servers. However, due to the limited hardware resources and software resources, the fog server may be in a high load state in some time. In this case, some real-time requests may not be processed in time, which will affect the performance of the network. Hence, we propose a request offloading and scheduling approach to improve the performance of the net in processing the requests. Considering the influence of the distance between the devices on wireless communication, and the different deadlines of requests, we sort the terminal devices, and add the deadline of the request and the communication distance between the devices into the offloading and scheduling algorithm. These methods not only consider the real-time nature of requests, but also minimizes the average processing delay of requests. Finally, the simulation results prove that the proposed method is verified with efficacy.
引用
收藏
页码:185 / 188
页数:4
相关论文
共 12 条
  • [1] Scheduling Internet of Things requests to minimize latency in hybrid Fog-Cloud computing
    Aburukba, Raafat O.
    AliKarrar, Mazin
    Landolsi, Taha
    El-Fakih, Khaled
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2020, 111 (539-551): : 539 - 551
  • [2] Antonio, 2014, CISCO DELIVERS VISIO
  • [3] Bonomi F., 2012, P 1 ED MCC WORKSH MO, DOI [10.1145/2342509.2342513, DOI 10.1145/2342509.2342513]
  • [4] Resource Sharing of a Computing Access Point for Multi-User Mobile Cloud Offloading with Delay Constraints
    Chen, Meng-Hsi
    Dong, Min
    Liang, Ben
    [J]. IEEE TRANSACTIONS ON MOBILE COMPUTING, 2018, 17 (12) : 2868 - 2881
  • [5] Energy-Efficient Resource Allocation for Cache-Assisted Mobile Edge Computing
    Cui, Ying
    He, Wen
    Ni, Chun
    Guo, Chengjun
    Liu, Zhi
    [J]. 2017 IEEE 42ND CONFERENCE ON LOCAL COMPUTER NETWORKS (LCN), 2017, : 640 - 648
  • [6] Task Offloading and Scheduling in Fog RAN: A Parallel Communication and Computation Perspective
    Guo, Kun
    Sheng, Min
    Quek, Tony Q. S.
    Qiu, Zhiliang
    [J]. IEEE WIRELESS COMMUNICATIONS LETTERS, 2020, 9 (02) : 215 - 218
  • [7] Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968
  • [8] 5G Radio Access Network Design with the Fog Paradigm: Confluence of Communications and Computing
    Ku, Yu-Jen
    Lin, Dian-Yu
    Lee, Chia-Fu
    Hsieh, Ping-Jung
    Wei, Hung-Yu
    Chou, Chun-Ting
    Pang, Ai-Chun
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2017, 55 (04) : 46 - 52
  • [9] Peng MG, 2016, IEEE NETWORK, V30, P46, DOI 10.1109/MNET.2016.7513863
  • [10] Penner T, 2014, IEEE GLOB COMM CONF, P2801, DOI 10.1109/GLOCOM.2014.7037232