A Vehicular Task Offloading Method With Eliminating Redundant Tasks in 5G HetNets

被引:2
作者
Zhang, Rui [1 ,2 ]
Wu, Libing [1 ,2 ,3 ]
Cao, Shuqin [1 ]
Wu, Dan [4 ]
Li, Jianxin [5 ]
机构
[1] Wuhan Univ, Sch Comp Sci, Wuhan 430000, Peoples R China
[2] Guangdong Prov Lab Artificial Intelligence & Digit, Shenzhen 518107, Peoples R China
[3] Wuhan Univ, Sch Cyber Sci & Engn, Wuhan 430000, Peoples R China
[4] Univ Windsor, Sch Comp Sci, Windsor, ON N9B 3P4, Canada
[5] Deakin Univ, Sch Informat Technol, Melbourne, Vic 3217, Australia
来源
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT | 2023年 / 20卷 / 01期
基金
中国国家自然科学基金;
关键词
Task analysis; 5G mobile communication; Base stations; Servers; Games; Costs; Computational modeling; Vehicular task offloading; redundant tasks; 5G HetNets; game theory; task completion rate; EDGE; COOPERATION; INTERNET; TECHNOLOGIES; CHALLENGES; NETWORKS;
D O I
10.1109/TNSM.2022.3201953
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The combination of mobile edge computing and 5G heterogeneous networks (5G HetNets) provides new vehicular task offloading research solutions. Most existing task offloading studies assume that vehicle tasks are unique and there are no redundant tasks between vehicles. However, there is a duplication of tasks for vehicles within the same base station. That causes a waste of computing resources and increases task offloading costs. To address this problem, this paper proposes the task offloading algorithm TOERT to eliminate redundant tasks in 5G HetNets. The TOERT algorithm is designed to eliminate redundant tasks, improve vehicle task completion rates and reduce offloading costs. Specifically, we consider two cases of redundant tasks within the macro cell base station (MCBS). When the task results have been stored in the MCBS, vehicles directly agree on the transaction price with the MCBS to obtain the task results. The MCBS first eliminates redundant tasks between vehicles when task results are not stored. Then, the MCBS determines the appropriate small cell base station (SCBS) to participate in the partial offloading. Finally, the vehicles negotiate with the MCBS to obtain task results. Against the other five algorithms considered for comparison purposes, the TOERT algorithm effectively eliminates redundant tasks, improves the task completion rate and increases the benefits of both the vehicles and the MCBS.
引用
收藏
页码:456 / 470
页数:15
相关论文
共 47 条
  • [1] Abbas Y., MOBILE EDGE COMPUTIN
  • [2] Apostolopoulos G., 2021, IEEE T MOBILE COMPUT, DOI [10.1109/TMC.2021.3069911.[29]Y., DOI 10.1109/TMC.2021.3069911.[29]Y]
  • [3] Emerging technologies and research challenges for intelligent transportation systems: 5G, HetNets, and SDN
    Camacho F.
    Cárdenas C.
    Muñoz D.
    [J]. International Journal on Interactive Design and Manufacturing (IJIDeM), 2018, 12 (1): : 327 - 335
  • [4] Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing
    Chen, Xu
    Jiao, Lei
    Li, Wenzhong
    Fu, Xiaoming
    [J]. IEEE-ACM TRANSACTIONS ON NETWORKING, 2016, 24 (05) : 2827 - 2840
  • [5] 5MART: A 5G SMART Scheduling Framework for Optimizing QoS Through Reinforcement Learning
    Comsa, Ioan-Sorin
    Trestian, Ramona
    Muntean, Gabriel-Miro
    Ghinea, Gheorghita
    [J]. IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2020, 17 (02): : 1110 - 1124
  • [6] Malicious Code Detection under 5G HetNets Based on a Multi-Objective RBM Model
    Cui, Zhihua
    Zhao, Yaru
    Cao, Yang
    Cai, Xingjuan
    Zhang, Wensheng
    Chen, Jinjun
    [J]. IEEE NETWORK, 2021, 35 (02): : 82 - 87
  • [7] Dandala V., 2017, PROC INT C COMPUT CO, P1
  • [8] Guo H., 2018, 2018 IEEE International Conference on Communications ICC, P1
  • [9] Multi-Hop Cooperative Computation Offloading for Industrial IoT-Edge-Cloud Computing Environments
    Hong, Zicong
    Chen, Wuhui
    Huang, Huawei
    Guo, Song
    Zheng, Zibin
    [J]. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2019, 30 (12) : 2759 - 2774
  • [10] Reliable Computation Offloading for Edge-Computing-Enabled Software-Defined IoV
    Hou, Xiangwang
    Ren, Zhiyuan
    Wang, Jingjing
    Cheng, Wenchi
    Ren, Yong
    Chen, Kwang-Cheng
    Zhang, Hailin
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2020, 7 (08): : 7097 - 7111