Computing Offloading Decision Based on Adaptive Estimation of Distribution Algorithm in Internet of Vehicles

被引：0
|
作者：
Yu F. [1 ]
Chen M. [1 ]
Yu B. [2 ]
机构：
[1] Shanwei Polytechnic, China
[2] Shenzhen Institute of Information Technology, China
来源：
International Journal of Cognitive Informatics and Natural Intelligence | 2022年 / 16卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Adaptive Estimation of Distribution Algorithm; Computing Offloading; Internet of Vehicle;
D O I：
10.4018/IJCINI.312250
中图分类号：
学科分类号：
摘要：
Aimed to improve the efficiency of computing offloading in internet of vehicles (IoV), a collaborative multi-task computing offloading decision mechanism with adaptive estimation of distribution algorithm for MEC-IoV was proposed in this paper. The algorithm considered the energy and time consumption as well as priority among different tasks. It presented a local search strategy and an adaptive learning rate according to the characteristics of the problem to improve the estimation of distribution algorithm. Experimental results show that compared with other offloading strategies, the proposed offloading strategy has obvious effects on the total cost optimization; the solutions quality of AEDA is 86.6% of PSO and 67.3% of GA. © 2022 IGI Global. All rights reserved.
引用
收藏
相关论文
共 50 条
  • [21] Task offloading method of edge computing in internet of vehicles based on deep reinforcement learning
    Degan Zhang
    Lixiang Cao
    Haoli Zhu
    Ting Zhang
    Jinyu Du
    Kaiwen Jiang
    Cluster Computing, 2022, 25 : 1175 - 1187
  • [22] An efficient task offloading strategy based on Aquila Student Psychology Optimization Algorithm in internet of vehicles-fog computing systems
    Lohat, Savita
    Jain, Sheilza
    Kumar, Rajender
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2024, 37 (04)
  • [23] Research on Cloud-Edge-End Collaborative Computing Offloading Strategy in the Internet of Vehicles Based on the M-TSA Algorithm
    Xu, Qiliang
    Zhang, Guo
    Wang, Jianping
    SENSORS, 2023, 23 (10)
  • [24] QoS-SLA-aware adaptive genetic algorithm for multi-request offloading in integrated edge-cloud computing in Internet of vehicles
    Materwala, Huned
    Ismail, Leila
    Hassanein, Hossam S.
    VEHICULAR COMMUNICATIONS, 2023, 43
  • [25] MOBILE EDGE COMPUTING FOR THE INTERNET OF VEHICLES Offloading Framework and Job Scheduling
    Feng, Jingyun
    Liu, Zhi
    Wu, Celimuge
    Ji, Yusheng
    IEEE VEHICULAR TECHNOLOGY MAGAZINE, 2019, 14 (01): : 28 - 36
  • [26] Computation Offloading in Edge Computing for Internet of Vehicles via Game Theory
    Liu, Jianhua
    Wei, Jincheng
    Luo, Rongxin
    Yuan, Guilin
    Liu, Jiajia
    Tu, Xiaoguang
    CMC-COMPUTERS MATERIALS & CONTINUA, 2024, 81 (01): : 1337 - 1361
  • [27] An Offloading Algorithm based on Markov Decision Process in Mobile Edge Computing System
    Yao B.
    Wu B.
    Wu S.
    Ji Y.
    Chen D.
    Liu L.
    International Journal of Circuits, Systems and Signal Processing, 2022, 16 : 115 - 121
  • [28] Deep reinforcement learning based offloading decision algorithm for vehicular edge computing
    Hu, Xi
    Huang, Yang
    PEERJ COMPUTER SCIENCE, 2022, 8
  • [29] Deep reinforcement learning based offloading decision algorithm for vehicular edge computing
    Hu, Xi
    Huang, Yang
    PEERJ, 2022, 10
  • [30] Deep reinforcement learning based offloading decision algorithm for vehicular edge computing
    Hu X.
    Huang Y.
    PeerJ Computer Science, 2022, 8
12345