A service selection method in mobile edge and cloud environment based on skyline and cuckoo optimisation algorithm

被引:0
|
作者
Yan, Xiukun [1 ]
Zhu, Ming [1 ]
Li, Jing [1 ]
Zhao, Jinling [1 ]
机构
[1] Shandong Univ Technol, Coll Comp Sci & Technol, Zibo, Peoples R China
基金
中国国家自然科学基金;
关键词
edge computing; cloud computing; service selection; skyline; cuckoo optimisation algorithm; COA;
D O I
10.1504/IJWGS.2022.126125
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Compared with traditional cloud computing, services provided by edge computing have several advantages such as high speed and low latency, which make edge services become the key technology of 5G. However, the number of edge servers, the computing capability of an edge server and the number of services deployed on an edge server are limited. Therefore, researchers propose to combine edge computing with cloud computing. How to select appropriate cloud and edge services with low response time and cost to meet complex needs of mobile users is a NP-hard problem. To solve the problem, in this paper, we propose a mobile service selection method in an edge and cloud computing environment based on the combination of skyline and cuckoo optimisation algorithm. Firstly, the skyline method is used to pre-process candidate services and filter out services with poor quality. Secondly, by modelling the mobility of user and the service composition pattern, the cuckoo optimisation algorithm is utilised to select proper edge and cloud services to fulfil user's requirements. To verify the effectiveness and efficiency of the proposed method, experiments are carried out and results indicate that the proposed method has better performance than the referred state-of-art methods.
引用
收藏
页码:453 / 478
页数:27
相关论文
共 50 条
  • [41] Forensics-as-a-Service for Mobile Cloud Environment
    Roy, Asmita
    Midya, Sadip
    Majumder, Koushik
    Phadikar, Santanu
    2018 FOURTH IEEE INTERNATIONAL CONFERENCE ON RESEARCH IN COMPUTATIONAL INTELLIGENCE AND COMMUNICATION NETWORKS (ICRCICN), 2018, : 6 - 11
  • [42] A Skyline-based Efficient Web Service Selection Method Supporting Frequent Requests
    Wang, Yue
    Song, You
    Liang, Mingyang
    2016 IEEE 20TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD), 2016, : 328 - 333
  • [44] Container-based task scheduling for edge computing in IoT-cloud environment using improved HBF optimisation algorithm
    Sobhanayak, Srichandan
    Jaiswal, Kavita
    Turuk, Ashok Kumar
    Sahoo, Bibhudatta
    Mohanta, Bhabendu Kumar
    Jena, Debasish
    INTERNATIONAL JOURNAL OF EMBEDDED SYSTEMS, 2020, 13 (01) : 85 - 100
  • [45] A Large Scale Transactional Service Selection Approach Based on Skyline and Ant Colony Optimization Algorithm
    Qi, Lin
    Yao, Wenbin
    Chang, Jingkun
    NOMS 2018 - 2018 IEEE/IFIP NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM, 2018,
  • [46] Action-Selection Method for Reinforcement Learning Based on Cuckoo Search Algorithm
    Abed-alguni, Bilal H.
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2018, 43 (12) : 6771 - 6785
  • [47] Action-Selection Method for Reinforcement Learning Based on Cuckoo Search Algorithm
    Bilal H. Abed-alguni
    Arabian Journal for Science and Engineering, 2018, 43 : 6771 - 6785
  • [48] Optimal mobile device selection for mobile cloud service providing
    Ao Zhou
    Shangguang Wang
    Jinglin Li
    Qibo Sun
    Fangchun Yang
    The Journal of Supercomputing, 2016, 72 : 3222 - 3235
  • [49] Efficient service selection approach for mobile devices in mobile cloud
    Chunlin Li
    Liu Yanpei
    Luo Youlong
    The Journal of Supercomputing, 2016, 72 : 2197 - 2220
  • [50] Efficient service selection approach for mobile devices in mobile cloud
    Li, Chunlin
    Liu Yanpei
    Luo Youlong
    JOURNAL OF SUPERCOMPUTING, 2016, 72 (06): : 2197 - 2220