Resource Allocation in Fog Computing based on Meta-Heuristic Approaches: A Systematic Review

被引:0
|
作者
Anu [1 ]
Singhrova, Anita [1 ]
机构
[1] Deenbandhu Chhotu Ram Univ Sci & Technol, Dept Comp Sci & Engn, Sonepat, Haryana, India
关键词
Fog Computing Meta-heuristic Bio-inspired Resource; Allocation QoS; CLOUD; ALGORITHMS; INTERNET;
D O I
10.22937/IJCSNS.2022.22.9.65
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Resource allocation in fog computing is a rigorous and challenging task and the allocation of appropriate resources to tasks generated by IoT users depends upon the QoS requirements of applications used by IoT users. Due to heterogeneity, mobility, uncertainty and limited availability of resources, the challenge of efficient resource allocation in fog computing cannot be addressed with traditional resource allocation strategies. Researchers are still facing problem in selecting an efficient resource allocation algorithm for wide variety of applications. This research study represents a systematic literature analysis of resource allocation in the fog computing. The current status of resource allocation in fog computing is distributed in several categories such as auction-based techniques, heuristics techniques and metaheuristic techniques etc. Methodological analysis of resource allocation techniques based on meta-heuristic approaches has been presented in this research paper. This research work will assist the researchers to find the important parameters of resource allocation algorithms and will also help in selecting appropriate resource allocation algorithm for tasks generated by IoT users.
引用
收藏
页码:503 / 514
页数:12
相关论文
共 50 条
  • [31] An efficient meta-heuristic algorithm for grid computing
    Pooranian, Zahra
    Shojafar, Mohammad
    Abawajy, Jemal H.
    Abraham, Ajith
    JOURNAL OF COMBINATORIAL OPTIMIZATION, 2015, 30 (03) : 413 - 434
  • [32] An efficient meta-heuristic algorithm for grid computing
    Zahra Pooranian
    Mohammad Shojafar
    Jemal H. Abawajy
    Ajith Abraham
    Journal of Combinatorial Optimization, 2015, 30 : 413 - 434
  • [33] Overview of Parallel Computing for Meta-Heuristic Algorithms
    Sun, Ying
    Chu, Shu-Chuan
    Hu, Pei
    Watada, Junzo
    Si, Mingchao
    Pan, Jeng-Shyang
    Journal of Network Intelligence, 2022, 7 (03): : 656 - 681
  • [34] Blockchain-Based Resource Allocation Model in Fog Computing
    Wang, Haoyu
    Wang, Lina
    Zhou, Zhichao
    Tao, Xueqiang
    Pau, Giovanni
    Arena, Fabio
    APPLIED SCIENCES-BASEL, 2019, 9 (24):
  • [35] Resource provisioning in edge/fog computing: A Comprehensive and Systematic Review
    Shakarami, Ali
    Shakarami, Hamid
    Ghobaei-Arani, Mostafa
    Nikougoftar, Elaheh
    Faraji-Mehmandar, Mohammad
    JOURNAL OF SYSTEMS ARCHITECTURE, 2022, 122
  • [36] Meta-heuristic based reliable and green workflow scheduling in cloud computing
    Rehani N.
    Garg R.
    International Journal of System Assurance Engineering and Management, 2018, 9 (4) : 811 - 820
  • [37] Resource Constrained Project Scheduling with Material Ordering: Two Hybridized Meta-Heuristic Approaches
    Zoraghi, N.
    Najafi, A. A.
    Niaki, S. T. A.
    INTERNATIONAL JOURNAL OF ENGINEERING, 2015, 28 (06): : 896 - 902
  • [38] Meta-heuristic algorithms for resource Management in Crisis Based on OWA approach
    Abdolreza Asadi Ghanbari
    Hossein Alaei
    Applied Intelligence, 2021, 51 : 646 - 657
  • [39] Meta-heuristic algorithms for resource Management in Crisis Based on OWA approach
    Ghanbari, Abdolreza Asadi
    Alaei, Hossein
    APPLIED INTELLIGENCE, 2021, 51 (02) : 646 - 657
  • [40] A Hybrid Meta-heuristic Method for Optimal Allocation of UPFCs
    Mori, Hiroyuki
    Maeda, Yukihiro
    ISCAS: 2009 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1-5, 2009, : 1705 - +