cs 18: e4

Research Article

Task scheduling in cloud computing based on metaheuristic techniques: A review paper

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  • @ARTICLE{10.4108/eai.13-7-2018.162829,
        author={Rasha A. Al-Arasi and Anwar  Saif},
        title={Task scheduling in cloud computing based on metaheuristic techniques: A review paper},
        journal={EAI Endorsed Transactions on Cloud Systems: Online First},
        volume={},
        number={},
        publisher={EAI},
        journal_a={CS},
        year={2020},
        month={1},
        keywords={Cloud computing, Resource scheduling, Optimization criteria, Scheduling, Meta-heuristic techniques, Task scheduling},
        doi={10.4108/eai.13-7-2018.162829}
    }
    
  • Rasha A. Al-Arasi
    Anwar Saif
    Year: 2020
    Task scheduling in cloud computing based on metaheuristic techniques: A review paper
    CS
    EAI
    DOI: 10.4108/eai.13-7-2018.162829
Rasha A. Al-Arasi1,*, Anwar Saif2
  • 1: Sana‘a University, Department of Computer Science, Sana‘a, Yemen
  • 2: Sana‘a University, Department of Information Systems, Sana‘a, Yemen
*Contact email: rasha.ali66@gmail.com

Abstract

Cloud computing delivers computing resources like software and hardware as a service to the users through a network. Due to the scale of the modern datacentres and their dynamic resources provisioning nature, we need efficient scheduling techniques to manage these resources. The main objective of scheduling is to assign tasks to adequate resources in order to achieve one or more optimization criteria. Scheduling is a challenging issue in the cloud environment, therefore many researchers have attempted to explore an optimal solution for task scheduling in the cloud environment. They have shown that traditional scheduling is not efficient in solving this problem and produce an optimal solution with polynomial time in the cloud environment. However, they introduced sub-optimal solutions within a short period of time. Meta-heuristic techniques have provided near-optimal or optimal solutions within an acceptable time for such problems. In this work, we have introduced the major concepts of resource scheduling and provided a comparative analysis of many task scheduling techniques based on different optimization criteria.