Glowworm swarm optimisation based task scheduling for cloud computing

Dabiah Ahmed Alboaneen, Huaglory Tianfield, Yan Zhang

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    Abstract

    Task scheduling is a non-deterministic polynomial-time hard (NP-hard) optimisation problem, thus applying metaheuristics is important. In this paper, we employ glowworm swarm optimisation (GSO) to solve the task scheduling problem in cloud computing to minimise the total execution cost of tasks while keeping the total completion time within the deadline. Simulation results show that GSO based task scheduling (GSOTS) algorithm outperforms shortest task first (STF), largest task first (LTF) and particle swarm optimisation (PSO) algorithms in reducing the total completion time and the cost of executing tasks.
    Original languageEnglish
    Title of host publicationProceedings of the 2nd International Conference on Internet of things and Cloud Computing
    PublisherACM
    Number of pages7
    ISBN (Print)9781450347747
    DOIs
    Publication statusPublished - 22 Mar 2017

    Keywords

    • cloud computing
    • resource management
    • glowworm swarm optimisation (GSO)
    • task scheduling

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  • Cite this

    Alboaneen, D. A., Tianfield, H., & Zhang, Y. (2017). Glowworm swarm optimisation based task scheduling for cloud computing. In Proceedings of the 2nd International Conference on Internet of things and Cloud Computing [152] ACM. https://doi.org/10.1145/3018896.3036395