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    Optimized online scheduling algorithms

    Access Status
    Fulltext not available
    Authors
    Tan, R.
    Leong, J.
    Sidhu, Amandeep
    Date
    2018
    Type
    Book Chapter
    
    Metadata
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    Citation
    Tan, R. and Leong, J. and Sidhu, A. 2018. Optimized online scheduling algorithms. In Studies in Computational Intelligence, 65-81.
    Source Title
    Studies in Computational Intelligence
    DOI
    10.1007/978-3-319-73214-5_5
    School
    Curtin Malaysia
    URI
    http://hdl.handle.net/20.500.11937/68808
    Collection
    • Curtin Research Publications
    Abstract

    © Springer International Publishing AG 2018. However, all algorithms mentioned in Chap. 2 are considered as concurrent processing but not parallel processing and all are suitable to handle non-data intensive applications in cloud environment as all are considered as complex algorithm which consumes relatively high amount of memory, bandwidth and computational power to maintain its data structure. The outcome of maintaining these data structures will cause the time of scheduling tasks unbounded and make loss in profit gains. Undeniably, profit gain by IaaS provider is inversely proportional to time consumed to finish a task. To encounter most of the aspects and issues which are mentioned in Chap. 3, this project propose an online scheduling algorithm is to overcome the various excessive overheads during process while maintaining service performance and comparable least time consuming approach for data intensive task to adapt in the future cloud system.

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