Abstract
In grid network and heterogeneous computing systems, the scheduling algorithms are important for obtaining high performance through transferring the data. In this paper, we present a new scheduling algorithm for a bounded number of fully connected graph based on Improve Max-Min, Min-Min and MiM-MaM scheduling task, (I-MMST) to optimize a new task scheduling algorithm for a specific data over cloud computing. Also, we offer significant makespan improvements by introducing a look-ahead feature without increasing the time complexity associated with computation cost by using the principle of components analysis algorithm (PCA). The analysis and experiments based on randomly generated graphs with various characteristics, show that our scheduling algorithm significantly surpass previous approaches in term of makespan, speedup, and efficiency.
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Al-Maytami, B.A., Fan, P., Hussain, A. (2018). I-MMST: A New Task Scheduling Algorithm in Cloud Computing. In: Huang, DS., Jo, KH., Zhang, XL. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science(), vol 10955. Springer, Cham. https://doi.org/10.1007/978-3-319-95933-7_69
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DOI: https://doi.org/10.1007/978-3-319-95933-7_69
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