Abstract
Task scheduling algorithm is the core of cloud computing. Due to the heterogeneity of hardware devices, most traditional scheduling algorithms are insufficient to handle the makespan and load balancing at the same time. To establish a scheduling algorithm adapted to the intelligent meter cloud testing platform, this paper proposes an algorithm based on sectional sorting and standard deviation. According to the characteristics of tasks and the performance of compute nodes, considering the idea of dynamic programming technology, the paper adjusts the expected execution time matrix-ETC with segmental method, and then calculates the standard deviation to optimize the algorithm. At last the experiment shows this algorithm outperforms traditional min-min algorithm in terms of makespan and load balancing.
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Zhao, B., Gao, X., Wang, P., Wang, R. (2019). Task Scheduling Algorithm Based on Sectional Sorting and Standard Deviation for Intelligent Meter Cloud Testing. In: Liang, Q., Mu, J., Jia, M., Wang, W., Feng, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, vol 463. Springer, Singapore. https://doi.org/10.1007/978-981-10-6571-2_264
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DOI: https://doi.org/10.1007/978-981-10-6571-2_264
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