Abstract
The existing resource scheduling algorithms for virtual machines usually use serial job deployment ways which easily lead to the job completion time overlong and the system load unbalance. To solve the problems, an Improved Potential Capacity (IPC) based resource scheduling algorithm for virtual machines is proposed, which comprehensively considers the overall job completion time and system load balancing, and applies a new metric to dynamically estimate the resource remaining capacities of virtual machines, and thus reduce the inexact matching between jobs and virtual machines. A batch job deployment method is also proposed to execute the batch job deployment. Many simulation experimental results show that the proposed algorithm can effectively decrease the overall job completion time and improve the load balancing of a cloud system.
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Acknowledgements
This research was supported by the National Natural Science Foundation of China (Nos. 61073063 and 61332006) and the Public Science and Technology Research Funds Projects of Ocean (No. 201105033).
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Qiao, B. et al. (2016). Improved PC Based Resource Scheduling Algorithm for Virtual Machines in Cloud Computing. In: Wang, Y., Yu, G., Zhang, Y., Han, Z., Wang, G. (eds) Big Data Computing and Communications. BigCom 2016. Lecture Notes in Computer Science(), vol 9784. Springer, Cham. https://doi.org/10.1007/978-3-319-42553-5_27
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DOI: https://doi.org/10.1007/978-3-319-42553-5_27
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