@inproceedings{39c16c675011426497d36f63db1c6b07,
title = "Improved PC based resource scheduling algorithm for virtual machines in cloud computing",
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.",
keywords = "Cloud computing, Resource scheduling, Virtual machine",
author = "Baiyou Qiao and Muchuan Shen and Junhai Zhu and Yujie Zheng and Xiaolong Li and Bin Tong and Donghai Chen and Guoren Wang",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 2nd International Conference on Big Data Computing and Communications, BigCom 2016 ; Conference date: 29-07-2016 Through 31-07-2016",
year = "2016",
doi = "10.1007/978-3-319-42553-5_27",
language = "English",
isbn = "9783319425528",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "321--331",
editor = "Yu Wang and Ge Yu and Guoren Wang and Yanyong Zhang and Zhu Han",
booktitle = "Big Data Computing and Communications - 2nd International Conference, BigCom 2016, Proceedings",
address = "Germany",
}