Issue No. 06 - June (2013 vol. 24)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPDS.2012.283
Zhen Xiao , Peking University, Beijing
Weijia Song , Peking University, Beijing
Qi Chen , Peking University, Beijing
Cloud computing allows business customers to scale up and down their resource usage based on needs. Many of the touted gains in the cloud model come from resource multiplexing through virtualization technology. In this paper, we present a system that uses virtualization technology to allocate data center resources dynamically based on application demands and support green computing by optimizing the number of servers in use. We introduce the concept of "skewness” to measure the unevenness in the multidimensional resource utilization of a server. By minimizing skewness, we can combine different types of workloads nicely and improve the overall utilization of server resources. We develop a set of heuristics that prevent overload in the system effectively while saving energy used. Trace driven simulation and experiment results demonstrate that our algorithm achieves good performance.
Servers, Resource management, Prediction algorithms, Green products, Load modeling, Algorithm design and analysis, Computational modeling, green computing, Cloud computing, resource management, virtualization
W. Song, Z. Xiao and Q. Chen, "Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment," in IEEE Transactions on Parallel & Distributed Systems, vol. 24, no. , pp. 1107-1117, 2013.