Harmonizing Model in Cloud Computing Environment
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We present a system that uses virtualization technology to assign data center resources dynamically based on request 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 store 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. This article introduces a better load balance model for the public cloud based on the cloud partition concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.