PARALLEL PRECEDENCE CONSOLIDATION FOR SIMILAR WORKLOAD IN CLOUD
Abstract
Cloud computing allows business customers to scale up and down their resource usage based on
needs. Many of the routed 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 multi-dimensional 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 Green Computing techniques that prevent overload in the
system effectively while saving energy used. Trace driven simulation and experiment results
demonstrate that our algorithm achieves good performance by Resource Management.
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