Dynamic Channel Allocation Using Virtual Machines for Cloud Sensor Networking Environment

Abstract

Cloud computing allows business customers to scale up and down their resource usage based on needs.Many of the gains in the cloud model come from resource multiplexing through virtualization technology.In this work, 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 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.