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Virtual machines offer unique advantages to the scientific computing community, such as Quality of Service (QoS) guarantee, performance isolation, easy resource management, and the on-demand deployment of computing environments. Using virtual machines as a computing resource within a distributed environment, such as Service Oriented Architecture (SOA), creates a variety of new issues and challenges that must be overcome. Traditionally, parallel task scheduling algorithms only focus on handling CPU resources. Using of a virtual machine, however, requires the monitoring and management of additional resource properties.
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