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Virtualization can enhance the functionality and ease the management of
current and future Grids by enabling on-demand creation of services and
virtual clusters with customized environments, QoS provisioning and
policy-based resource allocation.
In this work, we consider the use of virtual machines (VMs) in a
data-center environment, where a significant portion of resources from a
shared pool are dedicated to Grid job processing. The goal is to improve
efficiency while supporting a variety of different workloads.
We analyze workload data for the past year from a Tier-2 Resource
Center at the RRC Kurchatov Institute (Moscow, Russia). Our
analysis reveals that a large fraction of Grid jobs have low CPU
utilization, which suggests that using virtual machines to isolate
execution of different Grid jobs on the shared hardware might be
beneficial for optimizing the data-center resource usage.
The introduction of VMs for Grid job execution enables policy-based
resource allocation and management in the data center: the
administrator can dynamically change the number of physical nodes
allocated for Grid jobs versus enterprise applications without
degrading performance support for Grid processing. Live migration of
VMs makes the management process even more flexible.
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