Co-management of Power and Performance in Virtualized Distributed Environments.
ABSTRACT Rapid growth of large-scale applications and their widespread use in research and industry has led to dramatic increases in
energy consumption in enterprise data centers and large-scale distributed systems such as Grids. Any attempt at reducing the
energy consumption without concern for performance can be destructive and deteriorate the overall efficiency of data centers
and large-scale distributed systems running such applications. In this paper, we present an optimization model for resource
management in virtualized distributed systems to minimize power costs automatically while satisfying performance constraints.
The objective of our model is to keep the utilization of servers near to an optimum point to prevent performance degradation.
The model includes two objective functions, one for power costs and another for performance. Using the objective functions,
we present a scheduling algorithm to place a set of virtual machines on a set of servers dynamically so that to integrate
power management with performance management. We show experimentally that the proposed scheduler consumes approximately 24%
less energy than static power management techniques while maintaining comparable performance.
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ABSTRACT: The use of virtualization technology (VT) has become widespread in modern datacenters and Clouds in recent years. In spite of their many advantages, such as provisioning of isolated execution environments and migration, current implementations of VT do not provide effective performance isolation between virtual machines (VMs) running on a physical machine (PM) due to workload interference of VMs. Generally, this interference is due to contention on physical resources that impacts performance in different workload configurations. To investigate the impacts of this interference, we formalize the concept of interference for a consolidated multi-tenant virtual environment. This formulation, represented as a mathematical model, can be used by schedulers to estimate the interference of a consolidated virtual environment in terms of the processing and networking workloads of running VMs, and the number of consolidated VMs. Based on the proposed model, we present a novel batch scheduler that reduces the interference of running tenant VMs by pausing VMs that have a higher impact on proliferation of the interference. The scheduler achieves this by selecting a set of VMs that produce the least interference using a 0-1 knapsack problem solver. The selected VMs are allowed to run and other VMs are paused. Users are not troubled by the pausing and resumption of VMs for a short time because the scheduler has been designed for the execution of batch type applications such as scientific applications. Evaluation results on the makespan of VMs executed under the control of our scheduler have shown nearly 33% improvement in the best case and 7% improvement in the worst case compared to the case in which all VMs are running concurrently. In addition, the results show that our scheduling algorithm outperforms serial and random scheduling of VMs as well.Future Generation Computer Systems 10/2013; 29(8):2057-2066. · 2.64 Impact Factor