Consolidation of workloads has emerged as a key mechanism to dampen the rapidly growing energy expenditure within enterprise-scale data centers. To gainfully utilize consolidation-based techniques, we must be able to characterize the power consumption of groups of colocated applications. Such characterization is crucial for effective prediction and enforcement of appropriate limits on power consumption-power budgets-within the data center. We identify two kinds of power budgets: 1) an average budget to capture an upper bound on long-term energy consumption within that level and 2) a sustained budget to capture any restrictions on sustained draw of current above a certain threshold. Using a simple measurement infrastructure, we derive power profile-sstatistical descriptions of the power consumption of applications. Based on insights gained from detailed profiling of several applicationsboth individual and consolidated-we develop models for predicting average and sustained power consumption of consolidated applications. We conduct an experimental evaluation of our techniques on a Xen-based server that consolidates applications drawn from a diverse pool. For a variety of consolidation scenarios, we are able to predict average power consumption within five percent error margin and sustained power within 10 percent error margin. Using prediction techniques allows us to ensure safe yet efficient system operation-in a representative case, we are able to improve the number of applications consolidated on a server from two to three (compared to existing baseline techniques) by choosing the appropriate power state that satisfies the power budgets associated with the server.
|Number of pages||15|
|Journal||IEEE Transactions on Computers|
|Publication status||Published - 2010|
Bibliographical noteFunding Information:
degree in computer science from the Indian Institute of Technology, Madras, in 1989, and the MS and PhD degrees in computer science from Georgia Institute of Technology in 1991 and 1995, respectively. Since fall 1995, he has been on the faculty of The Pennsylvania State University, where he is currently a professor. His research interests are in computer architecture, operating systems, performance evaluation, and applications for both high-performance computer systems and embedded systems. His research has been funded by the US National Science Foundation (NSF) through several grants, including the CAREER Award, and from industries including IBM, Microsoft, and Unisys Corp. He has several publications in leading journals and conferences, has been on the editorial board of the IEEE Transactions on Parallel and Distributed Systems, and the IEEE Transactions on Computers. He is a recipient of the 2002, 2004, and 2005 IBM Faculty Awards. He is a senior member of the IEEE and ACM.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Hardware and Architecture
- Computational Theory and Mathematics