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Achieving Energy Proportionality In Server Clusters
Xinying Zheng, Yu Cai
Pages - 21 - 35     |    Revised - 30-10-2009     |    Published - 30-11-2009
Volume - 1   Issue - 1    |    Publication Date - November 2009  Table of Contents
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KEYWORDS
Green computing, energy proportional, server cluster
ABSTRACT
a great amount of interests in the past few years. Energy proportionality is a principal to ensure that energy consumption is proportional to the system workload. Energy proportional design can effectively improve energy efficiency of computing systems. In this paper, an energy proportional model is proposed based on queuing theory and service differentiation in server clusters, which can provide controllable and predictable quantitative control over power consumption with theoretically guaranteed service performance. Futher study for the transition overhead is carried out corresponding strategy is proposed to compensate the performance degradation caused by transition overhead. The model is evaluated via extensive simulations and is justified by the real workload data trace. The results show that our model can achieve satisfied service performance while still preserving energy efficiency in the system.
CITED BY (13)  
1 Bai, W. H., Xi, J. Q., Zhu, J. X., & Huang, S. W. (2015). Performance Analysis of Heterogeneous Data Centers in Cloud Computing Using a Complex Queuing Model. Mathematical Problems in Engineering, 2015.
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7 Li, K. (2012). Optimal configuration of a multicore server processor for managing the power and performance tradeoff. The Journal of Supercomputing, 61(1), 189-214.
8 Li, K. (2012). Optimal power allocation among multiple heterogeneous servers in a data center. Sustainable Computing: Informatics and Systems, 2(1), 13-22.
9 Zheng, X., & Cai, Y. (2012). Optimal server allocation and frequency modulation on multi-core based server clusters. International and Interdisciplinary Studies in Green Computing, 289.
10 Zheng, X. (2012). Managing server energy and reducing operational cost for online service providers.
11 Zheng, X., & Cai, Y. (2011). Energy-aware load dispatching in geographically located internet data centers. Sustainable Computing: Informatics and Systems, 1(4), 275-285.
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Miss Xinying Zheng
Michigan Technological University - United States of America
zxying@mtu.edu
Associate Professor Yu Cai
- United States of America