TY - GEN
T1 - Reducing data center power with server consolidation
T2 - 17th International Conference on High Performance Computing, HiPC 2010
AU - Subramanian, Chandrasekar
AU - Vasan, Arunchandar
AU - Sivasubramaniam, Anand
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - With the growing costs of powering data centers, power management is gaining importance. Server consolidation in data centers, enabled by virtualization technologies, is becoming a popular option for organizations to reduce costs and improve manageability. While consolidation offers these benefits, it is important to ensure proper resource provisioning so that performance is not compromised. In addition to reducing the number of servers, there are other knobs - such as frequency/voltage scaling - that are being offered by recent hardware for finer granularity of power control. In this paper, we look at exploiting server consolidation and frequency/voltage control to reduce power consumption, while meeting certain provisioning guarantees. We formulate the problem as a variant of variable-sized bin packing. We show that the problem is NP-hard, and present an approximation algorithm for the same. The algorithm takes O(n2 log n) time for n workloads, and has a provable approximation ratio. Experimental evaluation shows that in practice our algorithm obtains solutions very close (< 6.5% difference) to optimal.
AB - With the growing costs of powering data centers, power management is gaining importance. Server consolidation in data centers, enabled by virtualization technologies, is becoming a popular option for organizations to reduce costs and improve manageability. While consolidation offers these benefits, it is important to ensure proper resource provisioning so that performance is not compromised. In addition to reducing the number of servers, there are other knobs - such as frequency/voltage scaling - that are being offered by recent hardware for finer granularity of power control. In this paper, we look at exploiting server consolidation and frequency/voltage control to reduce power consumption, while meeting certain provisioning guarantees. We formulate the problem as a variant of variable-sized bin packing. We show that the problem is NP-hard, and present an approximation algorithm for the same. The algorithm takes O(n2 log n) time for n workloads, and has a provable approximation ratio. Experimental evaluation shows that in practice our algorithm obtains solutions very close (< 6.5% difference) to optimal.
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U2 - 10.1109/HIPC.2010.5713161
DO - 10.1109/HIPC.2010.5713161
M3 - Conference contribution
AN - SCOPUS:79952779649
SN - 9781424485185
T3 - 17th International Conference on High Performance Computing, HiPC 2010
BT - 17th International Conference on High Performance Computing, HiPC 2010
PB - IEEE Computer Society
Y2 - 19 December 2010 through 22 December 2010
ER -