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Managing energy and server resources in hosting centers
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
The case for power management in web servers
Power aware computing
An analysis of Internet content delivery systems
ACM SIGOPS Operating Systems Review - OSDI '02: Proceedings of the 5th symposium on Operating systems design and implementation
SLA based profit optimization in autonomic computing systems
Proceedings of the 2nd international conference on Service oriented computing
Managing server energy and operational costs in hosting centers
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Ensemble-level Power Management for Dense Blade Servers
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Making scheduling "cool": temperature-aware workload placement in data centers
ATEC '05 Proceedings of the annual conference on USENIX Annual Technical Conference
Energy conservation policies for web servers
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Energy-aware server provisioning and load dispatching for connection-intensive internet services
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IEEE Transactions on Parallel and Distributed Systems
Weatherman: Automated, Online and Predictive Thermal Mapping and Management for Data Centers
ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
Measurement-based power profiling of data center equipment
CLUSTER '07 Proceedings of the 2007 IEEE International Conference on Cluster Computing
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Dynamic energy-aware capacity provisioning for cloud computing environments
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Behavioral model for cloud aware load and power management
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Inter cloud capable dynamic resource management with model of behavior
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With the increasing popularity of Internet-based information retrieval and cloud computing, saving energy in Internet data centers (a.k.a. hosting centers, server farms) is of increasing importance. Current research approaches are based on dynamically adjusting the active server set in order to turn off a portion of the servers and save energy without compromising the quality of service; the workload is then distributed, conventionally equally (i.e. balanced), across the active servers. Although there is ample work that demonstrates energy savings through dynamic server provisioning, there is little work on thermal-aware server provisioning. This paper provides a formulation of the thermal aware active server set provisioning (TASP), in a nonlinear minimax binary integer programming form, and a series of heuristic approaches to solving them, namely MiniMax, bb-sLRH, CP-sLRH and sLRH. Furthermore, it introduces thermal-aware workload distribution (TAWD) among the active servers. The proposed heuristics are evaluated using a thermal model of the ASU HPCI data center, while the request traffic is based on real web traces of the 1998 FIFA World Cup as well as the SPECweb2009 suite. The TASP heuristics are found to outperform a power-aware-only server set selection scheme (CPSP), by up to 9.3% for the simulated scenario. The order of achieved energy efficiency is: MiniMax (9.3% savings), CP-sLRH (9.2%), bb-sLRH (8.6%), sLRH (5.8%), compared to CPSP.