IEEE Transactions on Software Engineering
Automated SLA Monitoring for Web Services
DSOM '02 Proceedings of the 13th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management: Management Technologies for E-Commerce and E-Business Applications
A model for web services discovery with QoS
ACM SIGecom Exchanges
Web services on demand: WSLA-driven automated management
IBM Systems Journal
A Framework and Ontology for Dynamic Web Services Selection
IEEE Internet Computing
Cremona: an architecture and library for creation and monitoring of WS-agreents
Proceedings of the 2nd international conference on Service oriented computing
A Power-Aware Run-Time System for High-Performance Computing
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Run-Time Monitoring of Instances and Classes of Web Service Compositions
ICWS '06 Proceedings of the IEEE International Conference on Web Services
Reliable QoS monitoring based on client feedback
Proceedings of the 16th international conference on World Wide Web
Lottery scheduling: flexible proportional-share resource management
OSDI '94 Proceedings of the 1st USENIX conference on Operating Systems Design and Implementation
CPU MISER: A Performance-Directed, Run-Time System for Power-Aware Clusters
ICPP '07 Proceedings of the 2007 International Conference on Parallel Processing
Harnessing Green IT: Principles and Practices
IT Professional
Supporting energy-driven adaptations in distributed environments
Proceedings of the 1st Workshop on Middleware and Architectures for Autonomic and Sustainable Computing
Balancing electricity bill and performance in server farms with setup costs
Future Generation Computer Systems
Power-aware virtual machine scheduling on clouds using active cooling control and DVFS
Proceedings of the 9th International Workshop on Middleware for Grids, Clouds and e-Science
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Green Computing is a recent trend towards designing, building, and operating computer systems to be energy efficient. While programs such as Energy Star have been around since the early 1990s, recent concerns regarding global climate change and the energy crisis have led to renewed interest in Green Computing. Data centers are a significant consumers of energy - both to power the computers as well as to provide the necessary cooling. This paper proposes a new approach to reduce energy utilization in data centers. In particular, our approach relies on consolidating services dynamically onto a subset of the available servers and temporarily shutting down servers in order to conserve energy. We present initial work on a probabilistic service dispatch algorithm that aims at minimizing the number of running servers such that they suffice for meeting the quality of service required by service-level agreements. Given the estimated energy consumption and projected growth in data centers, the proposed effort has the potential to positively impact energy consumption.