httperf—a tool for measuring web server performance
ACM SIGMETRICS Performance Evaluation Review
Energy-Efficient Real-Time Heterogeneous Server Clusters
RTAS '06 Proceedings of the 12th IEEE Real-Time and Embedded Technology and Applications Symposium
Rainbow: cost-effective software architecture-based self-adaptation
Rainbow: cost-effective software architecture-based self-adaptation
Tailoring configuration to user's tasks under uncertainty
Tailoring configuration to user's tasks under uncertainty
Energy-efficient server clusters
PACS'02 Proceedings of the 2nd international conference on Power-aware computer systems
Challenges in distributed energy adaptive computing
ACM SIGMETRICS Performance Evaluation Review
Introducing Scalileo: a Java based scaling framework
Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking
A dynamic optimization model for power and performance management of virtualized clusters
Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking
Server farms' power consumption minimized via best allocation of servers and ancillary equipments
AIKED'11 Proceedings of the 10th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Energy-aware service allocation
Future Generation Computer Systems
Enhancing data center sustainability through energy-adaptive computing
ACM Journal on Emerging Technologies in Computing Systems (JETC)
Stitch: A language for architecture-based self-adaptation
Journal of Systems and Software
Virtualized Web server cluster self-configuration to optimize resource and power use
Journal of Systems and Software
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This paper presents a framework to support dynamic adaptation of applications, which consists of a reusable infrastructure with standard elements to monitor and adapt running applications, and a contract-based adaptation language to enable one to express high-level adaptation policies. The proposed framework is used to introduce dynamic adaptation capabilities into a server cluster infrastructure, intended to address power and performance management concerns. By experimental evaluation, we demonstrate that our approach is useful and effective in providing the required support for describing and deploying typical power management contracts.