In search of invariants for e-business workloads
Proceedings of the 2nd ACM conference on Electronic commerce
Feedback Control of Computing Systems
Feedback Control of Computing Systems
Online Control for Self-Management in Computing Systems
RTAS '04 Proceedings of the 10th IEEE Real-Time and Embedded Technology and Applications Symposium
The dawning of the autonomic computing era
IBM Systems Journal
Hybrid Supervisory Utilization Control of Real-Time Systems
RTAS '05 Proceedings of the 11th IEEE Real Time on Embedded Technology and Applications Symposium
ICDCS '06 Proceedings of the 26th IEEE International Conference on Distributed Computing Systems
Energy-aware server provisioning and load dispatching for connection-intensive internet services
NSDI'08 Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation
Adaptive fair resource management with an arbiter for multi-tier computing systems
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
A distributed control framework for performance management of virtualized computing environments
Proceedings of the 7th international conference on Autonomic computing
Modelling of staged routing for reduced carbon footprints of large server clusters
International Journal of Communication Networks and Distributed Systems
A dynamic power management controller for optimizing servers' energy consumption in service centers
ICSOC'10 Proceedings of the 2010 international conference on Service-oriented computing
Self-organizing agent communities for autonomic resource management
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
| Hi-index | 0.00 |
The authors' distributed cooperative-control framework uses concepts from optimal control theory to adaptively manage theperformance ofcomputer clusters operating in dynamic and uncertain environments. Decomposing the overall performance-management probleminto smaller sub problems that individual controllers solve cooperatively allows for the scalable control of large computing systems. Theframework also adapts to controller failures and allows for the dynamic addition and removal of controllers during system operation. Thisarticle presents a case study showing how to manage the dynamic power consumed by a computer cluster processing a time varying Webworkload.