Conference proceeding
Adaptive performance control of computing systems via distributed cooperative control: Application to power management in computing clusters
3RD INTERNATIONAL CONFERENCE ON AUTONOMIC COMPUTING, PROCEEDINGS
01 Jan 2005
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Advanced control and optimization techniques offer a theoretically sound basis to enable self-managing behavior in distributed computing models such as utility computing. To tractably solve the performance management problems of interest, including resource allocation and provisioning in such distributed computing environments, we develop a fully decentralized control framework wherein the optimization problem for the system is first decomposed into sub-problems, and each sub-problem is solved separately by individual controllers to achieve the overall performance objectives. Concepts from optimal control theory are used to implement individual controllers. The proposed framework is highly scalable, naturally tolerates controller failures, and allows for the dynamic addition/removal of controllers during system operation. As a case study, we apply the control framework to minimize the power consumed by a computing cluster subject to a dynamic workload while satisfying the specified quality-of-service goals. Simulations using real-world workload traces show that the proposed technique has very low control overhead, and adapts quickly to both workload variations and controller failures.
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Details
- Title
- Adaptive performance control of computing systems via distributed cooperative control: Application to power management in computing clusters
- Creators
- Mianyu WangNagarajan KandasamyAllon GuezMoshe KamIEEE
- Publication Details
- 3RD INTERNATIONAL CONFERENCE ON AUTONOMIC COMPUTING, PROCEEDINGS
- Conference
- 3RD INTERNATIONAL CONFERENCE ON AUTONOMIC COMPUTING, 3rd
- Publisher
- IEEE
- Number of pages
- 10
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Identifiers
- 991019170601004721
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