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Adaptive performance control of computing systems via distributed cooperative control: Application to power management in computing clusters
Please use this identifier to cite or link to this item:
http://hdl.handle.net/1860/1681
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| Title: | Adaptive performance control of computing systems via distributed cooperative control: Application to power management in computing clusters |
| Authors: | Wang, Mianyu
Kandasamy, Nagarajan
Guez, Allon
Kam, Moshe |
| Issue Date: | 2006 |
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
| Citation: | Proceedings of the 3rd International Conference on Autonomic Computing, ICAC 2006, pp. 165-174. |
| 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. |
| URI: | http://hdl.handle.net/1860/1681 |
| Appears in Collections: | Faculty Research and Publications (ECE)
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