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Authors: Mianyu Wang, Nagarajan Kandasamy , Allon Guez , and Moshe Kam Proceedings of the 3 rd International Conference on Autonomic Computing, ICAC 2006, Dublin, Ireland Presenter: Ramya Pradhan , Fall 2012, UCF.

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  1. Authors: Mianyu Wang, NagarajanKandasamy, AllonGuez, and Moshe Kam Proceedings of the 3rd International Conference on Autonomic Computing, ICAC 2006, Dublin, Ireland Presenter: RamyaPradhan, Fall 2012, UCF. Adaptive performance control of computing systems via distributed cooperative control: application to power management in computing clusters

  2. Outline • Research problem • Proposed solution • Evaluation of proposed solution • Strengths • Limitations • Proposed extensions

  3. Research Problem Clients Server cluster Power Consumption How to balance power consumption with time-varying workload and QoS?

  4. Proposed solution • Fully decentralized and cooperative control framework using optimal control theory • balance cluster operating frequency and average response time • scalable due to problem decomposition • fault-tolerant due to cooperative control • no intra-cluster communication

  5. Proposed solution using optimal control • Optimal control • “uses predictive approach that generates sequence of control inputs over a specified lookahead horizon while estimating changes in operating conditions.” • System Model • System state: queue size • Constrained control input: operating frequency • Output: average response time

  6. Distributed control framework Global request buffer Server cluster Clients Dynamic Controllers

  7. Evaluation • System settings • e-commerce • Virtual store consisting of 10000 objects • response time uniformly chosen between (4,11) ms • request distribution • popularity • temporal locality • cluster of four servers

  8. Evaluation Adaptive power consumption

  9. Evaluation Adaptive power consumption during processors’ failure

  10. Strengths • Development of a communication-less framework for distributed optimization • Implementation of the framework of power consumption and guarantee QoS • Usage of distributed framework • autonomous controllers • no single point of failure • capable of self-* properties

  11. Limitations • Main concept: decomposing power management into optimal control problems for each server, based on the assumption that resource provisioning and allocation can also be decomposed into such problems; this may not always be possible. • Adding new servers adds to the overhead in predicting its behavior by all other servers. Results for adding servers is not presented.

  12. Possible extensions • Study the system under dynamic adding and removing of servers • Experiment with perturbations when servers are optimally performing • remove servers that almost always guanranteeQoS and see how other servers respond • add more servers to observe how estimating the other servers’ behavior affects guarantee of QoS

  13. Thank You!

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