CAREER: Decentralized Control and Optimization Techniques for Autonomic Performance Management of Distributed Computing Systems

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CAREER: Decentralized Control and Optimization Techniques for Autonomic Performance Management of Distributed Computing SystemsPI: Nagarajan Kandasamy, Drexel University, Philadelphia, PA 19104SummaryTo operate distributed computing systems effectively in an uncertain and dynamic environment, multiple performance-related parameters such as resource provisioning to applications, relative priority between applications, and application operational modes, must be dynamically tuned to match time-varying application requirements and operating conditions. To cope with their growing scale and complexity, these systems must become autonomic, i.e., capable of managing themselves given high-level objectives from administrators. This project aims to develop the theory and practice of designing autonomic computing systems. The specific research objectives are to: (1) Develop a decentralized framework, using concepts from model-predictive and optimal control, to manage large-scale computing systems; (2) Analyze the performance of the control algorithms in terms of stability and robustness properties; and (3) Validate the control techniques using trace-based simulations and actual implementations on a Blade-server cluster. The expected outcome of this project is a set of technologies to convert a significant number of system management tasks into systematic processes using proven control-theoretic techniques. This will reduce system operating costs while ensuring the smooth operation of applications supporting the business, science, and engineering communities. The obtained results will be disseminated to the research community via relevant journals and conferences, and software artifacts will be freely available via the project web site.The educational plan seeks to: (1) Tutor high-school students in the computer sciences as part of a community-based educational support project in Chester, Pennsylvania; (2) Enhance undergraduate course offerings at Drexel University; and (3) Create a new graduate course on autonomic computing.