Title: Utility Functions in Autonomic Systems
Speaker: William Walsh, IBM Watson Labs
Date: December 1, 2004 11:00 AM
Location: CoRE Bldg, CoRE 601, Rutgers University, Busch Campus, Piscataway, NJ
Utility functions provide a natural and advantageous framework for achieving self-optimization in distributed autonomic computing systems. We present a distributed architecture, implemented in a realistic prototype data center, that demonstrates how utility functions can enable a collection of autonomic elements to continually optimize the use of computational resources in a dynamic, heterogeneous environment. Broadly, the architecture is a two-level structure of independent autonomic elements that supports flexibility, modularity, and self-management. Individual autonomic elements manage application resource usage to optimize local service-level utility functions, and a global Arbiter allocates resources among application environments based on resource-level utility functions obtained from the managers of the applications. We present empirical data that demonstrate the effectiveness of our utility function scheme in handling realistic, fluctuating Web-based transactional workloads running on a Linux cluster. We are exploring a variety of technical challenges that arise in our utility-based framework. One challenge is predicting how application tuning and resource allocation affects service-level utility. Because of the difficulty of analytically modeling complex, distributed sytems, we are employing machine learning methods to automatically generate these mappings. Another challenge is the computational complexity of computing resource-level utility functions. We have developed a preference elicitation approach based on minimax regret criteria to reduce the computational burden.
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