Utility functions in autonomic systems

TLDR

Utility functions provide a natural and advantageous framework for achieving self‑optimization in distributed autonomic computing systems. The authors present a distributed architecture that demonstrates how utility functions enable autonomic elements to continually optimize computational resources in a dynamic, heterogeneous environment. The architecture comprises a two‑level structure of independent autonomic elements that manage application resource usage via local utility functions, while a global arbiter allocates resources among application environments based on resource‑level utility functions. Empirical data show that the utility‑function scheme effectively handles realistic, fluctuating Web‑based transactional workloads on a Linux cluster.

Abstract

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.