A Comprehensive Toolset for Workload Characterization, Performance Modeling and On-line Control

With the advances of computer hardware and software technologies, electronic businesses are
moving towards the on-demand era, where services and applications can be deployed or accommodated in a dynamic and autonomic fashion. This leads to a more flexible and efficient way to manage various system resources. For on-demand services and applications, performance modeling and analysis play key roles in many aspects of such an autonomic system. In this paper, we present a comprehensive toolset developed for workload characterization, performance modeling and analysis, and on-line control. The development of the toolset is based on state-of-the art techniques in statistical analysis, queueing theory, scheduling techniques, and on-line control methodologies. Built on a flexible software architecture, this toolset provides significant value for key business processes. This includes capacity planning, performance prediction, performance engineering and on-line control of system resources.

By: Li Zhang, Zhen Liu, Anton Riabov, Monty Schulman, Honghui Xia, Fan Zhang

Published in: Lecture Notes in Computer Science, volume 2794, (no ), pages 63-77 in 2003

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