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: RC23451 in 2004
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