An optimization framework for web farm configuration.

ABSTRACTA common problem that sales consultants face in the field is the selection of an appropriate hardware and software configuration for web farms. Over-provisioning means that the tender will be expensive while under-provisioning will lead to a configuration that does not meet the customer criteria. Indy is a performance modeling environment which allows developers to create custom modeling applications. We have constructed an Indy-based application for defining web farm workloads and topologies. The paper presents an optimization framework that allows the consultant to easily find configurations that meet customers' criteria. The system searches the solution space creating possible configurations, using the web farm models to predict their performance. The optimization tool is then employed to select an optimal configuration. Rather than using a fixed algorithm, the framework provides an infrastructure for implementing multiple optimization algorithms. In this way, the appropriate algorithm can be selected to match the requirements of different types of problem. The framework incorporates a number of novel techniques, including caching results between problem runs, an XML based configuration language, and an effective method of comparing configurations. We have applied the system to a typical web farm configuration problem and results have been obtained for three standard optimization algorithms.