Evaluation of an Evolutionary Algorithm to Dynamically Alter Partition Sizes in Web Caching Systems

There has been an explosion in the volume of data that is being accessed from the Internet. As a result, the risk of a Web server being inundated with requests is ever-present. One approach to reducing the performance degradation that potentially comes from Web server overloading is to employ Web caching where data content is replicated in multiple locations. In this paper, we investigate the use of evolutionary algorithms to dynamically alter partition size in Web caches. We use established modeling techniques to compare the performance of our evolutionary algorithm to that found in statically-partitioned systems. Our results indicate that utilizing an evolutionary algorithm to dynamically alter partition sizes can lead to performance improvements especially in environments where the relative size of large to small pages is high.