Abstract
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.
Highlights
Today’s Internet is a vast network of interconnected computing devices, through which information is shared at an extremely high volume and speed
We will examine the impact of the cache size (C), relative size of large to small pages (k), percentage of small pages (p), number of Web pages (M), and the relative performance benefits of a Web caching system that utilizes dynamically-controlled partition sizes against to a system that used statically-assigned partition sizes
We have investigated the use of an evolutionary algorithm to dynamically control partition size in a Web cache system
Summary
Today’s Internet is a vast network of interconnected computing devices, through which information is shared at an extremely high volume and speed. The amount of data transferred between computing devices has increased dramatically To put it into perspective, the modern Internet consists of an environment of video streaming, online television, massively multiplayer online games, and live music streaming. By storing copies of Web pages requested by clients, a Web cache can process future requests for those particular pages without involving the actual server. This is based on the assumption that those cached pages will be requested again at some point in the immediate to near future by other clients [7].
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