Evaluation of an Evolutionary Algorithm to Dynamically Alter Partition Sizes in Web Caching Systems
Evaluation of an Evolutionary Algorithm to Dynamically Alter Partition Sizes in Web Caching Systems作者机构：Department of Computer Science Trent University Peterborough ON Canada
出 版 物：《Journal of Software Engineering and Applications》 (软件工程与应用（英文）)
年 卷 期：2020年第13卷第9期
页 面：191-205页
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：Evolutionary Algorithm Web Cache Partition Simulation Performance Analysis Hit Rate
摘 要：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.
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