Cost-Benefit Analysis of Web Prefetching Algorithms from the User’s Point of View

Abstract

AbstractSince web prefetching techniques were proposed in the second half of the 90s as mechanisms to reduce final users’ perceived latency, few attempts to evaluate their performance have been done in the research literature. Even more, to the knowledge of the authors this is the first study that evaluates different proposals from the user’s point of view, i.e., considering the latency perceived by the user as the key metric. This gap between the proposals and their correct performance comparison is due to the difficulty to use a homogeneous framework and workload. This paper is aimed at reducing this gap by proposing a cost-benefit analysis methodology to fairly compare prefetching algorithms from the user’s point of view. The proposed methodology has been used to compare three of the most used algorithms in the bibliography, considering current workloads.KeywordsDependency GraphLink PredictionLatency ReductionCurrent WorkloadPrefetching AlgorithmThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.