A user-focused evaluation of web prefetching algorithms

Abstract

Web prefetching mechanisms have been proposed to benefit web users by hiding the download latencies. Nevertheless, to the knowledge of the authors, there is no attempt to compare different prefetching techniques that consider the latency perceived by the user as the key metric. The lack of performance comparison studies from the user’s perspective has been mainly due to the difficulty to accurately reproduce the large amount of factors that take part in the prefetching process, ranging from the environment conditions to the workload. This paper is aimed at reducing this gap by using a cost-benefit analysis methodology to fairly compare prefetching algorithms from the user’s point of view. This methodology has been used to configure and compare five of the most used algorithms in the literature under current and old workloads. In this paper, we analyze the perceived latency versus the traffic increase (both in bytes and in objects) to evaluate the benefits from the user’s perspective. In addition, we also analyze the performance results from the prediction point of view to provide insights on the observed performance. Results show that higher algorithm complexity does not improve performance, object-based algorithms outperform those based on pages, and performance among object-based algorithms present minor differences in the object traffic increase.