An Intelligent Technique for Controlling Web Prefetching Costs at the Server Side

Abstract

Prefetching is an interesting technique for improving web performance by reducing the user-perceived latency when surfing the web. Nevertheless, due to its speculative nature, prefetching can increase the network traffic and the server load. This could negatively affect the overall system performance and decrease the quality of service. To minimize and maintain under control these adverse effects, in this paper we propose an intelligent prefetching mechanism that dynamically adjusts the aggressiveness of the prefetching algorithm at the server side. To this end, we also propose a traffic estimation model that permits to accurately calculate, in the server side, the extra load and traffic generated by the prefetching. The performance evaluation study shows that our proposal effectively regulates the adverse effects of web prefetching without affecting its benefits.

Neural Network Based Prefetching Control Mechanism

“…J. Domenech et al [2] proposed an intelligent prefetching mechanism which dynamically adjusted the aggressiveness of prefetching at server side. Authors calculated the extra traffic generated by prefetching based on the type of requests known by the server i.e.…”

“…Ping [1] is an ICMP echo message used to show the Round-Trip Time (RTT) with some additional information such as max/min/avg RTT, number of packets sent and received and packet drops. Round Trip Time [2] is the time measured in milliseconds required to get response corresponding to a request RTT is typically measured using a ping. Ping RTT has been employed here because:…”

“…Every activation function takes a single number and performs mathematical operation on it as presented by J. Márquez et al [2]. Following are major activation functions used in literature:…”