Performance analysis of a client-side caching/prefetching system for Web traffic

Abstract

Network congestion remains one of the main barriers to the continuing success of the Internet. For Web users, congestion manifests itself in unacceptably long response times. One possible remedy to the latency problem is to use caching at the client, at the proxy server, or within the Internet. However, Web documents are becoming increasingly dynamic (i.e., have short lifetimes), which limits the potential benefit of caching. The performance of a Web caching system can be dramatically increased by integrating document prefetching (a.k.a. "proactive caching") into its design. Although prefetching reduces the response time of a requested document, it also increases the network load, as some documents will be unnecessarily prefetched (due to the imprecision in the prediction algorithm). In this study, we analyze the confluence of the two effects through a tractable mathematical model that enables us to establish the conditions under which prefetching reduces the average response time of a requested document. The model accommodates both passive client and proxy caching along with prefetching. Our analysis is used to dynamically compute the "optimal" number of documents to prefetch in the subsequent client's idle (think) period. In general, this optimal number is determined through a simple numerical procedure. Closed-form expressions for this optimal number are obtained for special yet important cases. We discuss how our analytical results can be used to optimally adapt the parameters of an actual prefetching system. Simulations are used to validate our analysis and study the interactions among various system parameters.

An immune inspired co-evolutionary affinity network for prefetching of distributed object

“…Web prefetching is built on Web caching to improve the page access time from Web servers [1,21]. The hierarchy of pages makes it possible by prefetching and caching to improve page access time.…”

Key factors in web latency savings in an experimental prefetching system

“…Finally, Balamash et al [10] proposed a mathematical model for a web prefetching architecture. Their results showed that prefetching was profitable even with the presence of a good caching system.…”

“…However, few studies [7][8][9][10] focus on the maximum performance achievable through web prefetching and the main constraints to reach it. Some of these works study the upper bounds in performance of web prefetching from a theoretical point of view but, to the best of our knowledge, none of them has empirically analyzed how real restrictions affect the benefits of prefetching.…”

On Wide Area Network Optimization

“…At the maximum, more than 95% of the user's perceived latency can be achieved with a collaborative client-server or proxy-server predictor. A detailed performance analysis on the client-side caching and prefetching system is presented in [42].…”

“…Both the prediction engine and prefetching engine can be located at the clients [47] to reduce the interaction between the prediction engine and prefetching engine. (ii) Server-initiated prefetching.…”