Link prefetching

Abstract: This paper provides a synopsis of a server-driven link prefetching mechanism that we have designed and implemented for the Mozilla web browser, a popular Open Source web browser. The mechanism depends on the origin server or an intermediate proxy server determining the best set of documents for the browser to prefetch. The browser follows prefetch directives provided by the server, either embedded in an HTML document using the 〈LINK〉 tag or specified via Link HTTP response headers. The browser determines when best to prefetch the specified URLs based on its own heuristics. In this paper, we describe the mechanism and discuss some of the practical issues that impacted its design and implementation.

Abstract: This paper provides a synopsis of a server-driven link prefetching mechanism that we have designed and implemented for the Mozilla web browser, a popular Open Source web browser. The mechanism depends on the origin server or an intermediate proxy server determining the best set of documents for the browser to prefetch. The browser follows prefetch directives provided by the server, either embedded in an HTML document using the 〈LINK〉 tag or specified via Link HTTP response headers. The browser determines when best to prefetch the specified URLs based on its own heuristics. In this paper, we describe the mechanism and discuss some of the practical issues that impacted its design and implementation.

Abstract: This paper provides a transparent and speculative algorithm for content based web page prefetching. The algorithm relies on a profile based on the Internet browsing habits of the user. It aims at reducing the perceived latency when the user requests a document by clicking on a hyperlink. The proposed user profile relies on the frequency of occurrence for selected elements forming the web pages visited by the user. These frequencies are employed in a mechanism for the prediction of the user's future actions. For the anticipation of an adjacent action, the anchored text around each of the outbound links is used and weights are assigned to these links. Some of the linked documents are then prefetched and stored in a local cache according to the assigned weights. The proposed algorithm was tested against three different prefetching algorithms and yield improved cache-hit rates given a moderate bandwidth overhead. Furthermore, the precision of accurately inferring the user's preference is evaluated through the recall-precision curves. Statistical evaluation testifies that the achieved recall-precision performance improvement is significant.

Abstract: The perceived latency for a user surfing the Internet is the target of a transparent and speculative algorithm that relies on a user behavior model. The model is based on past user behavior and in combination with a weighting scheme for the outbound links of a particular web page, aims at reducing the perceived latencies. The assistance is in the form of prefetching some linked web pages and storing them in the browser's cache. A comparison between the proposed algorithms against two other prefetching algorithms yield improved cache-hit rates given a moderate bandwidth overhead. Furthermore, the experimental results are proven to be statistically significant.