A survey of web caching schemes for the Internet <s> Between browser clients and Web servers <s> World-Wide Web (WWW) services have grown to levels where significant delays are expected to happen. Prefetching techniques are likely to help reduce waiting times. However pre-fetching is only effective if the right documents are identified and if user's move is correctly predicted. Therefore, it is productive to determine whether a revisit will occur or not, before starting pre-fetching. In this paper we develop two user models that help determine user's next move. One model uses random walk approximation and the other is based on digital signal processing techniques. We also give hints on how to use such models with a simple pre-fetching technique that we are developing. <s> BIB001 </s> A survey of web caching schemes for the Internet <s> Between browser clients and Web servers <s> Prefetching has been shown to be an effective technique for reducing user perceived latency in distributed systems. In this paper we show that even when prefetching adds no extra traffic to the network, it can have serious negative performance effects. Straightforward approaches to prefetching increase the burstiness of individual sources, leading to increased average queue sizes in network switches. However, we also show that applications can avoid the undesirable queueing effects of prefetching. In fact, we show that applications employing prefetching can significantly improve network performance, to a level much better than that obtained without any prefetching at all. This is because prefetching offers increased opportunities for traffic shaping that are not available in the absence of prefetching. Using a simple transport rate control mechanism, a prefetching application can modify its behavior from a distinctly ON/OFF entity to one whose data transfer rate changes less abruptly, while still delivering all data in advance of the user's actual requests. <s> BIB002
Early studies focus on the prefetching schemes between browser clients and Web servers. Padmanabhan and Mogul [63] analyze the latency reduction and network traffic of prefetching using Web server traces and trace-driven simulation. The prediction algorithm they used is based on the Prediction-by-Partial-Matching (PPM) data compressor with prefix depth of 1. The study shows that prefetching from Web servers to individual clients can reduce client latency by 45% at the expense of doubling the network traffic. Bestavros and Cunha  present a model for speculative dissemination of World Wide Web documents. The work shows that reference patterns observed at a Web server can be used as an effective source of information to drive prefetching, and reaches similar results as  . Cunha and Jaccouduse BIB001 a collection of Web client traces and study how effectively a user's future Web accesses can be predicted from his or her past Web accesses. They show that a number of models work well and can be used in prefetching. Crovella and Barford BIB002 analyzed the network effects of prefetching and shows that prefetching can reduce access latency at the cost of increasing network traffic and increasing network traffic burstiness (and thereby increasing network delays). They proposed a rate-controlled prefetching scheme to minimize the negative network effect by minimizing the transmission rate of prefetched doeuments. However, these early studies do not consider or model caching proxies and hence fail to answer the question about performance of prefetching completely.