The rapid growth of the WWW has inspired numerous techniques to reduce Web latency. While some of these techniques have not been implemented because they either increase network traffic or require cooperation between tiers, recent studies cast a shadow on techniques already in use (e.g. proxy caching) as a result of the increasingly dynamic aspects of the WWW. In particular, the proliferation of dynamically generated Web pages (i.e. cgi, ASP), which are either linked to a database, or extract information from cookies, reduces the effectiveness of caching techniques. Most techniques attempt to improve on part of the overall latency, and often neglect to address the internal latency, which can be a serious bottleneck in heterogeneous environments. We propose a client-side prefetching mechanism, where the decision of what to prefetch is left to the user. We found it has the potential of reducing latency by up to 81% in a homogeneous environment and 63% in a heterogeneous environment. In data taken on the client, the technique depicted the potential to decrease latency by three-fold. Client-side prefetching does not increase network traffic, it attempts to improve on all parts of latency, and it can be implemented on the client side, without the cooperation of any other tier. Moreover, it can work seamlessly with any other latency reduction technique. We advocate the inclusion of a suitable mechanism in future Web browsers to support client-side prefetching.

The importance of an accurate branch prediction mechanism has been well documented. Since the introduction of gshare and the observation that aliasing in the PHT is a major factor in reducing prediction accuracy, several schemes have been proposed to reduce aliasing in the PHT. All these schemes are aimed at maximizing the prediction accuracy with the fewest resources. In this paper we introduce Yet Another Global Scheme (YAGS)-a new scheme to reduce the aliasing in the PHT-that combines the strong points of several previous schemes. YAGS introduces tags into the PHT that allows it to be reduced without sacrificing key branch outcome information. The size reduction more than offsets the cost of the tags. Our experimental results show that YAGS gives better prediction accuracy for the SPEC95 benchmark suite than several leading prediction schemes, for the same cost. It also performs better than the other schemes in the presence of a context switch. Finally, YAGS displays good results for the go benchmark, which is of special interest since it has a large number of static branches and reflects situations where aliasing in the PHT can be a problem.