Using experience to guide Web server selection

We examine the use of the anycasting communication paradigm to improve client performance when accessing replicated multimedia objects. Anycasting supports dynamic selection of a server amongst a group of servers that provide equivalent content. It the selection is done well, the client will experience improved performance. A key issue in anycasting is the method used to maintain performance information used in server selection. We explore using past performance or experience to predict future performance. We conduct our work in the context of a customized web prefetching application called WebSnatcher. We examine a variety of algorithms for selecting a server using past performance and find that the overall average and weighted average algorithms are closest to optimal performance. In addition to the WebSnatcher application, this work has implications for responsible network behavior by other applications that generate network traffic automatically. By using the techniques we present here, such applications can reduce network and server load, potentially improving performance for interactive applications. The results can also be used to reach conclusions about the performance that would be obtained if anycasting were used in an interactive application.