Description
To address this issue, we propose to replicate content in units of clusters, each containing objects which are likely to be requested by clients that are topologically close. To this end, we describe three clustering techniques, and use various topologies and several real traces from large Web servers to evaluate their performance. Our results show that clusterbased replication achieves 40 - 60% improvement over full Web site replication. In addition, by adjusting the number of clusters, we can smoothly trade off the management and computation cost for better client performance.
To take into account of change in users' access patterns, we also explore incremental clusterings to adaptively add new documents to the content clusters. We examine both offline and online incremental clusterings, where the former assumes access history is available while the latter predicts access pattern based on the hyperlink structure. Our results show that the offline clusterings yield close to the performance of the complete re-clustering while at much lower overhead. The online incremental clustering and replication cut down the retrieval cost by 4.6 - 8 times compared to no replication and random replication, so it is especially useful to improve document availability during flash crowds.