Loosely coupled applications can take advantage of the publish/subscribe communication paradigm. In this latter, subscribers declare which events, or which range of events, they wish to monitor, and are asynchronously informed whenever a publishers throws an event. In such a system, when a publication occurs, all peers whose subscriptions contain the publication must be informed. In our approach, the subscriptions are represented by a DR-tree, which is an R-tree where each minimum bounding rectangle is supervised by a peer. Instead of attempting to statically optimize the DR-tree, we give an on-line algorithm, the work function algorithm, which continually changes the DR-tree in response to the sequence of publications, in attempt to dynamically optimize the structure. The competitiveness of this algorithm is computed to be at most 5 for any example where there are at most three subscriptions and the R-tree has height 2. The benefit of the on-line approach is that no prior knowledge of the distribution of publications in the attribute space is needed.
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