Subscription summaries for scalability and efficiency in publish/subscribe systems

A key issue when designing and implementing largescale publish/subscribe systems is how to efficiently propagate subscriptions among the brokers of the system. Brokers require this information in order to forward incoming events only to interested users, filtering out unrelated events, which can save significant overheads (particularly network bandwidth and processing time at the brokers). In this paper we contribute the notion of subscription summaries, a mechanism appropriately compacting subscription information. We develop the associated data structures and matching algorithms. The proposed mechanism can handle event/subscription schemata that are rich in terms of their attribute types and powerful in terms of the allowed operations on them. Our major results are that the proposed mechanism (i) is scalable, with the bandwidth required to propagate subscriptions increasing only slightly, even at huge-scales, and (ii) is significantly more efficient, up to orders of magnitude, depending on the scale, with respect to the bandwidth requirements for propagating subscriptions.