Brief announcement: Distributed self-organizing event space partitioning for content-based publish/subscribe systems

Publish/subscribe systems have commonly been divided in two large families on the basis of their event-selection model [2]: topic-based and content-based systems. The former trade reduced subscription expressiveness with simpler implementations and higher performance. Conversely, the latter allow to accurately map published data in a complex event schema on top of which expressive subscriptions can be defined, but incur the cost of more complex implementations that delivers reduced performance on large distributed settings. System developers are thus faced with a choice about which kind of system is best suited to the target application. A common solution to this dilemma lies in the event space partitioning [4] technique: the event schema is partitioned in a number of subspaces that are then statically mapped to topics. The partitioning must be globally known and subscribers are expected to subscribe those topics where subspaces that have a non-empty intersection with their content-based subscriptions have been mapped. Undesired events (false positives) can be filtered out at the receiver side. The event space partitioning granularity strongly affects the performance of such systems: if it is excessively coarse-grained too much resources are wasted to deliver false positives, while if it is too fine-grained the number of topics that will be generated, and that must be managed by the topic based system, could easily become huge. Current solutions [3] provide sub-optimal approximations that are calculated offline and then statically applied to the system. © 2011 Springer-Verlag.