Split and Subsume: Subscription Normalization for Effective Content-Based Messaging

Content-based publish/subscribe networks (CPSNs) scale to large numbers of publishers and subscribers by having brokers summarize subscriptions from subscribers and down-stream brokers based on coverage relationships ("subsumption") between subscriptions. A broker forwards the summary to brokers which are upstream on the routes to the publishers. Current summarization and event processing mechanisms induce heavy event processing load on brokers, leading to low event throughput and high latency and further sharp performance degradation under high rates of churn, i.e., addition, deletion, or modification of subscriptions. This paper describes Beretta, a novel CPSN that leverages a simple model of typed events, enabling a succinct and uniform normalized representation of subscriptions. This in turn supports highly effective subsumption and attribute-wise split filtering with matching complexity logarithmic in the number of subscriptions, and enables the systematic introduction of parameters into subscriptions to support both parametric and structural updates. We empirically demonstrate that our techniques significantly improve throughput and latency of event propagation and reduce response times to subscription updates.