Optimizing Pub/Sub Systems by Advertisement Pruning

Abstract

Supporting advertisements in large publish/subscribe services has an improving influence on the system scalability. The additional application of event routing optimizations based on subscriptions further increases the event throughput and decreases the memory usage of publish/subscribe systems. However, also advertisement-based optimizations can improve these system properties but have been widely neglected so far. In particular, no current optimizations are applicable to advertisements defined as arbitrary Boolean filter expressions. In this paper, we outline the final milestone on the way to practically support the arbitrary Boolean publish/subscribe model: We firstly develop a novel optimization approach, advertisement pruning, that is tailored to arbitrary Boolean advertisements. Secondly, we present a detailed evaluation of the optimization potential of this advertisement-based solution. We finally analyze the effects of additionally optimizing subscriptions on the advertisement pruning optimization.