Language Expressiveness and Quality of Service for Publish/Subscribe Systems

The publish/subscribe paradigm is known for its loosely cou-pled interactions and event filtering capabilities. Traditional applications using pub/sub systems require large-scale de-ployment and high event throughput. Thus, pub/sub has al-ways put the emphasis on scalability and performance, to the detriment of filtering expressiveness and quality of service. The matching language is usually limited to topic-based or content-based event filtering and does not allow complex stream-based subscriptions to be expressed. Messages are delivered on a best-effort basis without any ordering or re-liability guarantees. Installing additional services and event processing systems at the endpoints can overcome the limi-tations of pub/sub systems. However, we argue that such so-lutions are inefficient and put a lot of strain on the pub/sub layer itself. Therefore, the focus of this thesis is to develop integrated solutions to extend pub/sub language expression and quality of service, and demonstrate that our approach results in better performance from a holistic perspective. We first describe multiple case studies for pub/sub and identify major features which need to be supported. We then extract those requirements from our use cases and develop general solutions within the pub/sub layer. Features we have sup-ported so far includes total order and ranked data dissem-ination. Finally, we conduct experiments to compare the performance of our approach to baselines which rely on end-to-end services and perform holistic evaluations to assess the impact of our work