Practical high-throughput content-based routing using unicast state and probabilistic encodings

We address the problem that existing publish/subscribe messaging systems, including such commonly used ones as Apache’s ActiveMQ and IBM’s WebSphere MQ, exhibit degraded end-to-end throughput performance in a wide-area network setting. We contend that the cause of this problem is the lack of an appropriate routing protocol. Building on the idea of a content-based network, we introduce a protocol called B-DRP that can demonstrably improve the situation. A content-based network is a content-based publish/subscribe system architected as a datagram network: a message is forwarded hop-by-hop and delivered to any and all hosts that have expressed interest in the message content. This fits well with the character of a wide-area messaging system. B-DRP is based on two main techniques: a message delivery mechanism that utilizes and exploits unicast forwarding state, which can be easily maintained using standard protocols, and a probabilistic data structure to effciently represent and evaluate receiver interests. We present the design of B-DRP and the results of an experimental evaluation that demonstrates its support for improved throughput in a wide-area setting

Modelling Event-Based Interactions in Component-Based Architectures for Quantitative System Evaluation

This dissertation thesis presents an approach enabling the modelling and quality-of-service prediction of event-based systems at the architecture-level. Applying a two-step model refinement transformation, the approach integrates platform-specific performance influences of the underlying middleware while enabling the use of different existing analytical and simulation-based prediction techniques

Modelling Event-Based Interactions in Component-Based Architectures for Quantitative System Evaluation

This dissertation thesis presents an approach enabling the modelling and quality-of-service prediction of event-based systems at the architecture-level. Applying a two-step model refinement transformation, the approach integrates platform-specific performance influences of the underlying middleware while enabling the use of different existing analytical and simulation-based prediction techniques