Reliability and Timeliness Analysis of Fault-tolerant Distributed Publish/Subscribe Systems

Distributed publish / subscribe paradigm is a powerful data dissemination paradigm that offers both scalability and flexibility for time-sensitive applications. However, its nature of high expressiveness makes it difficult to analyze or predict the performance of publish / subscribe systems such as event delivery probability and end-to-end delivery delay, especially when the publish / subscribe systems are deployed over distributed, large-scale networks. While several fault tolerance techniques to increase reliability in distributed publish / subscribe systems have been proposed, event delivery probability and timeliness of publish / subscribe systems with such reliability enhancement techniques have not yet been analyzed. This paper proposes a generic model that abstracts the basic distributed publish / subscribe protocol, along with several commonly used fault-tolerant techniques, on top of distributed, large-scale networks. The overall goal of this model is to predict quality of service (QoS) in terms of event delivery probability and timeliness based on statistical attributes of each component in the distributed publish / subscribe systems. The evaluation results via extensive simulations with parameters computed from real-world traces verifies the correctness of the proposed prediction model. The proposed prediction model can be used as a building block for automatic QoS control in distributed, time-sensitive publish / subscribe systems such as subscriber admission control, broker deployment, and reliability optimization.