Byzantine Fault Tolerant Event Stream Processing for Autonomic Computing

Event stream processing has been used to construct many mission-critical event-driven applications, such as business intelligence applications and collaborative intrusion detection applications. In this paper, we argue that event stream processing is also a good fit for autonomic computing and describe how to design such a system that is resilient to both hardware failures and malicious attacks. Based on a comprehensive threat analysis of event stream processing, we propose a set of lightweight mechanisms that help achieve Byzantine fault tolerant event processing for autonomic computing. The mechanisms consist of voting at the event consumers and an on-demand state synchronization mechanism triggered when an event consumer fails to collect a quorum of matching decision messages. We also introduce an evidence-based safe-guarding mechanism that prevents a faulty event consumer from inducing unnecessary rounds of state synchronization.