|Language of instruction||English|
|Position within curricula||See TUMonline|
Understand requirements of event processing applications Understand characteristics of event processing paradigms Apply event processing formalisms, patterns and languages to use cases Analyze capabilities of emerging standards and products on event processing
Introduction Event processing applications What EP support is required? Characteristics and requirements Event processing terminology Theories of events & philosophical perspectives Event processing patterns Event generation Event detection Event filtering Event correlation Event processing formalisms & modelling event-based systems Event calculus Event algebra Petrie nets Event processing paradigms & models Event stream processing Event processing languages Publish/Subscribe Tuple spaces Rule-based event processing Trigger processing Continuous query processing Other approaches Event processing engines & algorithms For above paradigms: System model Language & data model ESP algorithems Programming with ESP System & architecture considerations Prototypes & systems Algorithms ESP - Different ESP window semantics P/S - Matching, filtering & correlation Rule & P/S - Rete Intelligent event processing Misceleneous topics Event processing networks Event-driven architecture Staged event-driven architecture Distributed event-based systems Distributed stream processing Event-based & event-driven programming Emerging standards & products as case studies
Programming in Java and C, basic data structures and algorithms, operating systems concepts, computer networks basics, data management background
Teaching and learning methods
Lectures, labs, assignments, use cases
Periodic (laboratory) assignments (e.g., assignments or milestones towards project), final exam.