Event Processing
Lecturer (assistant) |
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Number | 0000002032 |
Type | |
Duration | 4 SWS |
Term | Sommersemester 2020 |
Language of instruction | English |
Position within curricula | See TUMonline |
Dates | See TUMonline |
Dates
Admission information
Objectives
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
Description
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
Prerequisites
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
Examination
Periodic (laboratory) assignments (e.g., assignments or milestones towards project), final exam.