This document discusses event processing in ETALIS, an event processing system that can handle out-of-order event streams. It describes how background knowledge and semantic relations between events can be evaluated on-the-fly using stream reasoning. It also explains how ETALIS transforms inference rules to correctly process complex events even when events arrive out of order, and presents performance results showing the execution time for in-order versus out-of-order event processing.

1. Processing Out-Of-Order Event Streams
in ETALIS
Paul Fodor, Darko Anicic, Sebastian Rudolph, Roland Stühmer
4th ACM International Conference on Distributed Event-Based Systems (DEBS
2010), Cambridge, UK

2. Event Processing in ETALIS
What are semantic relations between EP with on-the-fly knowledge
events w.r.t background knowledge? evaluation and stream reasoning:
ψ=? • Classification and filtering
π ← φ ∨ ¬ ψ.
φ = true.
• Context
• Intelligent recommendation
• predictive analysis
Figure source: Tali Yatzkar & Opher Etzion, IBM Research

3. Out-of-Order Event Processing
 Hedge fund with independent cooperating agents: events arrive out-of-order.
ce1 ← stock(Agent1, “GO”, Pr1,Vol1) SEQ
stock(Agent2, “GO”, Pr2,Vol2) WHERE Pr1*1.20<Pr2.
ce2 ← stock(Agent1, “MS”, Pr1,Vol1) SEQ
stock(Agent2, “MS”, Pr2,Vol2) WHERE Pr1>1.20*Pr2.
 Missing complex events due to out-of-order stream: stock(agent1, “GO”,
100,10) SEQ stock(agent2, “GO”, 125,10);
 False positives complex event ce2 due to an out-of-order event.

4. Inference Rule Transformation

5. Performance Evaluation
Configuration: Pentium dual-core processor 2GHz CPU, 3GB running on
Ubuntu Linux. ETALIS was run using Yap Prolog version 5.1.31.
The execution time for in-order vs. out-of-order experiments

6. Thank you! Questions…
ETALIS
Open source:
http://code.google.com/p/etalis
See also our Live DEMO at:
http://krake26.perimeter.fzi.de:8080/etalis
Darko.Anicic@fzi.de