FZI Research Center for Information Technology, Germany

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1 FZI FORSCHUNGSZENTRUM INFORMATIK Event Processing and Stream Reasoning with ETALIS Darko Anicic FZI Research Center for Information Technology, Germany INQUEST 2012, Oxford, United Kingdom

2 Agenda Motivation and Introduction ETALIS Approach Implementation & Evaluation Applications Future Work Context Darko Anicic. Event Processing and Stream Reasoning with ETALIS, PhD Thesis, November 2011, KIT FZI Forschungszentrum Informatik 2

3 MOTIVATION AND INTRODUCTION FZI Forschungszentrum Informatik 3

4 Shifting Event Processing Toward More Intelligent Event Processing EP iep FZI Forschungszentrum Informatik 4

5 Shifting Reasoning Toward Stream Reasoning Reasoning Stream Reasoning FZI Forschungszentrum Informatik 5

6 Scenario: Setting Speed Limits on Roads How to capture & detect many possible situations? Define abstract, high-level situations, as patterns, and leave specific cases related to those situations to be inferred from the domain knowledge. A1-2 How to detect criticality of situations and their possible implications? A model which captures dependencies between situations and enable reasoning about implications. Collision - head-on (50) - side (60) - rear-end (50) - rollover (40) - pile-up (10) Weather - rain - tires lose traction - snow - with low visibility - ice, fog Road - A1 - A1-2 - A A2-3 - A FZI Forschungszentrum Informatik 6

7 Event Processing Enhanced with Domain Knowledge Situation t =10 min Temporal Knowledge Explicit & Implicit (Static) Knowledge Reasoning about sub-class relations as reasoning about more specific or more general situations Reasoning about transitive or indirect situations to detect relevant situations Sit_011 & Sit_01 Sit_10 Rd_1 Ar_1 Rd_1 Ar_ FZI Forschungszentrum Informatik 7

8 Event Processing & Stream Reasoning A Logic Programming Approach Background knowledge provides the context or domain in which events are interpreted. π =? π φ ψ. φ = true. Event Sources EP Detected Situations Pattern Definitions Figure source: Tali Yatzkar & Opher Etzion, IBM Research FZI Forschungszentrum Informatik 8

9 Event Processing and Stream Reasoning ETALIS APPROACH FZI Forschungszentrum Informatik 9

10 Overview of ETALIS Approach ETALIS Foundations ETALIS Language Execution Model EPN in ETALIS ETALIS Extensions Retraction in EP Out-of-Order EP EP-SPARQL Practical Considerations Implementation Evaluation ETALIS in Use FZI Forschungszentrum Informatik 10

11 ETALIS Language for Events - Syntax A predicate name with arity n, t(i) denotes terms t is a term of type boolean q is a nonnegative rational number BIN: SEQ, AND, PAR, OR, EQUALS, MEETS, STARTS, or FINISHES Event rule is defined as a formula of the following shape: where p is an event pattern containing all variables occurring in FZI Forschungszentrum Informatik 11

12 ETALIS: Interval-based Semantics FZI Forschungszentrum Informatik 12

13 ETALIS Language for Events - Semantics FZI Forschungszentrum Informatik 13

14 Example: Event Filtering FZI Forschungszentrum Informatik 14

15 Example: Sub-Class Relations FZI Forschungszentrum Informatik 15

16 Example: Iterative and Aggregative Patterns The k-fold sequential execution of an event a: A length-based window of size n: A sum over an unbound event stream until a threshold value is met: FZI Forschungszentrum Informatik 16

17 ETALIS: Operational Semantics (SEQ) a SEQ b SEQ c ce1 ((a SEQ b) SEQ c) ce1 1. Complex event pattern 2. Decoupling a SEQ b ie ie SEQ c ce1 3. Binarization 4. Event-driven backward chaining (EDBC) rules FZI Forschungszentrum Informatik 17

18 Order of Rule Execution: SEQ & AND c SEQ b a b SEQ a ie a OP1 OP2 ie c b c SEQ b a b AND a ie FZI Forschungszentrum Informatik 18

19 Additional Features in ETALIS Aggregates; Alarms; Consumption policies; Event-triggered actions; Dynamic updates; Multiplication of events; Garbage collection; Justification; Retractions; Out-of-order; Join; Projection; Selection Windows Logging; Event persistence Many of these features are contributed to the use of EDBC Rules and the Logic Programming approach in ETALIS FZI Forschungszentrum Informatik 19

20 EP-SPARQL FZI Forschungszentrum Informatik 20

21 handles handle EP-SPARQL: Toward Real-Time Semantic Web Rapidly changing data represented as events Static or slowly evolving background knowledge Event Processing (EP) Semantic Web technologies including EP SPARQL EP-SPARQL Temporal relatedness Semantic relatedness Stream reasoning FZI Forschungszentrum Informatik 21

22 EP-SPARQL - Syntax Extends SPARQL to enable event-based processing by taking into account temporal situatedness of triple assertions. Syntactical and semantic downward-compatibility to plain SPARQL. Operators: FILTER, AND, UNION, OPTIONAL, SEQ, EQUALS, OPTIONALSEQ, and EQUALSOPTIONAL getduration() yields a literal of type xsd:duration giving the time interval associated to the graph pattern getstarttime() and getendtime() retrieve the time stamps of type xsd:datetime of the start and end of the interval; FZI Forschungszentrum Informatik 22

23 EP-SPARQL - Semantics FZI Forschungszentrum Informatik 23

24 EP-SPARQL Example: Traffic Monitoring D. Anicic, P. Fodor, S. Rudolph, N. Stojanovic. EP-SPARQL: A Unified Language for Event Processing and Stream Reasoning, WWW FZI Forschungszentrum Informatik 24

25 IMPLEMENTATION AND EVALUATION FZI Forschungszentrum Informatik 25

26 ETALIS: System Diagram Parser Compiler Execution Auxiliary components

27 ETALIS Interfaces FZI Forschungszentrum Informatik 27

28 Throughput (1000 x Events/Sec) Throughput (1000 x Events/Sec) Common Operators I Test patterns: Esper P-SWI P-YAP Esper P - SWI P - Yap Event stream size x Event stream size x FZI Forschungszentrum Informatik 28

29 Throughput (1000 x Events/Sec) Throughput (1000 x Events/Sec) Common Operators II Test patterns: Esper P-SWI P-Yap Esper P-SWI P-Yap Event stream size x ,5 5 7,5 10 Event stream size x FZI Forschungszentrum Informatik 29

30 Iterative Event Patterns Test patterns: Supply chain Check paths between the path from 100 the beginning and 5000 or from the last event FZI Forschungszentrum Informatik 30

31 Reasoning delay in ms Evaluation: Stream Reasoning Sub-class relations computed on-the-fly Test pattern: infer over streaming triples whether the subject of a triple is an instance of the class of concern, or any of its 40,080 subclasses No. of triples vs. Reasoning delay ETALIS-YAP Number of triples FZI Forschungszentrum Informatik 31

32 Consumed time in ms Consumed Memory in kb Scenario: Stream Reasoning Evaluation A Goods Delivery system in the city of Milan An agent delivers goods to a certain location While visiting a location, the system listens to traffic events related to the next location Inaccessible routes are recomputed on-the-fly 1 Visitor 10 Visitors 1 Visitor 10 Visitors Number of locations Number of locations Milan ontology was generously provided by AMAT Milano and CEFRIEL team: FZI Forschungszentrum Informatik 32

33 APPLICATIONS FZI Forschungszentrum Informatik 33

34 ETALIS in Use The Fast Flower Delivery in EPIA Event Processing in Action, by Opher Etzion and Peter Niblett An EPN implemented in ETALIS The Drug Discovery in SYNERGY Collaborative work on drug design ETALIS: extending SOA with EDA On the Live Measurements of Environmental Phenomena MesoWest sensor network Analysing sensor data over time and geographical space FZI Forschungszentrum Informatik 34

35 Smart Automation Intelligent Diagnosis in Manufacturing Networks ETALIS + Semantic Guide FZI Forschungszentrum Informatik 35

36 Smart Home FZI Living Lab: Ambient Assisted Living Demonstrates technologies and use cases Includes end-users and experts into research Helps to evaluate research results and service prototypes Goal: to enable real-time reactivity in an AAL scenario Use sensor networks for increasing situational awareness e.g. enable real-time reaction on dangerous situations 36

37 EP & SR Outlook FUTURE WORK FZI Forschungszentrum Informatik 37

38 Industry 4.0: From IoT to Event-driven and-cloudbased Services Event-Driven Predictive Analytics Event predictions with ETALIS Big scale intelligent Event Processing & Stream Reasoning Distributed ETALIS Event-Driven Cyber- Physical Systems Embedded ETALIS FZI Forschungszentrum Informatik 38

39 Credits People that contributed greatly to this work are: Dr. Sebastian Rudolph, KIT, Germany Dr. Paul Fodor, Stony Brook University, USA Roland Stühmer, a PhD student, FZI, Germany Ahmed Khalil Hafsi, a Master student at KIT, Germany Jia Ding, a Master student at KIT, Germany Vesko Georgiev, a Master student at TU Munich, Germany FZI Forschungszentrum Informatik 39

40 References [1] D. Anicic, S. Rudolph, P. Fodor, N. Stojanovic. Real-Time Complex Event Recognition and Reasoning A Logic Programming Approach, Applied Artificial Intelligence, Volume 26 Special Issue on Event Recognition. January [2] D. Anicic, S. Rudolph, P. Fodor, N. Stojanovic. Stream Reasoning and Complex Event Processing in ETALIS, Semantic Web Journal, Special Issue: Semantic Web Tools and Systems [3] D. Anicic, P. Fodor, S. Rudolph, R. Stühmer, N. Stojanovic, R. Studer.. ETALIS: Rule-Based Reasoning in Event Processing, Chapter in Reasoning in Event-based Distributed Systems, Springer. [4] D. Anicic, P. Fodor, S. Rudolph, R. Stühmer, N. Stojanovic, R. Studer.. A Rule-Based Language for Complex Event Processing and Reasoning, RR [5] D. Anicic, P. Fodor, S. Rudolph, N. Stojanovic. EP-SPARQL: A Unified Language for Event Processing and Stream Reasoning, WWW [6] D. Anicic, S. Rudolph, P. Fodor, N. Stojanovic. Retractable Complex Event Processing and Stream Reasoning, RuleML [7] D. Anicic, S. Rudolph, P. Fodor, N. Stojanovic. A Declarative Framework for Matching Iterative and Aggregative Patterns against Event Streams, RuleML [8] P. Fodor, D. Anicic, S. Rudolph. Results on Out-of-Order Event Processing, PADL [9] D. Anicic, P. Fodor, R. Stühmer, N. Stojanovic. Event-driven Approach for Logic-based Complex Event Processing, The IEEE International Conference on Computational Science and Engineering FZI Forschungszentrum Informatik 40

41 Thank you for your attention! ETALIS FZI Forschungszentrum Informatik 41