JCP 2017 Vol.12(4): 317-334 ISSN: 1796-203X
doi: 10.17706/jcp.12.4.317-334
doi: 10.17706/jcp.12.4.317-334
A Novel Engine: Complex Event Processing with LAIPE
Dong Wang1, Mingquan Zhou1, 2, Sajid Ali3, Yusong Liu4, Pengbo Zhou2
1School of Information Science and Technology, Northwest University, Xi’an 710127, China.
2College of Information Science and Technology, Beijing Normal University, Beijing 100875, China.
3Department of Computer Scinece, University of Education, Lahore 60000, Pakistan.
3School of Information, Renmin University of China, Beijing 100872, China.
Abstract—Most of the Complex Event Processing (CEP) engines are responsible for filtering, selecting and aggregating atomic events to represent high level composite events according to predefined rules are the latest breed of event-oriented software, which is being presented nowadays to better support timely information processing. Introducing CEP engines to the information system domain provides an opportunity to enhance the capabilities of event processing in real-time. To answer this need, we first propose an event algebra that defines the detailed semantics of event models and operators. More specifically, we propose a Lightweight Automata based Incremental Processing Engine (LAIPE) based on a layered architectural design. On the one hand, it adopts a language (LAIPL) and its rule structure which explicitly conceived to natural and easy identification of complex events. On the other hand, it provides efficient algorithms for rule translation and event incremental processing approach based on event automaton model. Finally, our evaluation on LAIPE and existing Esper engine shows that the time cost of LAIPE is averagely reduced 42.3% than Esper in different tests, and our developed engine has better performance in processing different sliding window and selectivity rates with a large number of events.
Index Terms—Complex event processing, light-weight automata based incremental processing, event automaton, event processing engine.
2College of Information Science and Technology, Beijing Normal University, Beijing 100875, China.
3Department of Computer Scinece, University of Education, Lahore 60000, Pakistan.
3School of Information, Renmin University of China, Beijing 100872, China.
Abstract—Most of the Complex Event Processing (CEP) engines are responsible for filtering, selecting and aggregating atomic events to represent high level composite events according to predefined rules are the latest breed of event-oriented software, which is being presented nowadays to better support timely information processing. Introducing CEP engines to the information system domain provides an opportunity to enhance the capabilities of event processing in real-time. To answer this need, we first propose an event algebra that defines the detailed semantics of event models and operators. More specifically, we propose a Lightweight Automata based Incremental Processing Engine (LAIPE) based on a layered architectural design. On the one hand, it adopts a language (LAIPL) and its rule structure which explicitly conceived to natural and easy identification of complex events. On the other hand, it provides efficient algorithms for rule translation and event incremental processing approach based on event automaton model. Finally, our evaluation on LAIPE and existing Esper engine shows that the time cost of LAIPE is averagely reduced 42.3% than Esper in different tests, and our developed engine has better performance in processing different sliding window and selectivity rates with a large number of events.
Index Terms—Complex event processing, light-weight automata based incremental processing, event automaton, event processing engine.
Cite: Dong Wang, Mingquan Zhou, Sajid Ali, Yusong Liu, Pengbo Zhou, "A Novel Engine: Complex Event Processing with LAIPE," Journal of Computers vol. 12, no. 4, pp. 317-334, 2017.
General Information
ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: [email protected]
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