Pattern rewriting framework for event processing optimization

Rabinovich, Ella; Etzion, Opher; Gal, Avigdor

doi:10.1145/2002259.2002277

Cited by 14 publications

(17 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A general methodology for pattern rewriting, which is similar in spirit to the first stage of pattern transformation, was proposed by Rabinovich et al [35]. In this work, we show how pattern rewriting can be instantiated in the presence of business processes.…”

Section: Related Workmentioning

confidence: 93%

Optimizing Event Pattern Matching Using Business Process Models

Weidlich

Ziekow²,

Gal

et al. 2014

IEEE Trans. Knowl. Data Eng.

Self Cite

View full text Add to dashboard Cite

A growing number of enterprises use complex event processing for monitoring and controlling their operations, while business process models are used to document working procedures. In this work, we propose a comprehensive method for complex event processing optimization using business process models. Our proposed method is based on the extraction of behaviorial constraints that are used, in turn, to rewrite patterns for event detection, and select and transform execution plans. We offer a set of rewriting rules that is shown to be complete with respect to the all, seq, and any patterns. The effectiveness of our method is demonstrated in an experimental evaluation with a large number of processes from an insurance company. We illustrate that the proposed optimization leads to significant savings in query processing. By integrating the optimization in state-of-the-art systems for event pattern matching, we demonstrate that these savings materialize in different technical infrastructures and can be combined with existing optimization techniques.Index Terms-Event processing, query optimisation, query rewriting Ç M. Weidlich is with the

show abstract

Section: Related Workmentioning

confidence: 93%

Optimizing Event Pattern Matching Using Business Process Models

Weidlich

Ziekow²,

Gal

et al. 2014

IEEE Trans. Knowl. Data Eng.

Self Cite

View full text Add to dashboard Cite

show abstract

“…In [9], an assertion-based pattern rewriting framework is presented for two operators, namely all (AN D) and sequence (SEQ). The patterns are split into disconnected components that can be independently processed.…”

Section: Query Rewriting/reorderingmentioning

confidence: 99%

Issues in Complex Event Processing Systems

Flouris

Giatrakos

Garofalakis

et al. 2015

2015 IEEE Trustcom/BigDataSE/Ispa

View full text Add to dashboard Cite

Many Big Data technologies were built to enable the processing of human generated data, setting aside the enormous amount of data generated from Machine-to-Machine (M2M) interactions. M2M interactions create real-time data streams that are much more structured, often in the form of series of event occurrences. In this paper, we provide an overview on the main research issues confronted by existing Complex Event Processing (CEP) techniques, as a starting point for Big Data applications that enable the monitoring of complex event occurrences in M2M interactions.

show abstract

“…The context representation in our work is based on the fuzzy ontology framework of [14] and optimized for event processing.…”

Section: A Fuzzy Ontology Based Context Representationmentioning

confidence: 99%

“…Ella et al, presented a formal model for pattern rewriting and demonstrated its usage in a comprehensive set of rewriting techniques for complex pattern types, taking various semantic interpretations into account [14]. Nicholas et al proposed a distributed complex event processing method based on query rewriting [15].…”

Section: Introductionmentioning

confidence: 99%

The Research on CEP Based on Query Rewriting for CPS

Cao¹,

Li²,

Wang³

2013

IJMO

View full text Add to dashboard Cite

Abstract-Now we are entering the era of "Big Data", and the important data source of which is Cyber Physical System (CPS) data, those data can hardly be processed by present data processing technology. Complex Event Processing (CEP) is the key part of middleware of CPS, which can process the big data, and context-awareness is an important feature of CEP engine. There are some challenges in context-aware complex event processing for CPS, such as heterogeneous, massive data, distributed event processing, uncertainly; therefore, we propose a distributed context-aware event processing method, based on context representation proposed fuzzy ontology and a distributed multi-level context reasoning method to support uncertainty and linguistic variables in event queries. Based on fuzzy ontology query and similarity based distributed reasoning, complex event query plans are generated and context-aware queries are rewritten into context independent sub-queries. Data window is partitioned according to different event patterns and context. The sub-queries are optimized and executed parallel based on data partition. The experiments show that this method can support fuzzy context in CEP and have acceptable performance and scalability.

show abstract

Pattern rewriting framework for event processing optimization

Cited by 14 publications

References 18 publications

Optimizing Event Pattern Matching Using Business Process Models

Optimizing Event Pattern Matching Using Business Process Models

Issues in Complex Event Processing Systems

The Research on CEP Based on Query Rewriting for CPS

Contact Info

Product

Resources

About