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On Load Shedding in Complex Event Processing

TLDR
This paper formalizes broad classes of CEP load-shedding scenarios as different optimization problems and demonstrates an array of complexity results that reveal the hardness of these problems and construct shedding algorithms with performance guarantees.
Abstract
Complex Event Processing (CEP) is a stream processing model that focuses on detecting event patterns in continuous event streams. While the CEP model has gained popularity in the research communities and commercial technologies, the problem of gracefully degrading performance under heavy load in the presence of resource constraints, or load shedding, has been largely overlooked. CEP is similar to “classical” stream data management, but addresses a substantially different class of queries. This unfortunately renders the load shedding algorithms developed for stream data processing inapplicable. In this paper we study CEP load shedding under various resource constraints. We formalize broad classes of CEP load-shedding scenarios as different optimization problems. We demonstrate an array of complexity results that reveal the hardness of these problems and construct shedding algorithms with performance guarantees. Our results shed some light on the difficulty of developing load-shedding algorithms that maximize utility.

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Citations
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Load Shedding for Complex Event Processing: Input-based and State-based Techniques

TL;DR: This work introduces a hybrid model that combines both input-based and statebased shedding to achieve high result quality under constrained resources and indicates that such hybrid shedding improves the recall by up to 14× for synthetic data and 11.4× for real-world data, compared to baseline approaches.
References
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Proceedings Article

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Proceedings ArticleDOI

Sequence Pattern Query Processing over Out-of-Order Event Streams

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