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  1. Proceedings of the on SIGMOD/PODS 2012 PhD Symposium (PhD '12)
  2. Towards an extensible efficient event processing kernel
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Towards an extensible efficient event processing kernel

Content Provider ACM Digital Library
Author Sadoghi, Mohammad
Abstract The efficient processing of large collections of patterns (Boolean expressions, XPath queries, or continuous SQL queries) over data streams plays a central role in major data intensive applications ranging from user-centric processing and personalization to real-time data analysis. On the one hand, emerging user-centric applications, including computational advertising and selective information dissemination, demand determining and presenting to an end-user only the most relevant content that is both user-consumable and suitable for limited screen real estate of target (mobile) devices. We achieve these user-centric requirements through novel high-dimensional indexing structures and (parallel) algorithms. On the other hand, applications in real-time data analysis, including computational finance and intrusion detection, demand meeting stringent subsecond processing requirements and providing high-frequency and low-latency event processing over data streams. We achieve real-time data analysis requirements by leveraging reconfigurable hardware -- FPGAs -- to sustain line-rate processing by exploiting unprecedented degrees of parallelism and potential for pipelining, only available through custom-built, application-specific, and low-level logic design. Finally, we conduct a comprehensive evaluation to demonstrate the superiority of our proposed techniques in comparison with state-of-the-art algorithms designed for event processing.
Ending Page 8
Page Count 6
Starting Page 3
File Format PDF
ISBN 9781450313261
DOI 10.1145/2213598.2213602
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2012-05-20
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Boolean expression indexing Publish/subscribe Complex event processing Data-centric workflows Data streams And fpgas
Content Type Text
Resource Type Article
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