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Hummer, W., Satzger, B., & Dustdar, S. (2013). Elastic stream processing in the Cloud. WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, VOUME 3(5), 333–345. http://hdl.handle.net/20.500.12708/155218
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY
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ISSN:
1942-4787
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Date (published):
2013
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Number of Pages:
13
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Publisher:
WILEY PERIODICALS, INC
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Peer reviewed:
Yes
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Abstract:
Stream processing is a computing paradigm that has emerged from the necessity of handling high volumes of data in real time. In contrast to traditional databases, stream-processing systems perform continuous queries and handle data on-thefly. Today, a wide range of application areas relies on efficient pattern detection and queries over streams. The advent of Cloud computing fosters the development
of elastic stream-processing platforms, which are able to dynamically adapt based on different cost-benefit trade-offs. This article provides an overview of the historical evolution and the key concepts of stream processing, with special focus on adaptivity and Cloud-based elasticity.
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Research Areas:
Distributed and Parallel Systems: 95% Computer Science Foundations: 5%
