Grand challenge: MapReduce-style processing of fast sensor data

Authors:
Kasper Grud Skat Madsen;Li Su;Yongluan Zhou
Affiliations:
University of Southern Denmark, Odense, Denmark;University of Southern Denmark, Odense, Denmark;University of Southern Denmark, Odense, Denmark
Venue:
Proceedings of the 7th ACM international conference on Distributed event-based systems
Year:
2013

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Abstract

MapReduce is a popular scalable processing framework for large-scale data. In this paper, we first briefly present our efforts on rectifying the traditional batch-oriented MapReduce framework for low-latency data stream processing. We investigated how to utilize such a MapReduce-style platform for fast sensor data processing by taking the DEBS Grand Challenge 2013 as an example. Both the analysis and experiments verify that our approach can obtain highly scalable solutions.