Abstract
This paper presents a novel approach to processing continuous aggregate queries in sensor networks, which lifts the assumption of tree-based routing. Given a query workload and a special-purpose gateway node where results are expected, the query optimizer exploits query correlations in order to generate an energy-efficient distributed evaluation plan. The proposed optimization algorithms identify common query sub-aggregates, and propose common routing structures to share the sub-aggregates at an early stage. Moreover, they avoid routing sub-aggregates of the same query through long-disjoint paths, thus further reducing the communication cost of result propagation. The proposed algorithms are fully-distributed, and are shown to offer significant communication savings compared to existing tree-based approaches. A thorough experimental evaluation shows the benefits of the proposed techniques for a variety of query workloads and network topologies.
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Trigoni, N., Guitton, A., Skordylis, A. (2007). Interplay of Processing and Routing in Aggregate Query Optimization for Sensor Networks. In: Rao, S., Chatterjee, M., Jayanti, P., Murthy, C.S.R., Saha, S.K. (eds) Distributed Computing and Networking. ICDCN 2008. Lecture Notes in Computer Science, vol 4904. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77444-0_42
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DOI: https://doi.org/10.1007/978-3-540-77444-0_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77443-3
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