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Title: Minimizing the communication cost for continuous skyline maintenance
Authors: Zhang, Zhenjie
Cheng, Reynold
Papadias, Dimitris
Tung, Anthony K. H.
Keywords: Skyline query
Continuous query
Issue Date: 2009
Citation: To appear in the Proceedings of the ACM Conference on the Management of Data (SIGMOD), Providence, Rhode Island, U.S.A., June 29-July 2, 2009
Abstract: Existing work in the skyline literature focuses on optimizing the processing cost. This paper aims at minimization of the communication overhead in client-server architectures, where a server continuously maintains the skyline of dynamic objects. Our first contribution is a Filter method that avoidstransmission of updates from objects that cannot influence the skyline. Specifically, each object is assigned a filter so that it needs to issue an update only if it violates its filter. Filter achieves significant savings over the naive approach of transmitting all updates. Going one step further, we introduce the concept of frequent skyline query over a sliding window (FSQW). The motivation is that snapshot skylines are not very useful in streaming environments because they keep changing over time. Instead, FSQW reports the objects that appear in the skylines of at least θ·s of the s most recent timestamps (0 < θ ≤ 1). Filter can be easily adapted to FSQW processing, however, with potentially high overhead for large and frequently updated datasets. To further reduce the communication cost, we propose a Sampling method, which returns approximate FSQW results without computing each snapshot skyline. Finally, we integrate Filter and Sampling in a Hybrid approach that combines their individual advantages.
Rights: © ACM, 2009. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version will be published in Proceedings of the ACM Conference on the Management of Data (SIGMOD), Providence, Rhode Island, U.S.A., June 29-July 2, 2009.
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