Minimizing the Communication Cost for Continuous Skyline Maintenance
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Date
2008-05-29
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Abstract
Numerous algorithms in the recent database literature deal with variants of skyline queries in different problem settings. However, the existing work 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 avoids transmission 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. The Filter method 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 ? of the s most recent times- tamps. The Filter method 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 the Filter and Sampling methods in a Hybrid approach that combines their individual advantages. We evaluate our techniques with extensive experiments.