Progressive skyline query processing in wireless sensor networks

With the further development of sensor techniques in wireless sensor networks (WSNs), it is becoming urgent that they should be able to support complicated queries like skyline query for multi-preference and decision making. In this paper, we consider skyline query evaluation in WSNs by devising evaluation algorithms for finding skyline points on a dataset progressively. The core techniques adopted are to partition the dataset into several disjoint subsets and output the skyline points by examining each subsequent subset progressively, using some of the skyline points obtained so far to filter out those unlikely skyline points in the current processing subset from transmission. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithms on synthetic and real datasets. The experimental results show that the proposed algorithms outperform existing algorithms significantly in network lifetime prolongation.