In this paper, we propose a novel skyline query algorithm in wireless sensor networks, according to the data's dominate ability progressively return the sensor data to construct the filter. At the same time, in order to reduce the overhead of the filter construction and broadcasting, we adopt mapping strategy to further eliminate the filtering cost. Theoretical analysis and experimental results all show that it can effectively reduce the communication cost, and eventually prolong the lifetime of the network.
In this paper we proposed a skyline query algorithm-DRCSky in wireless sensor networks. According to the history data's correlation the WSNs constructs multi-layer cluster architecture. The cluster heads collect statistic information of its member nodes, using the MIN-MAX algorithm to find the global pruning value--MINMAX-value, and then the cluster heads can determine whether to send the sensor data to its lower layer member nodes according to the MINMAX-value and the member nodes' uploaded statistic information, and finally achieve cluster-level pruning. The performance study indicates that DRCSky algorithm can effectively reduce the communication cost of the network and prolong the lifetime of WSNs significantly.
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