A data-related cluster architecture based pruning strategy

Abstract

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.

Connected Key Node Set‐Based Skyline Query Processing over Wireless Sensor Networks

“…The basic idea of MinMax-threshold approach such as MINMAX [10] , the plane project parallel skyline query strategy [13] and the incremental maintenance of the skyline [13] , is to use a threshold to prune the dominated data at intermediate tree nodes. Data-related cluster architecture based on the pruning strategy [14] use the MINMAX algorithm to find the global pruning value, and then cluster heads can determine whether to send sensor data to the lower layer member nodes. In the MinMax-threshold approach, the threshold of each node is determined locally so that many locally resultant tuples are not the global skyline.…”