An Efficient Index Building Algorithm for Selection of Aggregator Nodes in Wireless Sensor Networks

Abstract

In wireless sensor networks (WSNs), aggregator nodes perform the data aggregation process. Thus, careful selection of the aggregator nodes is needed to reduce network traffic in data aggregation process and prolong overall lifetime of the network. In this paper, we formulate selection process of the aggregator nodes as a top-k query problem. To answer the top-k queries efficiently in the large-scale WSNs, building and using the indexes are important. Thus, we propose an efficient index building algorithm for selection of aggregator nodes, called the Approximate Convex Hull Index (simply, aCH-Index). The main idea of our approach is to construct a convex hull over the sensor nodes in the WSNs, which enables speeding up the extraction of a set of sensor nodes that are potential candidates to become an aggregator node. In order to do so, the aCH-Index computes the skyline over the entire set of the sensor nodes, partitions the region into multiple subregions to reduce the computing time of convex hull in all origins, and then computes the convex hull in each subregion. Through the experiments with synthetic data, we show that aCH-Index outperforms the existing methods.