Adaptive DV-HOP Location Algorithm Using Anchor-Density-based Clustering for Wireless Sensor Networks

Localization is an important topic in the wireless sensor networks (WSN) because sensor nodes are randomly scattered over a region and can get connected into a network on their own. In this paper, we proposed an adaptive DV-HOP location algorithm using anchor-density-based clustering for wireless sensor networks. First, we select the maximum core density anchor node as head to reduce regional distance error; second, we divide cluster into different grade according to the number of anchor nodes and unknown nodes in each cluster; last, we use different method to locate unknown position for high-density cluster, low density cluster and sparse density cluster. The algorithm does not change the basic orientation of the traditional DV-Hop algorithm process, does not require additional hardware support and performs efficiently in regular as well as irregular network topologies. Simulation shows that the localization accuracy of the proposed algorithm is better and the communication overhead is lower than the traditional DV-HOP algorithm. Copyright © 2013 IFSA.