LIP: an efficient lightweight iterative positioning algorithm for wireless sensor networks

Wireless sensor networks (WSNs) are increasingly being used in remote environment monitoring, security surveillance, military applications, and health monitoring systems among many other applications. Designing efficient localization techniques have been a major obstacle towards the deployment of WSN for these applications. In this paper, we present a novel lightweight iterative positioning (LIP) algorithm for next generation of wireless sensor networks, where we propose to resolve the localization problem through the following two phases: (1) initial position estimation and (2) iterative refinement. In the initial position estimation phase, instead of flooding the network with beacon messages, we propose to limit the propagation of the messages by using a random time-to-live for the majority of the beacon nodes. In the second phase of the algorithm, the nodes select random waiting periods for correcting their position estimates based on the information received from neighbouring nodes. We propose the use of Weighted Moving Average when the nodes have received multiple position corrections from a neighbouring node in order to emphasize the corrections with a high confidence. In addition, in the refinement phase, the algorithm employs low duty-cycling for the nodes that have low confidence in their position estimates, with the goal of reducing their impact on localization of neighbouring nodes and preserving their energy. Our simulation results indicate that LIP is not only scalable, but it is also capable of providing localization accuracy comparable to the Robust Positioning Algorithm, while significantly reducing the number of messages exchanged, and achieving energy savings.