Effective Self Adaptive Multiple Source Localization Technique by Primal Dual Interior Point Method in Binary Sensor Networks

Abstract

Wireless sensor networks are creating a new era of pervasive computing applications, such as various monitoring and tracking system. The sensor network consists of so many tiny sensor nodes that have so many critical challenges, since they are battery operated and have limited processing capabilities. Binary sensor networks are modeled in a way that the sensor nodes can communicate with the only 1 b of information. One of the challenges in a binary sensor network is to localize the multiple sources. Very few works have been done considering this challenge. Localization failure may cause the whole system useless. We propose a multiple source localization method. We convert the localization problem into an optimization problem, and we solve that optimization problem using primal dual interior point method. Simulation results show that our proposed method provides better performance in every perspective compared with the existing works.