Iterative Localization in Decentralized Environment of WSN and IoT

In the recent literature, sensor localization has been considered as the most technical challenge of internet of thing and Wireless Sensor Networks. The main objective is to predict an accurate localization of sensor nodes. Recent approaches dealing with localization rely on meta-heuristics algorithms; hence, the localization procedure becomes an optimization issue in a multidimensional space. Bat algorithms are well suited for this kind of problems. It is also known in several recent papers that the Bat algorithm is well suited in space exploitation, but not as much in exploration. Throughout the paper, we propose an enhanced hybrid approach, namely “Enhanced Bat Algorithm with Doppler Effect or “EBADE”. Bat parameters are tuned using a modified frequency equation. EBADE computes thus iterative the position of the nodes through optimizing node Euclidean distances. Experimental results come up with remarkable improvement in terms of localization error and CPU run-time.