Obstacle Aware Density Based Nano-Router Localization in IoNT

Wireless Nano-Sensor Networks (WNSNs) are dense networks consisting of many nano-machines that work on nano-scale mediums in Internet of Nano-Things (IoNT) applications. In these kinds of mediums, the communication range is limited and could be interrupted by obstacles. Thus, the nano-router should be positioned in the correct location in order to achieve high data flow accuracy. Therefore, in this paper, a Machine Learning-supported obstacle-aware density-based nano-router localization algorithm is proposed in IoNT applications. The proposed algorithm is compared with the networks having only a nano-router which is placed at [0, 0] coordinates of the network. According to the results, the proposed algorithm successfully finds the best locations of the nano-routers on the network due to the nano-node density caused by the obstacles on the medium.