An Efficient Location Signature Generation‐Based Localization Framework Using Flog Algorithm in Wireless Sensor Networks

ABSTRACT In Wireless Sensor Networks (WSNs), localization is extensively wielded for determining the current location of the Sensor Nodes (SNs). But, localization is a challenging task. The localization problems in WSN can be addressed by the existing localization algorithms with the consequences of cost, size, as well as energy problems only. Thus, an efficient location signature generation framework is presented by using the Flexible Ligands Oriented on Grid (FLOG) localization algorithm in WSN. Primarily, the regions are identified and the nodes are randomly deployed. Then, the signal strength is collected. The sensor field is divided into equal triangles in which edge set, vertex set, and coverage value are extracted after the deployment of all the nodes. Then, by using Moore Graph 1‐Separation Formula Kemeny Constant, a planar graph is plotted. After taking all the edge nodes, the exact location of the nodes is discovered by using the Trilateration‐based Gorilla Troop Optimization along with the SAT‐3 algorithm (T‐GTO‐SAT‐3). Then, by using True‐True Matching, the location results are matched with the original node deployment status. Moreover, by using FLOG, the location signature is generated and the nodes are localized. Next, by using Eulerian Learning (EL), the dissemination line setup is done. Lastly, based on the threshold values, the network lifetime is calculated. Hence, the results proved that the proposed model obtained a Mean Localization Error (MLE) of 0.01, which outperformed traditional approaches.