Hybrid invasive weed optimization and squirrel search algorithm-based NLOS nodes localization mechanism for improving reliable data dissemination in VANETs

In emergency situations, the localization of Non Line of Sight (NLOS) nodes is essential for enhancing the reaction time of the vehicle drivers in response to the stimulus generated in VANETs. However, the existence of NLOS nodes intentionally or intentionally introduces broadcasting storm and congestion in the network. In this paper, a Hybrid Invasive Weed Optimization and Squirrel Search Algorithm-Localization Mechanism (HIWO-SSA-LM) is proposed for improving the localization of NLOS nodes to enhance the reliable data dissemination under emergency situations in VANETs. This proposed HIWO-SSA-LM integrates the reproductive capability of Invasive Weeds into the reproductive potential of a Flying Squirrel Algorithm for sustaining the degree of balance under exploitation and exploration involved during NLOS node localization. The predominance of the proposed HIWO-SSA-LM is explored based on experiments conducted using EstiNet 8.1 simulator using emergency message delivery rate, channel utilization rate, and neighborhood awareness rate by varying the number of vehicles and NLOS nodes in the network.