Sea Turtle Foraging and Hydrozoan Optimization Algorithm-based NLOS Node Positioning Scheme for Reliable Data Dissemination in Vehicular Ad hoc Networks

Vehicular Ad hoc NETworks (VANETs) is considered as an indispensable and predominant research area for facilitating public safety applications due to their ever increasing demand. The vehicular nodes in VANETs interact among them for the objective of exchanging traffic information, road maps and warning messages during emergency scenarios. In most of the applications supported by vehicular network, accuracy in localization is the major challenge when the location-based services are their core service. This major problem of localization is mainly due to Non Line of Sight (NLOS) nodes in the vehicular node whose position is unknown or unpredicted due to the existence of static and moving obstacles in the vehicular network. The problem of NLOS node localization is a Non Polynomial (NP) hard problem that could be potentially solved through the use of intelligent metaheuristic nature-inspired optimization algorithms. In this paper, Sea Turtle Foraging (STFOA)-and Hydrozoan Optimization Algorithm (HOA)-based NLOS node positioning scheme is proposed by embedding the exploitation capabilities of STFOA into exploration tendency imposed HOA algorithm for achieving reliable warning message delivery during emergency situations in vehicular networks. This proposed STFHOA scheme adopted a dynamic crossover operator through the incorporated hybrid algorithm in order to enhance the tendencies of exploration. The simulation results of the proposed STFHOA confirmed better mean warning message rate of 16.38%, mean channel utilization rate of 18.84%, mean neighborhood awareness rate of 17.21% with minimized mean localization error rate of 17.64% compared to the baseline approaches under scalable increase in the number of vehicular nodes in the network.