Hybrid Optimization with Enhanced QoS-based Path Selection in VANETs

Abstract

Vehicular ad hoc networks (VANETs) recently covered a wide range of intelligent transportation systems (ITSs) and applications. VANETs consist of convinced unique characteristics such as dynamic movement and high speed. Due to these characteristics, link failures occur, and delay and routing overhead is greatly increased, directly affecting the effectiveness, Quality of Service (QoS), and stability of VANETs. To achieve an efficient and reliable network performance, this paper proposes QoS Aware Hybrid Optimization for Improving Path Selection (HOIPS-VANETs) in VANETs. This hybrid optimization combines the Improved ant colony optimization (ACO) and Effective Whale Optimization Algorithm (EWOA). The EWOA algorithm is used for initial optimal path selection, and ACO is used to find the best optimal solution to achieve effective communication in VANETs. This optimization technique is also applied to low-density, medium-density, and high-density scenarios, as it is compared with the earlier methods. During the experimentation process, our findings reveal no noticeable change in the performance of the earlier methods when applied to the low-density and medium-density scenarios. Still, the performance is gradually reduced when applied to the high-density scenario. On the other hand, the performance of the proposed approach is better for all three tested scenarios and demonstrates effective communication for the VANETs.

Migrating Walrus Algorithm: A New Metaheuristic that Hybridizes Migration Algorithm and Walrus Optimization Algorithm

“…Mahdi and Yuhaniz modified the sparrow search algorithm and utilized it to improve the categorization of COVID-19 patients [2]. The ant colony optimization (ACO) and whale optimization algorithm (WOA) has been hybridized to improve the path selection process in the vehicular ad-hoc networks (VANET) system [3]. Bektas, Karaca, Taha, and Zaynal utilized the red deer algorithm (RDA) to eliminate the desired harmonic order in the multi-level inverters (MLI) by finding the optimum switching angles in this MLI [4].…”