Multi Objective Optimization Of UAV Base Station Deployment For Enhanced VANET Connectivity Using NSGA-II

Abstract

In the context of Vehicular Ad Hoc Networks (VANETs), UAV base stations have emerged as a critical component for extending network coverage and connectivity. However, the optimal placement of these UAV base stations is a complex challenge that requires a delicate balance between maximizing coverage and minimizing latency—two key factors crucial for enhancing overall network performance. To tackle these challenges comprehensively, we introduce a multifaceted mechanism[1] aimed at optimizing both coverage and latency for UAV base stations within VANETs. This mechanism unfolds in two main stages: Firstly, we address the critical question of optimal altitude selection for UAV base stations. This foundational step is essential in ensuring effective coverage and reducing latency. Subsequently, we employ the Non-dominated Sorting Genetic Algorithm II (NSGA-II) in conjunction with crowding techniques to thoroughly explore the solution space. This synergistic approach identifies solutions that strike a harmonious balance between maximizing coverage and minimizing latency, ultimately optimizing overall network operation. To evaluate the effectiveness of our proposed mechanism, we rigorously benchmark it against contemporary standards. Through comprehensive analysis, we assess its impact on both coverage and latency, revealing significant potential for substantial performance improvements. The empirical results underscore the viability of our mechanism in enhancing the efficiency of UAV base stations within VANETs.