Comparative Evaluation of Swarm Intelligence- Based Multipath Routing Protocols for Video Streaming in Vehicular Ad-Hoc Networks

Abstract

Video streaming in Vehicular Ad-Hoc Networks (VANETs) poses significant challenges due to strict Quality of Service (QoS) requirements, such as high throughput, reliable packet delivery, low transmission delay, and stable performance—particularly critical in emergency scenarios. These challenges are exacerbated by the inherently dynamic nature of VANETs, characterized by rapidly changing network topologies, varying vehicle densities, and environmental obstacles. This study examines the potential of Swarm Intelligence (SI) algorithms in optimizing routing protocols, emphasizing their adaptability and flexibility, which make them well-suited to the dynamic conditions of VANETs.
This paper provides an in-depth review of various SI-based multi-path routing protocols, including Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Moth Whale Optimization Algorithm (MWOA), and the Butterfly Optimization-PSO Hybrid (BO-PSO). The performance of these protocols is assessed based on key QoS metrics—End-to-End Delay (E2ED), Throughput (Th), and Packet Delivery Ratio (PDR)—under different vehicle density scenarios (50 and 100 nodes).
The results demonstrate that the ACO-based protocol excels in minimizing delay, making it particularly effective for emergency situations. Conversely, the MWOA protocol achieves superior throughput and enhanced packet delivery, rendering it more suitable for non-safety applications. These findings underscore the potential of SI algorithms in developing robust, efficient multi-path routing solutions for reliable, high-quality video streaming in dynamic vehicular environments.