Particle Swarm Optimization Video Streaming Service in Vehicular Ad-Hoc Networks

Owing to the increasing capabilities of mobile devices and the development of mobile communication techniques in vehicular ad hoc networks (VANETs), mobile multimedia services have focused on supporting high Quality of Service (QoS) and Quality of Experience (QoE) for the subscribers in video streaming services. In VANETs, high-quality video streaming services aim to provide subscribers with safety and various infotainment applications. Due to the dynamic topology and frequent connectivity changes in moving vehicles, video streaming services require elastic and continuous vehicle information updates to present interactive real-time views of nontrivial road scenarios. The QoS and QoE are affected due to obstacles, re-location tracking, network traffic, and bandwidth factors that occur due to mobility problems and significantly influence the ability of vehicles with mobility to provide video streaming services. To achieve high QoS and QoE of video streaming services in VANETs, this paper proposes a novel protocol named PSOstreaming based on a particle swarm optimization (PSO) which is one of the mainstream and nature-inspired algorithms for swarm intelligence (SI). PSOstreaming calculates the PSQ score, which is the scoring method of the node in the topology in terms of the data communication capability measurement to analyze and optimize topology information in real-road circumstances. In addition, PSOstreaming utilizes a 3D vector mobility prediction algorithm for the mobility prediction method for the vehicles to address the characteristics of VANETs. In the topology, PSOstreaming defines Global PSO members and Local PSO members to disseminate video packets for video-streaming services to the service requester by computational equations. Experimental results indicate that PSOstreaming achieves high-quality video streaming services with a flexible response to dynamic topology changes and a high frame delivery ratio in terms of QoS and QoE.