Experimental Design of Effective QoS Performance Using Advanced Shortest Path Algorithm for Vehicular Ad-Hoc Network

Vehicle Ad-hoc Network (VANET) is the emerging technology and maximum of the intelligent transportations are connected with the VANETs applications. The major goal of the VANETs network is providing road safety and congestion free communication among the vehicles. Due to high-speed mobility among the vehicles, certain issues are occurred during data transmission like network delay, overhead and high-power consumption. It becomes extremely important to create an optimal path to transfer the information or data packet from one place to another. For that reason, in this paper Effective QoS Performance using Advanced Shortest Path Algorithm (EQAS) is proposed which is the combination of Ant based optimization and game theory-based optimization. In this model the optimal is performed in two levels which are initial path selection and best solution finding among the vehicles. At the primary level using the ants the initial possible paths are identified. Secondly to find the best among those selected path the idea of game theory is utilized. Using this process the network quality of service (QoS) performance is increased. The proposed EQAS method is experimented in NS2 and SUMO. From the simulation demonstration and results discussion, it gets proven that the proposed EQAS attained 4% higher packet delivery ratio, 50 ms lower delay, 100 packets lower routing overhead and 20% higher energy efficiency.