Implementation of GPSR protocol with various mobility models in VANET Scenario

Abstract

In Vehicular Ad hoc Networks (VANET), topology varies very frequently because vehicles move in high speed. VANET is deployed on road. In GPSR Protocol, as the data packets are forwarded depending upon on the beacon information sent by neighboring nodes, which contain the location of neighbors. Hence nodes move in mobile nature as they change their positions. Mobile pattern of node is reflected by Mobility Models, as they characterize the movement of users who are mobile on the road, with respect to their direction, velocity and location over a period of time. Mobility models are practiced in implementation of protocols and the pattern by which the mobility models reflect real world practices of vehicles on the roads. Using simple pattern randomly, graph constrained mobility models are common practices while doing research. These models donot describe mobility of vehicles in realistic manner. For instance while accelerating and decelerating in the presence of nearby vehicles, these situations greatly affect the Network performance. Selecting the mobility model which is realistic one is the main focus of this paper. To address the challenges such as high mobility of vehicle nodes on the road and random topology, VANET needs a suitable mobility model to obtain improved Packet Delivery Ratio, Throughput, End to End Delay etc. This paper first implements the GPSR Protocol and then GPSR is analyzed by applying different mobility models such as Random Way Point, Gauss Markov, Manhattan Grid, Reference Point Group and Random direction. Results are analyzed by taking the following parameters: Routing overhead, Throughput, PDR and End to End Delivery. The implementation is carried out using NS—2.35 and Bonmotion is used to create mobility models.

A Deep-Learning-Based Secure Routing Protocol to Avoid Blackhole Attacks in VANETs

“…We specifically deploy 30, 50, and 100 nodes moving throughout 1000 m 2 × 1000 m 2 area in an urban scenario. Additionally, we compare two different mobility models, namely, the RPGM model [39,40] and the RWP model [41], to evaluate their performance in VANETs. The RPGM model represents a scenario where vehicles move cohesively in groups, following similar trajectories and maintaining relative proximity to each other.…”

“…The purpose of this comparison is to understand how the choice of mobility model impacts various performance metrics. The mobile nodes' initial positions are randomly distributed along the street, and they move at different speeds (20,40,60, and 80 km/h). Each mobile node has an omnidirectional antenna, and the node's maximum transmission range is set to 250 m (approximately).…”