Geographic routing is one of the most investigated themes by researchers for reliable and efficient dissemination of information in Vehicular Ad Hoc Networks (VANETs). Recently, different Geographic Distance Routing (GEDIR) protocols have been suggested in the literature. These protocols focus on reducing the forwarding region towards destination to select the Next Hop Vehicles (NHV). Most of these protocols suffer from the problem of elevated one-hop link disconnection, high end-to-end delay and low throughput even at normal vehicle speed in high vehicle density environment. This paper proposes a Geographic Distance Routing protocol based on Segment vehicle, Link quality and Degree of connectivity (SLD-GEDIR). The protocol selects a reliable NHV using the criteria segment vehicles, one-hop link quality and degree of connectivity. The proposed protocol has been simulated in NS-2 and its performance has been compared with the state-of-the-art protocols: P-GEDIR, J-GEDIR and V-GEDIR. The empirical results clearly reveal that SLD-GEDIR has lower link disconnection and end-to-end delay, and higher throughput as compared to the state-of-the-art protocols. It should be noted that the performance of the proposed protocol is preserved irrespective of vehicle density and speed.

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A multiobjective dynamic vehicle routing problem (M-DVRP) has been identified and a time seed based solution using particle swarm optimization (TS-PSO) for M-DVRP has been proposed. M-DVRP considers five objectives, namely, geographical ranking of the request, customer ranking, service time, expected reachability time, and satisfaction level of the customers. The multiobjective function of M-DVRP has four components, namely, number of vehicles, expected reachability time, and profit and satisfaction level. Three constraints of the objective function are vehicle, capacity, and reachability. In TS-PSO, first of all, the problem is partitioned into smaller size DVRPs. Secondly, the time horizon of each smaller size DVRP is divided into time seeds and the problem is solved in each time seed using particle swarm optimization. The proposed solution has been simulated in ns-2 considering real road network of New Delhi, India, and results are compared with those obtained from genetic algorithm (GA) simulations. The comparison confirms that TS-PSO optimizes the multiobjective function of the identified problem better than what is offered by GA solution.

Location verification has witnessed significant attention in vehicular communication due to the growth in number of location based Intelligent Transport System (ITS) applications. The Traditional cryptography based techniques have been suggested to secure and verify location of vehicles. The traditional techniques increase protocol complexity and computational overhead due to the adhoc nature of vehicular network environments. In this context, this paper proposes two layered Location Information Verification cum Security (LIVES) technique based on Transferable Belief Model (TBM). In layer 1, Tiles based Verification (TV) is performed using the concepts of virtual tiles on roads and received signal strength. In layer 2, TBM based verification is performed. Specifically, the belief of the presence of a vehicle on each tiles, and the belief of the presence of a vehicle as neighbour of other neighbouring vehicles are combined as collective belief to attest the location claim of a neighbour vehicle. The performance of LIVES is evaluated with roadbased and map-based network environments. The single, mixed and multiple adversary vehicles are considered in both the network environments. The comparative performance evaluations attest the benefits of LIVES as compared to the Verification and Inference of Position using Anonymous beaconing (A-VIP) and without using LIVES (W-LIVES).