Routing Protocol For Vehicular Networks Research Articles

Performance analysis of routing protocols for vehicular networks

Performance analysis of routing protocols for vehicular networks

Performance Evaluation of Routing Protocols for Vehicle Re-Routing in ITS-based Vehicular Networks

This study aims to assess the performance of routing protocols in Intelligent Transportation System (ITS)-based vehicular networks, specifically in accident and highway scenarios. The effective management of traffic flow in these situations is crucial for ensuring the safety and smooth operation of vehicular networks. Therefore, it is imperative to evaluate routing protocols to identify the most suitable one for these scenarios. The evaluation considers various commonly used routing protocols in vehicular networks, including Ad hoc On-Demand Distance Vector (AODV), Ad hoc On-Demand Multipath Distance Vector (AOMDV), and Destination-Sequenced Distance Vector (DSDV). The evaluation is based on several performance metrics, such as packet delivery ratio, end-to-end delay, network throughput, normalized routing load, and routing overhead. These metrics provide insights into the effectiveness and efficiency of the routing protocols in handling re-routing in accident and highway scenarios. The research is divided into two modules, Module I and Module II, to evaluate the effectiveness of routing protocols in these distinct scenarios using the NS2 simulation tool. The simulation results are analyzed and compared to determine the performance of the routing protocols in each module. The findings indicate that AODV consistently achieves the highest throughput, packet delivery ratio, and lowest end-to-end delay, routing overhead, and normalized routing load, followed by AOMDV and then DSDV. The findings of this study contribute to the understanding of the strengths and weaknesses of different routing protocols in accident and highway scenarios. This knowledge can assist in the development of more efficient and reliable routing protocols for vehicular networks.

Performance analysis of routing protocols for vehicular networks

Performance analysis of routing protocols for vehicular networks

On the prediction of large-scale road-network constrained trajectories

Trajectory data mining-based applications benefit from the increasing availability of vehicle trajectory and road network datasets. For instance, the application of trajectory prediction makes it possible to design more efficient routing protocols for vehicular networks. This paper proposes a novel cluster-based framework for the long-term prediction of road-network constrained trajectories. The framework employs a new hierarchical agglomerative clustering algorithm and trains prediction models from historical trajectory datasets. Experimental results show the framework’s effectiveness and efficiency to predict trajectories with different characteristics in a new real-world, large-scale scenario. Furthermore, the framework outperformed the related work in terms of prediction accuracy and time complexity.

DTMR: An adaptive Distributed Tree-based Multicast Routing protocol for vehicular networks

The modern driver-assistance and autonomous technologies in vehicles increase the ease of driving vehicles. The increased vehicle usage increases the requirement of efficient group communication between the vehicles to support the safety as well as the non-safety applications in Vehicular Ad-hoc NETworks (VANET). In VANET, multicast communication is mostly preferred for the effective utilization of computational resources and the attainment of the Quality of Service (QoS). To implement an efficient multicast communication, we need to build and retain a multicast tree. Due to the high mobility and rapid topology changes, the formation and maintenance of a multicast tree are challenging in VANET. Existing multicast communication techniques are either centralized or location-based flooding and suffer from tree reconfiguration overhead. In this paper, a novel Distributed Tree-based Multicast Routing (DTMR) algorithm is proposed. During the link failure, the connection is switched to a predetermined and highly stable guardian node. Further, the tree fragmentation and the rejoining delay is reduced in VANET using the proposed algorithm, DTMR. From the simulation results, it is evident that the DTMR achieves a significant performance improvement against the existing multicast techniques such as Distributed Time-limited Reliable Broadcast Incremental Power Strategy (DTRBIP) and Energy Efficient Multicast routing protocol based on Software Defined Networks and Fog computing for Vehicular networks (EEMSFV) in terms of delay, packet loss ratio, scalability, and reliability. In terms of end-to-end delay, packet loss rate, and reliability, the DTMR outperforms the existing DTRBIP and EEMSFV protocols. DTMR achieves 94--96% reliability in highway scenarios and 96--99% reliability in urban environments. Further, as a proof of concept, the proposed, DTMR is implemented and analyzed in real-time. It is found that the real-time experimental results are on par with the simulation results. Hence, the proposed DTMR achieves network stability and reliability in real-time.

Improved Road Segment-Based Geographical Routing Protocol for Vehicular Ad-hoc Networks

The real-time traffic information dissemination among on-road vehicles has been envisioned via realizing vehicular ad hoc networks (VANETs) as smart service-oriented roadside wireless sensor networks. The network enables various types of real-time traffic applications related to safety and infotainment for drivers and passengers. The information dissemination-centric routing protocols for vehicular networks have to dynamically adopt under the constrained network environment while considering the higher mobility of vehicular nodes and unpredictable physical topologies in the network. The issue needs to be addressed through smart and network-aware routing protocols. Geographical routing protocols have witnessed significant attention for information dissemination under these types of dynamic vehicular network environment. To this end, this paper presents an improved road segment-based geographical routing (ISR) protocol focusing on better head node selection for information dissemination. It divides the forwarding area into a number of road segments and selects a head node on each segment by focusing on traffic-aware information including the location, direction, and link quality-centric score for every vehicle on each road segment. Algorithms were developed for the complete process of head node selection and information dissemination among vehicles on the road segments. The simulation results attested the performance benefits of the proposed routing framework as compared to the state-of-the-art protocols considering dynamic vehicular traffic environment-related metrics.

Modeling and Solution of the Routing Problem in Vehicular Delay-Tolerant Networks: A Dual, Deep Learning Perspective

The exponential growth of cities has brought important challenges such as waste management, pollution and overpopulation, and the administration of transportation. To mitigate these problems, the idea of the smart city was born, seeking to provide robust solutions integrating sensors and electronics, information technologies, and communication networks. More particularly, to face transportation challenges, intelligent transportation systems are a vital component in this quest, helped by vehicular communication networks, which offer a communication framework for vehicles, road infrastructure, and pedestrians. The extreme conditions of vehicular environments, nonetheless, make communication between nodes that may be moving at very high speeds very difficult to achieve, so non-deterministic approaches are necessary to maximize the chances of packet delivery. In this paper, we address this problem using artificial intelligence from a hybrid perspective, focusing on both the best next message to replicate and the best next hop in its path. Furthermore, we propose a deep learning–based router (DLR+), a router with a prioritized type of message scheduler and a routing algorithm based on deep learning. Simulations done to assess the router performance show important gains in terms of network overhead and hop count, while maintaining an acceptable packet delivery ratio and delivery delays, with respect to other popular routing protocols in vehicular networks.

VANET routing protocol with traffic aware approach

Vehicular ad hoc network (VANET) is a type of mobile ad hoc network (MANET) that forms vehicles as nodes. Routing is the basic fundamental requirement of VANET applications. Therefore, it is necessary to devise a routing protocol that fits well for rapid topology changes and disconnected network conditions. To address these specific needs of VANET, we present a novel greedy routing protocol for vehicular networks called VRPTA that suite well for both city environment and the high way environment. With the help of localisation system named global positioning system (GPS), the proposed protocol is designed to efficiently relay the data in the network by considering different scenarios like road traffic variation and various environment characteristics. The protocol communicates in between vehicles as well as vehicle to infrastructure whichever is applicable, thereby ensuring reliable transmission. In addition, we also consider the information about vehicles speed, direction and density of a city traffic configuration consisting of double direction roads, multi lanes and highway scenario. The work is implemented using NS2 simulator.

A swarm intelligence-based routing protocol for vehicular networks

A swarm intelligence-based routing protocol for vehicular networks

A swarm intelligence-based routing protocol for vehicular networks

Vehicular Ad hoc Networks (VANETs) are a particular case of Mobile Ad hoc Networks (MANETs). They are applied to exchange information among vehicles and between vehicles and a nearby fixed infrastructure. Unlike the MANETs, the VANETs have highly mobile nodes that cause a dynamic topology, a disconnected network, etc. Consequently, these features pose numerous challenges. One of them is routing. In a vehicular environment, the routing protocol needs to cope with events like link failure and to find an effective path to propagate the information toward the desired destination. In this context, we assume in this paper that the vehicles are intelligent and have a knowledge base about their communication environment. Our aim is to carry out the routing of the data based on swarm intelligence. The optimum route is explored using the Particle Swarm Optimisation (PSO). The proposed approach is called the Optimised Agent-based AODV Protocol for VANET (OptA²PV).

Parallel multi-objective metaheuristics for smart communications in vehicular networks

This article analyzes the use of two parallel multi-objective soft computing algorithms to automatically search for high-quality settings of the Ad hoc On Demand Vector routing protocol for vehicular networks. These methods are based on an evolutionary algorithm and on a swarm intelligence approach. The experimental analysis demonstrates that the configurations computed by our optimization algorithms outperform other state-of-the-art optimized ones. In turn, the computational efficiency achieved by all the parallel versions is greater than 87 %. Therefore, the line of work presented in this article represents an efficient framework to improve vehicular communications.

Comparative Study on Non-delay Tolerant Routing Protocols in Vehicular Networks

Vehicular Ad-hoc network is an emerging technique for the Ad-hoc networks and Intelligent Transport System (ITS).VANET is mainly used for avoiding the accident and shares the traffic information among the vehicles. For sharing the information among the vehicles many challenges are faced, because the VANET has dynamic topology and high mobility model. To resolve this problem, VANET has many types of routing methods and various routing protocols, but those routing protocols do not fully resolve the problem during the communication. In this paper we discussed, Position based routing method and Non-delay tolerant routing protocols, its advantages and issues.

Comprehensive analysis of Highway, Manhattan and Freeway mobility models for vehicular ad hoc network

Mobility model of a Vehicular Ad Hoc Network VANET is one of the key determinants for developing routing protocol for vehicular communication. The mobility pattern in the mobility model is used to simulate the movement characteristics of the vehicles, which plays an eminent role for developing an efficient routing protocol for vehicular network. The main role of the mobility model in a VANET is to influence the route discovery mechanism, reconstruction of failure links and caching procedures. This paper describes Highway, Manhattan and Freeway mobility models that represent the mobile vehicles and their movement is completely dependent on other vehicles. This paper also presents the simulation results that illustrate the importance of various routing protocols, cluster schemes and the standard 802.11p. The simulation output demonstrates how the performance of VANET routing protocol changes significantly, when the mobility model is changed.

Analyzing Routing Protocol Performance with NCTUns for Vehicular Networks

Vehicular networks are an emerging field of study that brings many new features to support road transportation. In this paper, we evaluate the performance of three well-known routing protocols in vehicular networks, using NCTUns, a popular network simulator. We study those protocols by changing different metrics such as node mobility, number of vehicles, traffic pattern, and number of RSUs. We also report the total elapsed time for simulations and memory consumption with the aim of guiding researchers in their selection of an adequate routing protocol for large simulation scenarios using NCTUns in vehicular networks.

Analyzing Routing Protocol Performance with Nctuns for Vehicular Networks

Vehicular networks are an emerging field of study that brings many new features to support road transportation. In this paper, we evaluate the performance of three well-known routing protocols in vehicular networks, using NCTUns, a popular network simulator. We study those protocols by changing different metrics such as node mobility, number of vehicles, traffic pattern, and number of RSUs. We also report the total elapsed time for simulations and memory consumption with the aim of guiding researchers in their selection of an adequate routing protocol for large simulation scenarios using NCTUns in vehicular networks.

Social Contribution-Based Routing Protocol for Vehicular Network with Selfish Nodes

Routing in vehicular network is a challenging task due to the characteristic of intermittent connectivity, especially when nodes behave selfishly in the real world. Previous works usually assume that all nodes in the network are willing to forward packets for others, which is impractical in real world. Selfish behaviors of nodes would degrade network performance greatly. In this paper, we propose SCR, a social contribution-based routing protocol, for selfish vehicular network. When making forwarding decision, SCR considers both the delivery probability to the destination and the social contributions of the relay node. The delivery probability is determined by the social relations among nodes and social contribution is used as the incentive to stimulate selfish nodes to be more cooperative, which consists of reciprocal contribution and community contribution. The node with higher delivery probability and lower social contributions is the preferred candidate for the next hop. Simulation results show that SCR achieves better performance than other social routing protocols with the incentive scheme.

Performance Evaluation of Routing Protocols in Vehicular Networks

Vehicular Ad hoc Networks is pro mising research area to imp rove traffic safety by developing an intelligent inter-vehicle co mmunicat ion system. Routing of data in a vehicular ad hoc network is a challenging task due to the high dynamics of such a network. This paper presents a performance study of routing protocols in various network environment (Urban, Highway) based on metrics such as throughput, packet delivery ratio and average end-to-end delay. For the imp lementation purpose we have used network simulator-2 (NS-2) and VanetMobisim.

On adaptive routing in urban vehicular networks

Efficient data delivery in vehicular networks has received increasing attention in recent years. Existing routing protocols for vehicular networks can be loosely divided into two classes: road based routing (RBR) and road oblivious routing (ROR). RBR finds a routing path along roads while ROR does not explicitly forward packets along roads. We have the observation that using either of an RBR algorithm or an ROR algorithm alone in a realistic vehicular network setting leads to deficiency. This results from the fact that network conditions can be different at different locations and evolving over time. Motivated by this observation, this paper proposes an adaptive routing algorithm called RWR that adapts its routing strategy to network dynamics as the packet travels from the source to the destination. Extensive simulations based on a large dataset of real vehicular traces collected from around 2,600 taxis in Shanghai have been conducted. Comparison study shows that RWR produces higher delivery ratio than TSF and GPCR, representative routing algorithms of RBR and ROR, respectively. It achieves low delivery delay at the same time.

Fast energy-aware OLSR routing in VANETs by means of a parallel evolutionary algorithm

This work tackles the problem of reducing the power consumption of the OLSR routing protocol in vehicular networks. Nowadays, energy-aware and green communication protocols are important research topics, specially when deploying wireless mobile networks. This article introduces a fast automatic methodology to search for energy-efficient OLSR configurations by using a parallel evolutionary algorithm. The experimental analysis demonstrates that significant improvements over the standard configuration can be attained in terms of power consumption, with no noteworthy loss in the QoS.

Seamless Connectivity and Routing in Vehicular Networks with Infrastructure

The provision of UDP-based multimedia streams to vehicular users through a roadside wireless mesh network requires a fast-switching, robust protocol architecture. We consider vehicles (e.g., cars, buses or streetcars) that connect to different roadside mesh nodes as they move in an urban environment, and study the joint problem of traffic delivery and connectivity management in such scenario. We identify BATMAN as a candidate layer-2 implementation of a routing protocol for vehicular networks, and we use simulation to compare its performance with other routing protocols for wireless ad hoc and mesh networks. Since BATMAN shows some inconsistencies in its behavior, we propose an improved version of the protocol, named smart-window BATMAN (sw-BATMAN). Then, we design two testbeds that include both roadside and vehicular mesh nodes. There, we implement the selected routing solution along with a handover mechanism that, by leveraging a channel selection scheme, allows vehicles to connect to the different roadside mesh nodes in a seamless manner. The performance assessment on our testbeds shows the efficiency of the proposed solution and highlights that our traffic routing and connectivity management are suitable for sustaining the handover of UDP streams in a vehicular environment, in a seamless manner.