Routing In Vehicular Networks Research Articles

A deep reinforcement learning-based intelligent QoS optimization algorithm for efficient routing in vehicular networks

With the rapid development of Telematics, Vehicle Self-Organizing Networks (VANETs) play an increasingly critical role in Intelligent Transportation Systems (ITS). Especially in the environment without roadside assistance units (RSUs), how to effectively manage inter-vehicle communication and improve the stability and communication efficiency of the network has become a hot topic of current research. In this paper, a Deep Reinforcement Learning-based Intelligent QoS-optimized efficient routing algorithm for vehicular networks (DRLIQ) is proposed for VANETs with/without RSU environments, and routing methods are proposed respectively. Among them, in RSU-free environment, the DRLIQ algorithm utilizes the powerful processing capability of deep reinforcement learning to intelligently select the optimal data transmission path by dynamically learning and adapting to the changes in the vehicular network, thus effectively reducing communication interruptions and delays, and improving the accuracy of data transmission. The performance of the DRLIQ algorithm under different vehicle densities is evaluated in simulation experiments and compared with current popular algorithms. The experimental results show that the DRLIQ algorithm outperforms the comparison algorithms in reducing the number of communication interruptions, BER and network delay, especially in vehicle-dense environments. In addition, the DRLIQ algorithm shows higher adaptability and stability in coping with network topology changes and vehicle dynamics.

CDSPAN: A Collaborative Distributed SPANner backbone for multiple source multicast routing in vehicular network

CDSPAN: A Collaborative Distributed SPANner backbone for multiple source multicast routing in vehicular network

TrajData: On Vehicle Trajectory Collection With Commodity Plug-and-Play OBU Devices

For years, vehicle trajectory data have increasingly been important for a wide range of applications, from driver behavior investigation/classification, travel time/distance estimation, and routing in vehicular networks, to vehicle energy/emission evaluation. This article presents TrajData, the first systematic solution to reliable vehicle trajectory data collection, with only reliance on commercial-off-the-shelf (COTS) onboard unit (OBU) devices that utilize lightweight GPS modules and low-cost onboard diagnostics (OBD) readers. In the practical use of trajectory collection, GPS outages inevitably occur in urban environments thereby leading to large trajectory errors as well as missing vehicle location data. To resolve this, we propose a novel data-fusion-enabled deep learning approach with the purpose of achieving reliable vehicle trajectory collection in various urban road conditions. Specifically, we leverage motion information retrieved from OBD readers in TrajData to help reconstruct the trajectory data during GPS outages. By investigating the changes of direction angle from the OBD readings, we can identify different types of road sections. Furthermore, we integrate the neural arithmetic logic units (NALUs) into our trajectory reconstruction model to tame the challenges when GPS outages take place in various road sections. Experimental results from realistic data have demonstrated the effectiveness and reliability of the proposed method. In the road test, TrajData achieves an average position error below 15-m around a 60-s GPS outage, even in complex road sections, i.e., continuous turns and driving with accelerations/decelerations resulting in frequent changes of direction and speed.

Modeling Geographical Anycasting Routing in Vehicular Networks

Vehicular network is one of the most important subjects for researchers in recent years. Anycast routing protocols have many applications in vehicular ad hoc networks. The aim of an anycast protocol is sending packets to at least one of the receivers among candidate receivers. Studies done on anycast protocols over vehicular networks, however, have capability of implementation on some applications; they are partial, and application specific. No need to say that the lack of a comprehensive study, having a strong analytical background, is felt. Mathematical modeling in vehicular networks is difficult because the topology of these networks is dynamic. In this paper, it has been demonstrated that vehicular networks can be modeled based on time-expanded networks. The focus of this article is on geographical anycast. Three different scenarios were proposed including sending geographic anycast packet to exactly-one-destination, to at-least-one-destination, and to K-anycast destination, which can cover important applications of geographical anycast routing protocols. As the proposed model is of MILP type, a decentralized heuristic algorithm was presented. The evaluation process of this study includes the production of numerical results by Branch and Bound algorithm in general algebraic modeling system (GAMS) software and simulation of the proposed protocol in OMNET++ simulator. The comprehension of the result of proposed protocol and model shows that the applicability of this proposed protocol and its reactive conformity with the presented models based on presented metrics.

An effect of big data technology with ant colony optimization based routing in vehicular ad hoc networks: Towards smart cities

Rapid growth in urban population creates various kinds of issues like long hours traffic-jams, pollution which makes the city life insecure and non-liveable. The concept of a smart city is introduced to improve the quality of city life. Smart cities are being developed to satisfy the need for the safety of its users’ and secure journeys over in the urban scenario by proposing the smart mobility concept. At the same time, Vehicular adhoc network (VANET) comes under the type of mobile adhoc network (MANET), wherever the vehicles are treated as nodes in a network. The application of Big Data technologies to VANET gains useful insight from the massive quantity of operational data to enhance traffic management process like planning, engineering as well as operation. During the real-time processes, the VANET generates large data, and the VANET characteristics are mapped to Big Data attributes. Moreover, ant colony optimization (ACO) algorithm is employed for routing in vehicular networks over Hadoop Map Reduce standalone distributed framework and over multi-node cluster with 2, 3, 4 and 5 nodes. The simulation outcomes ensure that the processing time of the algorithm is significant decreases with a rise in the node count of the Hadoop framework.

Energy-efficient multicast routing protocol based on SDN and fog computing for vehicular networks

Vehicular networks have been expanding significantly to perform several applications and strategies related to vehicles, ambulances, traffic jam, drivers, and even passengers. The most important challenge in this network is routing data among vehicles. Therefore, there is a need to design efficient routing protocols for unicast, Geocast, multicast and broadcast transmission modes. The multicasting can be used in many application fields such as emergency, police, and firefighting. There is a large body of studies on multicast routing in vehicular networks. However, safety applications in vehicular networks require a special multicast routing protocol that takes into account the deadline and existing bandwidth constraints. On the other hand, there has been a growing tendency towards electric cars in recent years. Therefore, energy consumption is one of major parameters that should be considered in the design of this routing protocol. The goal of this paper is to present a new Energy Efficient Multicast routing protocol based on Software Defined Networks and Fog computing for Vehicular networks called EEMSFV including deadline and bandwidth constraints. Multicast routing with multiple constraints of QoS has been proved to be a NP complete problem. The proposed architecture consists of four layers: vehicles, fog computing, OpenFlow switches and SDN controller. Moreover, a priority based scheduling algorithm and a classification algorithm to schedule the multicast requests based on their application type and deadline constraint after classifying them are proposed. The partitioning concept is used to decrease time complexity and overhead in the SDN controller. From the simulation results, we concluded that EEMSFV is better than MABC and CVLMS in terms of successfully transmitted ratio, average end to end delay, normalized overhead load, multicast energy consumption, packet loss ratio and percentage of critical multicast sessions that meet the deadline.

Performance evaluation and comparative study of main VDTN routing protocols under small- and large-scale scenarios

This paper presents a performance evaluation through simulations and a comparative study of main routing protocols dedicated to Vehicular Delay-Tolerant Networks. The assessment is conducted under small- and large-scale scenarios with realistic vehicle mobility patterns as defined in the TAPAS Cologne simulation scenario. Through the literature, several evaluations have been conducted on routing for Vehicular Networks, but with an abstraction or a simplification regarding the delay tolerant aspect. Furthermore, considered scenarios were relatively small and too idealistic compared to the real-world environment and its multiples challenges. Moreover, to the best of our knowledge, this is the first extensive study that compares, in the same realistic simulation environment, the main flag-carriers of various categories of VDTN routing protocols, namely Epidemic, Direct Delivery, Prophet and GeoSpray protocols. Simulation results reveal better performance for the geographical approach advocated by GeoSpray compared to the predictive one of Prophet, under all considered scenarios. Moreover, they highlight the possibility for a minimalist and naive protocol such as Direct Delivery to perform well, under specific network conditions, as when considering an anycast communication scheme. Finally, deeper analysis was undertaken on both GeoSpray and Prophet. The studies reveal the potentialities to increase the performances of GeoSpray to some extent and highlight the difficulties of adapting Prophet settings for optimal performance in realistic scenarios.

Network condition and application‐based data adaptive intelligent message routing in vehicular network

SummaryRecent advances in intelligent transportation systems enable a broad range of potential applications that significantly improve the vehicle and road safety and facilitate the efficient dissemination of information among the vehicles. To assist the vehicle traffic, message broadcasting is a widely adopted technique for road safety. But efficient message broadcasting is a significant issue, especially in a high network density due to the broadcast storm problem. To solve this issue, several methods are proposed to eliminate the redundant transmission of safety packets. However, they lack in restricting the broadcasting region of safety messages, and the transmissions of safety packets outside the dangerous region, and force the vehicles to unnecessary detours. This paper proposes an adaptive multimode routing protocol, network condition, and application‐based data adaptive intelligent message routing in vehicular network (NetCLEVER) that supports 2 modes of operation such as message broadcasting and intelligent routing. In message broadcasting mode, the NetCLEVER decides the dangerous region of the network by considering the changes of neighbor vehicles velocity, instead of current vehicle velocity, because a vehicle decision in velocity is interdependent with the preceding vehicles. In intelligent routing mode, the NetCLEVER exploits the cuckoo search optimization in routing by taking into account multiple routing factors such as the road topology of intersections and traffic signals and their impact on link stability, which improves the reliability of routing packets significantly. The performance evaluation illustrates that the proposed NetCLEVER improves reliable wireless communication as well as road safety in vehicular ad hoc networks.

A Comprehensive Survey of Location Based Routing in Vehicular Networks

A Comprehensive Survey of Location Based Routing in Vehicular Networks

On Stochastic Analysis of Greedy Routing in Vehicular Networks

Even the greedy routing is widely used in wireless networks, its theoretical study is still limited in vehicle environments. In this paper, we theoretically analyze the performance of the greedy routing under three typical vehicle scenarios, i.e., the single-lane road, the multilane road, and the multilevel road. We first propose the analytical model by analyzing characteristics of traffic environments, which contain the width and multilevel features of roads. Specifically, we prove that the road-width is ignorable under certain conditions, whereas the data measured in an outdoor experiment reveal that the multilevel feature is non-ignorable because its existence dramatically degrades the transmission range. Based on the model, we analyze the routing length of the greedy routing for all scenarios in the following three aspects. 1) We derive the distribution function for the first one-hop progress. 2) We prove that routing increments are history-dependent and give one sufficient condition that ensures these increments are approximately i.i.d. 3) We calculate the routing length described by the $h$ -hop coverage and hop count using the renewal theory. Finally, simulations are conducted to verify the accuracy of our analysis.

Performance Study of Economical and Environmentally Friendly Geocast Routing in Vehicular Networks

Economical and environmentally friendly geocast (EEFG) uses traffic signals to communicate with approaching vehicles. The communication can be signal-to-vehicle (TLS2V) and vehicle-to-vehicle (V2V). Based on the information sent, the vehicle receiving the message adapts its speed to a recommended speed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="TeX">$(S_{R} ) $</tex-math></inline-formula> , which helps the vehicle reduce fuel consumption and emissions. Our previous paper entitled “Optimization of Fuel Cost and Emissions Using V2V Communications” develops a model to determine the optimum <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="TeX">$S_{R} $</tex-math></inline-formula> . It also proposes heuristic expressions to compute the optimum or near-optimum <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="TeX">$S_{R}$</tex-math></inline-formula> .

An evaluation of routing in vehicular networks using analytic hierarchy process

AbstractThis paper presents a comprehensive study of the performance of routing protocols in distributed vehicular networks. We propose a novel and efficient routing protocol, namely cross‐layer, weighted, position‐based routing, which considers link quality, mobility and utilisation of nodes in a cross layer manner to make effective position‐based forwarding decisions. An analytic hierarchy process approach is utilised to combine multiple decision criteria into a single weighting function and to perform a comparative evaluation of the effects of aforementioned criteria on forwarding decisions. Comprehensive simulations are performed in realistic representative urban scenarios with synthetic and real traffic. Insights on the effect of different communication and mobility parameters are obtained. The results demonstrate that the proposed protocol outperforms existing routing protocols for vehicular ad hoc networks, including European Telecommunications Standards Institute (ETSI's) proposed greedy routing protocol, greedy traffic aware routing protocol and advanced greedy forwarding in terms of combined packet delivery ratio, end‐to‐end delay and overhead. Copyright © 2015 John Wiley &amp; Sons, Ltd.

Metaheuristics for energy-efficient data routing in vehicular networks

Vehicular ad hoc networks provide a unique platform for information exchange between road users drivers and pedestrians and roadside infrastructure elements. The very necessary attempt to reduce global energy consumption and CO

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.

On efficient replication-based routing in vehicular networks

Efficient routing in vehicular networks is one of the most challenging problems because of frequent network disruption and fast topological change. Some replication-based routing protocols such as epidemic routing have been proposed. However, these existing replication-based routing protocols cannot achieve high delivery ratio, low end-to-end delay and low delivery cost. In this paper, we design an efficient replication-based routing protocol called ERR for efficient routing in vehicular networks. ERR is a fully distributed protocol, and it has the following three desirable design objectives: first, ERR delivers the majority of the messages generated in time-to-live; second, ERR achieves low end-to-end delay; third, ERR introduces as little delivery cost as possible. To achieve these design objectives, ERR adopts an adaptive strategy for the number of copies of a message in a distributed fashion. In addition, we propose two forwarding rules for a message carrier with some copies to decide whether it should forward the message when it meets a vehicle. Based on real traces of vehicles, we have conducted real trace-driven simulations. Performance results demonstrate that ERR can increase delivery ratio, decrease end-to-end delay, and decrease delivery cost, when compared with four other alternative protocols.

Performance of new Load Balancing protocol for VANET using AODV [LBV_AODV

Adhoc network has gained popular attention in last few years due to the provision of safety and comfort related applications.VANETs are direct offshoot of MANETs but with unique characteristics like high speed, dynamic changing topology and difficult communication environment. Due to these unique features ,routing in vehicular network has always been a challenging issue but besides efficient routing very less attention is being paid in the area of load balancing. So in this study, load optimization/management in VANET is focused and a new protocol is introduced with new metric i.e. local delay which uses interface queue length. The new protocol is an extension of conventional AODV and it is modified according to VANET parameters. The protocol is simulated on Ns2.34 and the performance analysis shows that the new protocol is better than AODV in terms of PDR and EED.

An evaluation of vehicular networks with real vehicular GPS traces

Vehicular networks have attracted increasing attention from both the academy and industry. Applications of vehicular networks require efficient data communications between vehicles, whose performance is concerned with delivery ratio, delivery delay, and routing cost. The most previous work of routing in vehicular networks assumes oversimplified node mobility when evaluating the performance of vehicular networks, e.g., random mobility or artificial movement traces, which fails to reflect the inherent complexity of real vehicular networks. To understand the achievable performance of vehicular networks under real and complex environments, we first comprehensively analyze the affecting factors that may influence the performance of vehicular networks and then introduce four representative routing algorithms of vehicular networks, i.e., Epidemic, AODV, GPSR, and MaxProp. Next, we develop an NS-2 simulation framework incorporating a large dataset of real taxi GPS traces collected from around 2,600 taxis in Shanghai, China. With this framework, we have implemented the four routing protocols. Extensive trace-driven simulations have been performed to explore the achievable performance of real vehicular networks. The impact of the controllable affecting factors is investigated, such as number of nodes, traffic load, packet TTL, transmission range, and propagation model. Simulation results show that a real vehicular network has surprisingly poor data delivery performance under a wide range of network configurations for all the routing protocols. This strongly suggests that the challenging characteristics of vehicular networks, such as unique node mobility, constraints of road topology, need further exploration.

Spatio-temporal multicast grouping for content-based routing in vehicular networks: A distributed approach

Efficient dissemination of vehicular network applications is still a challenging objective in the area of research. Their unique characteristics impose difficulties in proposing a framework to solve the dissemination related problems. Event broker middleware provides asynchronous communication and extensive messaging in heterogeneous environments. This can be integrated with multicast routing in vehicular networks for efficient dissemination. Proposed approach aggregates content-based subscriptions in a compact data format using Binary Decision Diagram and applies Spatio-temporal Multicast Routing Protocol to extend this context from the middleware-tier to construct an optimized dynamic dissemination mesh. The dynamic multicast group is created by aggregating subscriptions, applying clustering. This work has compared the performance of K-Means and hierarchical clustering methods for clustering subscriptions to form multicast groups. Cooperation between middleware-tier and network components allows to represent fine-grained subscriptions. Simulation results support the efficiency of the proposed approach.

Position-based routing in vehicular networks: A survey

Routing in vehicular network is a challenging task due to network partitioning, high vehicular speed, and city environment characteristics. These characteristics results in degraded performance in traditional routing protocols. Traditional routing protocols, addressing the issues of mobile ad hoc network, are applicable for MANET applications. Position-based routing protocols, which are mostly based on greedy routing, are more suited to highly dynamic and mobile network. In this paper, we survey state of art routing protocols previously used in vehicular networks, present open research challenges and possible future direction. We categorize protocols into two categories based on their communicating mode (vehicle-to-vehicle, vehicle-to-infrastructure) irrespective of their simulating environment (highway, urban). Both vehicle-to-vehicle and vehicle-to-infrastructure communication provides connectivity based on multi-hop paradigm in a seamless way. We discuss pros and cons for routing protocols belonging to each category. By doing qualitative comparison of routing protocols, it is observed that hybrid communication would be the better choice for both communication mode operable in either a city environment or an open environment.

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.