Traffic Aware Routing Protocol Research Articles

Multiple-Junction-Based Traffic-Aware Routing Protocol Using ACO Algorithm in Urban Vehicular Networks.

The burgeoning interest in intelligent transportation systems (ITS) and the widespread adoption of in-vehicle amenities like infotainment have spurred a heightened fascination with vehicular ad-hoc networks (VANETs). Multi-hop routing protocols are pivotal in actualizing these in-vehicle services, such as infotainment, wirelessly. This study presents a novel protocol called multiple junction-based traffic-aware routing (MJTAR) for VANET vehicles operating in urban environments. MJTAR represents an advancement over the improved greedy traffic-aware routing (GyTAR) protocol. MJTAR introduces a distributed mechanism capable of recognizing vehicle traffic and computing curve metric distances based on two-hop junctions. Additionally, it employs a technique to dynamically select the most optimal multiple junctions between source and destination using the ant colony optimization (ACO) algorithm. We implemented the proposed protocol using the network simulator 3 (NS-3) and simulation of urban mobility (SUMO) simulators and conducted performance evaluations by comparing it with GSR and GyTAR. Our evaluation demonstrates that the proposed protocol surpasses GSR and GyTAR by over 20% in terms of packet delivery ratio, with the end-to-end delay reduced to less than 1.3 s on average.

BETA: Beacon-Based Traffic-Aware Routing in Vehicular Ad Hoc Networks

Data transmission in Vehicular Ad Hoc Networks (VANETs) often suffers from routing interruptions due to the unstable communication links between vehicles. Over the past decades, many traffic-aware routing protocols have been proposed to alleviate routing interruptions by sensing traffic conditions. However, in most traffic-aware routing protocols, vehicles must transmit a large number of control packets to accumulate traffic information, which may degrade network performance due to the resulting intense competition over the wireless medium. Instead of using control packets, we propose to leverage the beacon mechanism that has been widely used in VANETs to realize traffic awareness. Vehicles broadcast beacons to exchange necessary information with their neighbors periodically. We can leverage this information exchange process among vehicles to replace control packets. To realize this idea, first, a mathematical analysis is provided to demonstrate its feasibility. Then, we propose a concrete protocol to address the technical challenges of using beacons. Extensive simulation results show that our protocol performs better than the state-of-the-art counterparts regarding packet delivery ratio, average delivery time, and network overhead.

An Optimisation driven Deep Residual Network for Sybil attack detection with reputation and trust-based misbehaviour detection in VANET

ABSTRACT Vehicular Ad hoc Network (VANET) has recently gained significant attention as a means of enhancing the mobility, efficiency, and safety of applications in the intelligent transportation system. However, because of its high-speed mobility, wireless connectivity, and extensive node coverage, security is a more difficult procedure. The Sybil security threat on VANET is a growing problem today. The Road Side Unit (RSU) failed to synchronise its clock with the legal vehicle, then unplanned vehicles are predicted, thereby incorrect messages are transferred to them. In this paper, Competitive Dolphin Echolocation Optimisation (CDEO)-based Deep Residual Network is proposed for Sybil attack and RSU misbehaviour detection. Here, the effective routing process is performed using Fractional Glow-Worm Swarm Optimisation (FGWSO)-based traffic-aware routing protocol. In the base station, the Sybil attack detection is done. The Sybil attack detection process is done using a Deep residual network, which is trained by the proposed CDEO algorithm. The CDEO algorithm is devised by incorporating Dolphin Echolocation Optimisation (DEO) technique and Competitive Swarm Optimiser (CSO). Additionally, using the Deep residual network, the RSU misbehaviour detection is done. The performance of the developed method is compared with certain performance metrics, like precision, F1-measure, and recall of 0.9197, 0.9121, and 0.9046.

A novel cloud-based traffic aware data routing protocol for smart connected vehicles

A novel cloud-based traffic aware data routing protocol for smart connected vehicles

Retracted: A smart transportation system in VANET based on vehicle geographical tracking and balanced routing protocol

SummaryIn present scenario, Vehicular Ad‐hoc Network (VANET) has obtained extensive attention because of its unique characteristics that handle high mobility of vehicles, reaping topological changes and frequent route breakages or failures. Hence, for providing smart transportation with enhanced traffic regulation and safety, a new position‐based routing protocol called Traffic Dynamism‐Balanced Routing Protocol (TDBRP) for VANET has been proposed in this paper. Moreover, the work concerns the instantaneous scenario of urban cities with the bidirectional and multilane roads. Efficient junction selection algorithm (EJSA) has been incorporated based on the traffic dynamism for establishing optimal route paths between nodes, hence, forwarding the data packets efficiently. Furthermore, the novel EJSP and the route framing between junctions are established on the basis of information gained from two‐hop neighbors, which tends to reduce end‐to‐end delay and enhances packet delivery ratio (PDR). The TDBRP has been implemented and evaluated in Network Simulator (NS 2.34). And the results are examined and compared with some existing protocols like Geographic Source Routing (GSR), Enhanced Greedy Traffic Aware Routing protocol (E‐GyTAR), and Anchor‐based Street and Traffic‐Aware Routing (A‐STAR). The outcomes outperform the existing works by minimizing the routing overhead and end‐to‐end delay by an average of 16% and 13%, respectively, and increase the PDR value by an average of 25% than others. The proposed protocol also evidences that the two‐hop neighbor information‐based packet forwarding provides better result and efficient routing than neighbor information.

RSU-Assisted Traffic-Aware Routing Based on Reinforcement Learning for Urban Vanets

In urban vehicular ad hoc networks (VANETs), the high mobility of vehicles along street roads poses daunting challenges to routing protocols and has a great impact on network performance. In addition, the frequent network partition caused by an uneven distribution of vehicles in an urban environment further places higher requirements on the routing protocols in VANETs. More importantly, the high vehicle density during the traffic peak hours and a variety of natural obstacles, such as tall buildings, other vehicles and trees, greatly increase the difficulty of protocol design for high quality communications. Considering these issues, in this paper, we introduce a novel routing protocol for urban VANETs called RSU-assisted Q-learning-based Traffic-Aware Routing (QTAR). Combining the advantages of geographic routing with the static road map information, QTAR learns the road segment traffic information based on the Q-learning algorithm. In QTAR, a routing path consists of multiple dynamically selected high reliability connection road segments that enable packets to reach their destination effectively. For packet forwarding within a road segment, distributed V2V Q-learning (Q-learning occurs between vehicles) integrated with QGGF (Q-greedy geographical forwarding) is adopted to reduce delivery delay and the effect of fast vehicle movements on path sensitivity, while distributed R2R Q-learning (Q-learning occurs between RSU units) is designed for packet forwarding at each intermediate intersection. In the case of a local optimum occurring in QGGF, SCF (store-carry-forward) is used to reduce the possibility of packet loss. Detailed simulation experimental results demonstrate that QTAR outperforms the existing traffic-aware routing protocols, in terms of 7.9% and 16.38% higher average packet delivery ratios than those of reliable traffic-aware routing (RTAR) and greedy traffic-aware routing (GyTAR) in high vehicular density scenarios and 30.96% and 46.19% lower average end-to-end delays with respect to RTAR and GyTAR in low vehicular density scenarios, respectively.

An Efficient Greedy Traffic Aware Routing Scheme for Internet of Vehicles

A new paradigm of VANET has emerged in recent years: Internet of Vehicles (IoV). These networks are formed on the roads and streets between travellers who have relationships, interactions and common social interests. Users of these networks exchange information of common interest, for example, traffic jams and dangers on the way. They can also exchange files such as multimedia files. IoV is considered as part of the Internet of Things (IoT) where objects are vehicles, which can create a multitude of services dedicated to the intelligent transportation system. The interest is to permit to all connected vehicles to communicate with each other and/or with a central server, through other vehicles. Vehicle to Vehicle (V2V) communication is the main component, because the services encompassed in the IoV are based on the vehicles in question, such as transmitter, relay and receiver. This work is focusing on designing and developing a Quality of Service (QoS) routing scheme dedicated to IoV networks. Especially, we aim to improve the Greedy Traffic Aware Routing (GyTAR) protocol to support QoS in IoV networks. To evaluate the proposed approach in terms of QoS in the context of IoV networks, the performance metrics such as average end-to-end delay and packet delivery ratio are taken into consideration to analyse the network situation.

PTCCR: A Path Transmission Costs-Based Multi-Lane Connectivity Routing Protocol for Urban Internet of Vehicles

In Internet of Vehicles (IoV), high vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, variation of network topology and constraints for routing protocols. Besides, with vehicular positions and street-level digital maps available, the intersection-based geographic routing becomes indispensable considering its ability for avoid forwarding packets through segments with low network density and high scale of network disconnections. In this paper, considering the benefits of intersection-based routing and challenges of high dynamic IoV, a Path Transmission Costs-based Multi-lane Connectivity Routing protocol (PTCCR) is proposed with the help from intersection nodes and/or neighboring nodes. First, we investigate the multi-lane connectivity based on vehicular speed under free-flow state for various types of road sections. Second, A Path Transmission costs (PTC) measurement mechanism is proposed considering the impact of the sequence of selected sections or intersections on the routing performance. After that, the PTC of sent packets is quantitatively analyzed and used as the path selection metric. Finally, the path with the largest multi-lane connectivity and lowest PTC is selected as the optimal path taking the transmission direction, neighbor's location and destination position into account. Numerical results show that our proposed PTCCR outperforms two state-of-art routings, i.e., the real-time intersection-based segment aware routing protocol (RTISAR) and Reliable Traffic Aware Routing protocol (RTAR), in terms of packet delivery ratio, average end-to-end delay and communication overhead.

Multi‐objective auto‐regressive whale optimisation for traffic‐aware routing in urban VANET

Vehicular ad-hoc network (VANET) is a growing networking concept that has been used increasingly in various applications including traffic alert broadcasting. The main purpose of VANET is to provide safety to the drivers by alerting them to the dangers that may happen. This study presents a traffic-aware routing protocol in VANET by the introduction of multi-objective auto-regressive whale optimisation (ARWO) algorithm. ARWO algorithm selects the best path from the multiple paths by considering the multiple objectives, such as end-to-end delay (EED), link life time, packet delay and distance, in the fitness function. Here, the traffic density and the expected average speed of the vehicle are predicted by the exponential weighted moving average approach. The performance of ARWO protocol is compared with four existing techniques, like stable CDS-based routing protocol, fractional glow worm swarm optimisation, glow worm swarm optimisation, and Whale Optimization Algorithm (WOA), using the metrics, EED, distance, traffic density, and throughput. The simulation results show that the proposed ARWO algorithm achieves EED of 2.941, a distance of 2.15, traffic density of 0.009 and throughput of 0.1, respectively, at maximum constraints, i.e. at a maximum number of vehicles and simulation time and thus proves its efficiency against the comparative protocols.

Dynamic Multiple Junction Selection Based Routing Protocol for VANETs in City Environment

VANET (Vehicular Ad-hoc Network) is an emerging offshoot of MANETs (Mobile Ad-hoc Networks) with highly mobile nodes. It is envisioned to play a vital role in providing safety communications and commercial applications to the on-road public. Establishing an optimal route for vehicles to send packets to their respective destinations in VANETs is challenging because of quick speed of vehicles, dynamic nature of the network, and intermittent connectivity among nodes. This paper presents a novel position based routing technique called Dynamic Multiple Junction Selection based Routing (DMJSR) for the city environment. The novelty of DMJSR as compared to existing approaches comes from its novel dynamic multiple junction selection mechanism and an improved greedy forwarding mechanism based on one-hop neighbors between the junctions. To the best of our knowledge, it is the first ever attempt to study the impact of multiple junction selection mechanism on routing in VANETs. We present a detailed depiction of our protocol and the improvements it brings as compared to existing routing strategies. The simulation study exhibits that our proposed protocol outperforms the existing protocols like Geographic Source Routing Protocol (GSR), Enhanced Greedy Traffic Aware Routing Protocol (E-GyTAR) and Traffic Flow Oriented Routing Protocol (TFOR) in terms of packet delivery ratio, end-to-end delay, and routing overhead.

Reliable Intersection-Based Traffic Aware Routing Protocol for Urban Areas Vehicular Ad Hoc Networks

Nowadays, providing reliable vehicle to vehicle communications in vehicular ad hoc networks is essential to serve the emerging intelligent transportation systems. Traffic aware routing is considered a promising approach for delivering data packets between geographically separated vehicles. However, most of the existing traffic aware routing protocols greedily select the next-hop based on distance. Consequently, high packet loss ratio occurs especially with the vehicles high speed mobility. Some existing forwarding schemes attempted to improve the next-hop selection by considering inter-vehicle communication quality or neighbours predicted positions. Nevertheless, such schemes depend on the neighbours mobility information received through beacons regardless of its freshness. In addition, the differentiation between road and intersection areas while forwarding packets was neglected. Therefore, a reliable traffic aware routing protocol is proposed, which selects the next-hop based on roads structure, neighbours predicted positions and their received signal strength, and the recentness of the mobility information received from neighbours. The simulation results show significant improvements in terms of packet delivery ratio and end-to-end delays.

FGWSO‐TAR: Fractional glowworm swarm optimization for traffic aware routing in urban VANET

SummaryIn mobile distributed applications, such as traffic alert dissemination, dynamic route planning, file sharing, and so on, vehicular ad hoc network (VANET) has emerged as a feasible solution in recent years. However, the performance of the VANET depends on the routing protocol in accord with the delay and throughput requirements. Many of the routing protocols have been extensively studied in the literature. Although there are exemptions, they escalate research challenges in traffic aware routing (TAR) protocol of VANET. This paper introduces the fractional glowworm swarm optimization (FGWSO) for the TAR protocol of VANET in an urban scenario that can identify the optimal path for the vehicle with less traffic density and delay time. The proposed FGWSO searches the optimal routing path based on the fitness function formulated in this paper. Fractional glowworm swarm optimization is the combination of the GWSO and fractional theory. Moreover, exponential weighted moving average is utilized to predict the traffic density and the speed of the vehicle, which is utilized as the major constraints in the fitness function of the optimization algorithm to find the optimal traffic aware path. Simulation of FGWSO shows the significant improvement with a minimal end‐to‐end delay of 6.6395 seconds and distance of 17.3962 m, respectively, in comparison with the other existing routing approaches. The simulation also validates the optimality of the proposed TAR protocol.

Traffic‐aware routing protocol with cooperative coverage‐oriented information collection method for VANET

A traffic-aware routing protocol (TARCO) that considers integrated real-time traffic conditions for constructing delivery paths over a vehicular environment is presented. This goal was achieved through three mechanisms: cooperative traffic information collection, lightweight real-time road scoring and adaptable data route construction. An accurate overall view of the real-time traffic conditions was obtained from the cooperation between information aggregators at junctions and information collectors on road segments. Each road segment was then assigned a weight according to the overall view of the traffic conditions and updated periodically to reflect traffic variations. Finally, the road segments providing efficient and reliable data routes were used to construct a routing path with guaranteed connectivity and a short delivery delay to the destination. Simulation results showed that the use of TARCO leads to high network performance in terms of the packet delivery ratio, end-to-end delay and communication overhead.

Lightweight intersection-based traffic aware routing in Urban vehicular networks

One of the important characteristics of VANETs is the multi-hop communications, which provides Vehicle-to-Vehicle(V2V) communication for many applications. In order to adapt to mobility in high speeds and limited-time communication links, traffic aware routing was proposed in many research works. As a type of position based routing protocols, traffic aware routing utilizes vehicles’ positions and traffic status as two main routing parameters. However, providing real-time measurements for traffic status on each road generates high network overhead. In addition, to make such measurement always updated and available for routing purposes, the measurement process has to be applied frequently. This paper introduces a Lightweight Intersection-based Traffic Aware Routing (LITAR) protocol for V2V communication in urban vehicular networks. LITAR introduces two new algorithms to reduce the network overhead generated by the traffic status measurement process while preserving the accuracy of measurement. Moreover, LITAR make routing decisions based on vehicular directional density, Road Network Connectivity (RNC) and distance towards destination. The evaluation of the proposed LITAR protocol shows significant performance improvements in terms of packet delivery ratio, while reducing communication overhead as compared to existing routing approaches.

SIR: a secure and intelligent routing protocol for vehicular ad hoc network

Security in routing is an important issue in vehicular ad hoc network (VANET) to protect the valuable information. However, this intelligent transportation system (ITS) services provided by VANET are affected by the malicious vehicles. In this study, a secure and intelligent routing (SIR) protocol is proposed to transmit the data in a quickest path through the authenticated vehicles. Sending the data in a most connected path with less link connection problem enhances the system performance and selecting the authenticated vehicles in this quickest path protects the system from the malicious attacks. In this protocol, a weight W is calculated for every neighbouring junction Jneighbour by using the safety message transmission model, delay model, link connectivity model and vehicle position model. The Jneighbour with minimum W is selected as the junction through which the data are forwarded to the destination D. Simulation results show SIR performs better than secure path routing protocol, greedy traffic-aware routing, anchor-based street and traffic aware routing and geographic source routing protocols in terms of average end-to-end delay, network gap encounter and path length.

Traffic aware routing in vehicular ad hoc networks: characteristics and challenges

Vehicular ad hoc networks (VANETs) are gaining tremendous interest among researchers and industries. Although the main reason for developing VANETs is traffic safety, many applications such as traffic status monitoring, road traffic management, routing and distribution of data, have emerged. VANETs exploit multi-hop communications among vehicles to deliver data packets. However, with fast mobility and intermittent link connectivity between vehicles, efficient and reliable routing in VANETs is becoming a challenging task. In order to make routing protocols robust to frequent communication disruptions and aware of unstable traffic and network conditions, several new routing metrics have been integrated with routing protocols. Such protocols are called traffic aware routing (TAR) protocols as their routing decisions are influenced by traffic and network status. The goal of this paper is to review the most recent traffic aware routing protocols while emphasising on traffic and network conditions awareness issues. In addition, this review investigated TAR protocols capabilities and limitations in terms of routing process, routing metrics measurement, forwarding mechanisms and recovery techniques. Moreover, challenges, critical issues and open research problems were discussed in the "Challenges and issues to consider" sections.

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 & Sons, Ltd.

A Traffic Aware Routing Protocol for Congestion Avoidance in Content-Centric Network

Content-Centric Network (CCN) is next generation internet communication technology to provide existing internet communication paradigm as content based communication for efficient use various information in the Internet. Therefore, unlike existing internet communication technology, which focus on host based communication process, all of resource is defined as contents in CCN. Moreover it focuses on purpose of communication for using information. CCN communicate with between routers through broadcast flooding method in their network environments. This characteristic of CCN is not considering increasing network traffic about each of CCN routers. Therefore, when the requesters are rapidly increased to particular CCN router, network congestion may be occurred by broadcast traffic. Moreover, this characteristic of CCN has low turnaround time about user request due to reducing performance of network system. To resolve this problem, this paper proposes a traffic aware routing protocol for congestion avoidance in CCN. The proposed routing protocol considers rapidly increasing traffic in the situation and establishes another routing path to avoid increasing traffic problem in CCN.

A Traffic Aware Routing Protocol for Congestion Avoidance in Content-Centric Network

Content-Centric Network (CCN) is next generation internet communication technology to provide existing internet communication paradigm as content based communication for efficient use various information in the Internet. Therefore, unlike existing internet communication technology, which focus on host based communication process, all of resource is defined as contents in CCN. Moreover it focuses on purpose of communication for using information. CCN communicate with between routers through broadcast flooding method in their network environments. This characteristic of CCN is not considering increasing network traffic about each of CCN routers. Therefore, when the requesters are rapidly increased to particular CCN router, network congestion may be occurred by broadcast traffic. Moreover, this characteristic of CCN has low turnaround time about user request due to reducing performance of network system. To resolve this problem, this paper proposes a traffic aware routing protocol for congestion avoidance in CCN. The proposed routing protocol considers rapidly increasing traffic in the situation and establishes another routing path to avoid increasing traffic problem in CCN.

LSGO: Link State aware Geographic Opportunistic routing protocol for VANETs

Abstract Robust and efficient data delivery in vehicular ad hoc networks (VANETs) with high mobility is a challenging issue due to dynamic topology changes and unstable wireless links. The opportunistic routing protocols can improve the reliability of routing by making full use of the broadcast characteristics and assist in data transmission through additional backup links. In this paper, we propose a Link State aware Geographic Opportunistic routing protocol (LSGO) which exploits a combination of geographic location and the link state information as the routing metric. The LSGO aims to improve the reliability of data transmission in a highly dynamic environment, which selects the forwarders and prioritizes them based on the vehicle’s geographic location and the link’s quality. We compare the performance of LSGO with GpsrJ + which removes the unnecessary stop at a junction and greedy traffic aware routing protocol (GyTAR) using network simulator ns-2. The simulation results show that it opens more nodes to participate in the opportunistic data forwarding and increases a connection’s throughput while using no more network capacity than traditional routing. In the simulation, compared with other two protocols, when the number of vehicles and the average vehicle velocity increase, LSGO’s packet dropping rate is reduced and the network throughput is improved.