Intersection-based Routing Research Articles

An Intersection-Based QoS Routing for Vehicular Ad Hoc Networks With Reinforcement Learning

Vehicular ad hoc networks (VANETs) have the characteristics of high mobility, frequently changing topology and uneven distribution, which made it a challenge to design an efficient and robust routing protocol with low latency and high packet delivery rate. Currently, intersection-based routing method and full-path based routing method are two popular solutions for the packet routing in VANETs. Although the intersection-based routing method has better real-time performance, it has the problem of local optimization, making the routing results not global optimal. Although the full-path based method can obtain the global optimal solution, it is weak in dealing with the dynamically changing topological network. Aiming at solving the above problems, this paper designs an intersection-based QoS routing (IQRRL) algorithm, which mainly includes two crutial steps: the next intersection selection and the next hop vehicle selection. In the selection of the next intersection, this paper uses an improved intersection-based routing protocol. In addition to considering connectivity and delay, IQRRL also considers the communication quality from the neighbor’s road to the destination node while evaluating the quality of the neighbor’s road, which minimizes the problem of local optimization. When the next intersection is determined, a road is then determined, and then the next hop vehicle within the road should be chosen to relay the packet forward. In the next-hop vehicle selection step, this paper adopts multi-hop evaluation technology based on reinforcement learning. In addition to using “greedy decision-making” to select the next-hop vehicle, it also comprehensively evaluates whether the next-hop vehicle is still optimal in the future, so that the stability and reliability of data forwarding are improved and local optimal problems are avoided. Besides, this article uses a simulation system to compare IQRRL with other routing algorithms. The result reveals that IQRRL outperforms in terms of packet delivery ratio and transmission delay.

An Intersection-Based Routing Scheme Using Q-Learning in Vehicular Ad Hoc Networks for Traffic Management in the Intelligent Transportation System

Vehicular ad hoc networks (VANETs) create an advanced framework to support the intelligent transportation system and increase road safety by managing traffic flow and avoiding accidents. These networks have specific characteristics, including the high mobility of vehicles, dynamic topology, and frequent link failures. For this reason, providing an efficient and stable routing approach for VANET is a challenging issue. Reinforcement learning (RL) can solve the various challenges and issues of vehicular ad hoc networks, including routing. Most of the existing reinforcement learning-based routing methods are incompatible with the dynamic network environment and cannot prevent congestion in the network. Network congestion can be controlled by managing traffic flow. For this purpose, roadside units (RSUs) must monitor the road status to be informed about traffic conditions. In this paper, an intersection-based routing method using Q-learning (IRQ) is presented for VANETs. IRQ uses both global and local views in the routing process. For this reason, a dissemination mechanism of traffic information is introduced to create these global and local views. According to the global view, a Q-learning-based routing technique is designed for discovering the best routes between intersections. The central server continuously evaluates the created paths between intersections to penalize road segments with high congestion and improve the packet delivery rate. Finally, IRQ uses a greedy strategy based on a local view to find the best next-hop node in each road segment. NS2 software is used for analyzing the performance of the proposed routing approach. Then, IRQ is compared with three methods, including IV2XQ, QGrid, and GPSR. The simulation results demonstrate that IRQ has an acceptable performance in terms of packet delivery rate and delay. However, its communication overhead is higher than IV2XQ.

Intersection-Based Routing with Fuzzy Multi-Factor Decision for VANETs

Due to the limitations of the urban environment, the data transferred between vehicles can only change direction at the intersections. Therefore, the routing decision at an intersection will largely affect the overall routing decision. In this article, we propose an Intersection-Based Routing with Fuzzy Multi-Factor Decision (IRFMF), which utilizes several factors to decide the next road segment. In the scheme, each intersection introduces three factors including the direction, the number of lanes, and the traffic. After the fuzzification and defuzzification of these factors, the candidate segment with the highest evaluation will be selected. The simulation shows a significant improvement of VANETs performance on packet delivery ratio and end-to-end delay.

ACO–IBR: a modified intersection‐based routing approach for the VANET

The usage of dedicated short-range communication, vehicular ad hoc network (VANET) significantly increases the security of stakeholders and improves the efficacy of the intelligent transportation system. It supports multifarious applications to make transportation convenient through routing of the messages. Changing the topological scenario, high acceleration of vehicles and intermittent communication result in the reduction of successful packet transmission and overhead. To overcome such constraints, a new routing protocol for the city environment named ant colony optimisation and intersection-based routing (ACO–IBR) is proposed. The key objective is to identify the necessity of intersection oriented routing and selection of the route as a task of optimisation. It uses a new metric called intersection rating and a greedy approach to forward a packet through the intersection to minimise the time required to discover the route. The efforts have been made to calculate intersection rating using three parameters such as the distance between vehicles, travel direction and the time taken to reach the intersection. The performance of ACO–IBR is determined by overhead, packet delivery ratio, delay and throughput. The results are compared with the standard protocols such as greedy perimeter stateless routing, intersection-based routing, AntHocNet and zone routing protocol. On the basis of extensive simulation, experimental results show that the ACO–IBR minimises routing overhead and improves the packet delivery ratio.

MMIR: a microscopic mechanism for street selection based on intersection records in urban VANET routing

In urban vehicular ad hoc networks (VANETs), the intersection-based routing scheme has represented its greater applicability and better efficiency to adapt to high and constrained mobility. How to make an accurate decision for street selection is a challenging issue due to the rapid topology changes in VANETs. In this paper, we propose a microscopic mechanism based on intersection records (MMIR) in which the intersection vehicle nodes maintain and update a records table with every passing vehicle’s individual information. By analyzing and processing these entries, we evaluate these vehicles’ current positions so as to compute the connectivity probability or estimated delivery delay for all candidate streets to support street selection. In contrast to the statistical and macroscopic information for the common condition, we firstly make use of the individual and microscopic data to enhance the accuracy of estimated results. Furthermore, according to the quantity and the running interval, we classify vehicles into two categories: individual and queue vehicles, in order to effectively decrease the complexity of position estimation. Lastly, since there are no dedicated control packets generated in MMIR, the network overhead is low. The simulation results show that the proposed MMIR outperforms existing approaches of street selection in terms of the accuracy of computed connectivity probability and estimated delay.

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.

Intersection Intelligence: Supporting Urban Platooning with Virtual Traffic Lights over Virtualized Intersection-Based Routing.

The advent of the autonomous car is paving the road to the realization of ideas that will help optimize traffic flows, increase safety and reduce fuel consumption, among other advantages. We present one proposal to bring together Virtual Traffics Lights (VTLs) and platooning in urban scenarios, leaning on vehicle-to-vehicle (V2V) communication protocols that turn intersections into virtual containers of data. Newly-introduced protocols for the combined management of VTLs and platoons are validated by simulation, comparing a range of routing protocols for the vehicular networks with the baseline given by common deployments of traditional traffic lights ruled by state-of-the-art policies. The simulation results show that the combination of VTLs and platoons can achieve significant reductions in travel times and fuel consumption, provided that proper algorithms are used to handle the V2V communications.

Genetic Algorithm Based QoS Perception Routing Protocol for VANETs

A genetic algorithm (GA) based QoS perception routing protocol (GABR) is proposed to guarantee the quality of service (QoS) influenced by broken links between vehicles and the failure of packets transmission in a vehicular ad hoc network (VANET). With the observation that all improvable paths are probed by the intersection based routing protocol, the genetic GA is utilized to optimize the global available paths which satisfies the QoS requirement. Moreover, by means of the numerical results, it is shown that the proposed scheme is significantly improved compared with protocols of the intersection based routing (IBR) and connectivity aware routing (CAR) in terms of transmission delay and packet loss rate.

Multi-Copy Intersection-Based Routing Protocol for VANET in Urban Areas

Multi-Copy Intersection-Based Routing Protocol for VANET in Urban Areas

Efficient and viable intersection-based routing in VANETs on top of a virtualization layer

Recent vehicular ad hoc network routing protocols have relied on geographic forwarding and careful selection of road segments as ways to reduce the impact of individual vehicle movements. This paper shows how a virtualization layer and a new protocol running on top of it —called VNIBR, intersection-based routing on virtual nodes—can achieve better performance than state-of-the-art approaches, enabling an efficient and computationally feasible combination of topological and geographical routing. We prove by means of network simulations that this proposal consistently ensures moderate overhead, good packet delivery ratios, and low end-to-end delays, whereas the other protocols exhibit weaknesses due to flooding processes that scale poorly, proactive routing burdens or costly location services. We also present the results of graphics processing unit profiling used to assess the computational feasibility of the different schemes in the context of a real on-board computer, which reveals new advantages about scalability and impact of computational shortages on the routing performance.

A connectivity-aware intersection-based routing in VANETs

Vehicular ad hoc networks (VANETs) are going to be an important communication infrastructure in our moving life. The design of routing protocols in VANETs is a significant and necessary issue for supporting VANET-based applications. However, due to high mobility, frequent link disconnection, and uneven distribution of vehicles, it becomes quite challenging to establish a robust route for delivering packets. This paper presents a connectivity-aware intersection-based routing (CAIR) protocol to address these problems by selecting an optimal route with higher probability of connectivity and lower experienced delay; then, geographical forwarding based on position prediction is used to transfer packets between any two intersections along the route. Simulation results show that the proposed protocol outperforms existing routing protocols in terms of data delivery ratio and average transmission delay in typical urban scenarios.

Intersection-based routing for urban vehicular communications with traffic-light considerations

In this article, we explore the impact of traffic lights on routing protocol design in vehicular ad hoc networks. Specifically, we focus on intersection-based routing protocols designed for vehicular communications in urban areas. We find that traffic lights greatly impact routing in urban areas, but this issue has not been well treated in existing routing protocols. In this article, we propose a new protocol called Shortest-Path-Based Traffic-Light-Aware Routing (STAR) for VANETs with traffic light considerations. For STAR, the signals of traffic lights on the intersection, together with the traffic patterns, determine how packets are forwarded. We show via analysis and simulation that our proposed STAR protocol is superior to Green Light First forwarding (i.e., packets are forwarded on the path with green lights). We also conduct ns-2 simulations to evaluate the performance of STAR. The results show that STAR achieves shorter average delay, higher delivery ratio and higher TCP throughput than existing routing protocols for urban VANET communications.

Intersection-Based Routing Protocol for VANETs

Vehicular ad hoc network (VANET) is an emerging wireless communications technology that is capable of enhancing driving safety and velocity by exchanging real-time transportation information. In VANETs, the carry-and-forward strategy has been adopted to overcome uneven distribution of vehicles. If the next vehicle located is in transmission range, then the vehicle forwards the packets; if not, then it carries the packets until meeting. The carry mostly occurs on sparsely populated road segments, with long carry distances having long end-to-end packet delays. Similarly, the dense condition could have long delays, due to queuing delays. The proposed intersection-based routing protocol finds a minimum delay routing path in various vehicle densities. Moreover, vehicles reroute each packet according to real-time road conditions in each intersection, and the packet routing at the intersections is dependent on the moving direction of the next vehicle. Finally, the simulation results show that the proposed Intersection-Based Routing (IBR) protocol has less end-to-end delay compared to vehicle-assisted data delivery (VADD) and greedy traffic aware routing protocol (GyTAR) protcols.