E2E Delay Reduction in VANETs using SARSA-based Reinforcement Learning

Vehicular Ad hoc Networks (VANETs) are a class of wireless networks built dynamically in an ad hoc network manner. VANET is a key technology for smart and Intelligent Transportation System. Efficient and intelligent algorithms for routing in VANETs are critically required for safety information propagation. Routing in highly dynamic VANET topology is important for the achievement of any vehicular safety applications. The routing mechanism in vehicular networks is critical because of VANETconstraints such as unpredictable network topology, frequent disconnections, varying network densities, etc. Multi agent scheme based routing scheme for VANETs is addressed in the paper. We address the challenge of how to route the data with short communication delay, overhead, and the complexity. Specifically, we consider the scenario for (V2V) vehicle-to-vehicle communication. Multi agent scheme consists of static agent and mobile agents. The scheme operates as follows: (1) establishing a connectivity pattern between the vehicles; (2) creating a set of beliefs; (3) desire development; (4) finalizing the intention. We validate the proposed scheme by simulation. Evaluated simulation results are packet delivery ratio, bandwidth utilization, and route identification delay.

Vehicular Ad Hoc Networks (VANETs) and the Internet of Vehicles (IoV) are critical for intelligent transportation, yet face challenges such as dynamic topologies, frequent disconnections, and high data traffic. This paper proposes a Genetic Bee Colony (GBC) algorithm, a hybrid of Genetic Algorithms and Artificial Bee Colony optimization, to enhance routing and communication efficiency in VANETs. The framework integrates vehicle-to-vehicle, vehicle-to-infrastructure, vehicle-to-cloud, and vehicle-to-pedestrian communications, applying GBC to optimize routing under varying traffic conditions. Simulations conducted in NS-2.35 evaluate throughput, packet delivery ratio (PDR), and end-to-end delay. Results show that the GBC-based approach outperforms conventional methods, achieving higher PDR, reduced delay, and improved throughput. Additionally, a built-in monitoring and traceback mechanism detects misbehaving nodes, ensuring secure and reliable communication. This work demonstrates the potential of bio-inspired algorithms for scalable, adaptive, and secure IoV systems, advancing the development of smart transportation networks.

The swift improvement of wireless communication technology has aided the creation of vehicular ad hoc networks (VANETs) as a revolutionary option for the realization of intelligent transportation systems (ITSs). VANETs facilitate seamless communication between vehicles and infrastructure (V2I) and among the vehicles themselves (V2V). These networks can enhance safety and traffic control while providing various infotainment options. To ensure stable and efficient communication in highly dynamic and quickly changing vehicular contexts, effective data packet routing is a crucial component of VANETs. This survey delves further into the VANET routing algorithms for ITS. The study aims to evaluate the effectiveness and acceptability of various routing protocols suggested for VANETs while considering their unique requirements and difficulties. The review covers ad hoc on‐demand distance vector (AODV) and dynamic source routing (DSR), as well as more current strategies designed specifically for VANETs, such as geographic routing, cluster‐based routing, and hybrid routing protocols. The review assesses the routing algorithms based on several vital parameters, including packet delivery ratio (PDR), end‐to‐end delay, throughput, network overhead, scalability, and robustness. This detailed assessment supports aspiring researchers in acquiring a better knowledge of the benefits and drawbacks of the routing algorithms currently used in VANETs.

Due to many challenging issues in vehicular ad-hoc networks (VANETs), such as high mobility and network instability, this has led to insecurity and vulnerability to attacks. Due to dynamic network topology changes and frequent network re-configuration, security is a major target in VANET research domains. VANETs have gained significant attention in the current wireless network scenario, due to their exclusive characteristics which are different from other wireless networks such as rapid link failure and high vehicle mobility. In this are, the authors present a Secured and Safety Protocol for VANET (STVAN), as an intelligent Ad-Hoc On Demand Distance Vector (AODV)-based routing mechanism that prevents the Denial of Service attack (DoS) and improves the quality of service for secured communications in a VANET. In order to build a STVAN, the authors have considered a smart traffic environment in a smart city and introduced the concept of load balancing over VANET vehicles in a best effort manner. Simulation results reveal that the proposed STVAN accomplishes enhanced performance when compared with other similar protocols in terms of reduced delay, better packet delivery ratio, reasonable energy efficiency, increased network throughput and decreased data drop compared to other similar approach.

Vehicular Ad-Hoc Networks (VANET) are a proper subset of mobile wireless networks, where nodes are revulsive, the vehicles are armed with special electronic devices on the motherboard OBU (On Board Unit) which enables them to trasmit and receive messages from other vehicles in the VANET. Furthermore the communication between the vehicles, the VANET interface is donated by the contact points with road infrastructure. VANET is a subgroup of MANETs. Unlike the MANETs nodes, VANET nodes are moving very fast. Impound a permanent route for the dissemination of emergency messages and alerts from a danger zone is a very challenging task. Therefore, routing plays a significant duty in VANETs. decreasing network overhead, avoiding network congestion, increasing traffic congestion and packet delivery ratio are the most important issues associated with routing in VANETs. In addition, VANET network is subject to various security attacks. In base VANET systems, an algorithm is used to dicover attacks at the time of confirmation in which overhead delay occurs. This paper proposes (P-Secure) approach which is used for the detection of DoS attacks before the confirmation time. This reduces the overhead delays for processing and increasing the security in VANETs. Simulation results show that the P-Secure approach, is more efficient than OBUmodelVaNET approach in terms of PDR, e2e_delay, throughput and drop packet rate.

The vehicular ad hoc network is an emerging area of technology that provides intelligent transportation systems with vast advantages and applications. Frequent disconnections between the vehicular nodes due to high-velocity vehicles impact network performance. This can be addressed by efficient clustering techniques. Several recent studies have attempted to develop optimal clustering algorithms to improve network performance metrics using soft computing techniques. Although sufficient work on soft computing techniques has been carried out, it seems less commonplace to find an analysis of various algorithms’ network parameters together. This paper provides a systematic analysis of the clustering-based routing protocols used in vehicular networks that are aware of soft computing techniques. The categorization is performed according to various soft computing techniques: particle swarm optimization, k-means, neural networks, artificial bee colony, genetic algorithm, firefly algorithm, and fuzzy logic. A comparative study of soft computing strategies is also provided in the survey with a focus on their objectives, along with their strengths and limitations. This survey makes it easier for researchers to pick the required soft computing technique used in vehicular networks in order to improve metrics such as packet delivery ratio, end-to-end delay, throughput, cluster lifetime, and message overhead.

Vehicular ad hoc network (VANET) is an innovative technology that has attracted many researchers and the industrial sector. The increase in vehicle movement and the requirement for effective traffic management systems have resulted in the development of VANETs. The Super Cluster Head based Efficient Traffic Control (SCHETF) model aims to alleviate traffic congestion and decrease energy consumption in VANETs through a novel integration of Cluster Head (CH) election, cluster gateway formation, and effective data transmission. SCHETF utilizes a parameter-driven CH election process that considers factors such as network connectivity, distance, speed, and trust levels. This approach guarantees the most suitable CH selection, reducing energy expenditure while enhancing network efficiency. The model assesses network connectivity through indicators like traffic flow and lane weights, ensuring precise determination of link reliability. Metrics for distance and speed are normalized to evaluate the changing behavior of vehicles, while trust ratings are given based on historical and community information to improve reliability. The creation of cluster gateways reduces unnecessary cluster formations by implementing Cluster Gateway Creation (CGC) at strategic sites, lessening communication load, and boosting cluster stability. Efficient data transmission is accomplished by appointing several Cluster Gateway (CGW) within clusters. A backoff timer mechanism gives priority to the CGW that is farthest from the CH for message forwarding, avoiding unnecessary repetitions and guaranteeing effective message dispatch. The model is smart clustering and gateway strategies lessen signaling load during handovers and enhance resource management in dynamic vehicular settings. The SCHETF model offers a thorough framework for tackling the challenges faced by VANETs, providing scalable and energy-efficient communication options. This improves data distribution, assures dependable connectivity, and plays a crucial role in the progress of intelligent transportation systems. The model has been put into practice through experimentation in Network Simulator 2 (NS2). The parameters considered in this study encompass energy efficiency, throughput, packet delivery ratio, end-to-end delay, packet loss, and routing overhead. To undertake a comparison study, the developed SCHETF findings are compared to older approaches such as Evolutionary Algorithm-based Vehicular Clustering Technique (EAVCT), Region Collaborative Management for Dynamic Clustering (RCMDC), and Novel Hypergraph Clustering Model (NHGCM). The outcomes indicate that the suggested SCHETF strategy outperforms previous methods.

Vehicular Ad hoc Network (VANET) is an emerging technology with some unique characteristics that makes it different from other ad-hoc networks. VANETs could be a key networking technology of the future vehicle communications, where the communication is possible between V2V, V2I and other hybrid architectures. One of the major issues in VANET is routing due to high mobility and dynamic topology. Since the routing protocol decides how better the communication occurs between the vehicles, the design of routing protocol is very important. We bring the current research efforts on the intelligent routing scheme for VANET. In this research paper, we determine the position of vehicles using GPS, in both city and highway scenarios and establish the communication links between vehicles based on fish swarm algorithm. Our simulation results shows that the proposed intelligent routing algorithm performs better in terms of bandwidth utilized, packet delivery ratio and end-to-end delay etc.

<h2>Abstract</h2> <p><strong>Objective:</strong> The objective of this work is to enhance Adhoc On-demand Distance Vector (AODV) routing protocol for better communication through reliable routing scheme.<strong> Methods:</strong> In this paper, a reliable path selection algorithm is proposed to find the Most Reliable Path (MRP) between the source and destination vehicles. Reliable Path Ad-hoc On demand Distance Vector (RPAODV) is proposed for efficient route discovery in Vehicular Ad-hoc Network (VANET). The algorithm divide network into manageable group and it maintains Cluster Member (CM) updates handling, Cluster Head (CH) re-selection, Cluster merging. The efficient routing decisions would lead to better communication in VANET. It is made by assigning dynamic and static information appropriately to the variables in process. The dataset used is both static and dynamic which is efficient in when compared with existing protocols. <strong>Findings:</strong> The finding of most reliable path in the network of VANET is carried out by the proposed reliable path selection algorithm. The algorithm divides the network as various parts that comprise the information of clustering. The clustering is the mechanism of grouping of nodes into clusters. Clusters possess members and head. The cluster head would be the point of initiation of communication and any node can be re-selected as cluster head. The members of clusters would be updated as per changes in clustering mechanism. The uniqueness of the proposed algorithm revealed through easy identification of vehicles to form a cluster, cluster members maintenance, and fast data communication over the network. The proposed RPAODV adds the extra fields for RouteREQuest (RREQ) and RouteREPly (RREP) messages (CH and CM information). It also works out for static and dynamic topology in good manner by the implementation of modified AODV algorithm. The scalability is also taken care by enhancing topology variant. The performance of the algorithm is measured and analyzed with the existing protocols and posted in graphs. <strong>Novelty:</strong> The simulation results show that the proposed work outperforms 60% than the existing schemes works Cluster-based VANET-oriented Evolving Graph( CVoEG), Leapfrog-Anti-Colony Optimization(LP-ACO) in terms of route reliability (0.11s high), packet delivery ratio (20% high), end to end delay (0.5 saverage), and throughput (10 kbps high).</p> <p><strong>Keywords:</strong> VANET; Routing Protocol; RPAODV; Clustering; Reliable Routing; and Cluster message</p>

The exploration of Vehicular Ad Hoc Networks (VANETs) has garnered attention from scholars and businesses alike because of their changing structure and expected traffic flow patterns. VANETs offer an avenue to boost road safety by offering drivers up-to-the-minute updates and predictions regarding road conditions. As a version of Mobile Ad Hoc Networks (MANETs) VANETs consist of units that can communicate wirelessly and share information. This study explores elements of VANET (Vehicular Ad Hoc Networks) such, as structures and functions of networks connection points and the issues and methods used for guiding traffic efficiently to create a secure and dependable communication network system. Key indicators of performance like how many packets delivered (Packet Delivery Ratio. PDR) packet losses experienced during transmission processes are carefully analyzed to gauge the overall reliability of the system. Additionally, the research includes a comparison among routing strategies employed in VANET environments such as those based on network topology information or geographical location details, versus approaches centered around organized clusters of vehicles. Highlighting how these differ from methodologies typically seen in traditional cellular networks. This paper provides insights into how different routing protocols work in networking paradigms by examining different perspectives.

Rapid and tremendous advances in wireless technology, miniaturization, and Internet of things (IoT) technology have brought significant development to vehicular ad hoc networks (VANETs). VANETs and IoT together play a vital role in the current intelligent transport system (ITS). However, a VANET is highly vulnerable to various security attacks due to its highly dynamic, decentralized, open-access medium, and protocol-design-related concerns. Regarding security concerns, a black hole attack (BHA) is one such threat in which the control or data packets are dropped by the malicious vehicle, converting a safe path/link into a compromised one. Dropping data packets has a severe impact on a VANET’s performance and security and may cause road fatalities, accidents, and traffic jams. In this study, a novel solution called detection and prevention of a BHA (DPBHA) is proposed to secure and improve the overall security and performance of the VANETs by detecting BHA at an early stage of the route discovery process. The proposed solution is based on calculating a dynamic threshold value and generating a forged route request (RREQ) packet. The solution is implemented and evaluated in the NS-2 simulator and its performance and efficacy are compared with the benchmark schemes. The results showed that the proposed DPBHA outperformed the benchmark schemes in terms of increasing the packet delivery ratio (PDR) by 3.0%, increasing throughput by 6.15%, reducing the routing overhead by 3.69%, decreasing the end-to-end delay by 6.13%, and achieving a maximum detection rate of 94.66%.

Vehicular Ad Hoc Network (VANET) is the basic technology of intelligent transportation systems for providing reliable and real-time communications between vehicles and vehicles or roadside units. In order to improve the communication quality of VANET, this paper studies the effects of different maximum routing hop count parameters on the performance of the network under different vehicle densities. We establish the mathematical models of node connectivity probability and the packet delivery ratio by using the Poisson distribution model. And the maximum routing hop count selection algorithm (MRHSA) is proposed based on the theoretical model established in the paper. The simulation experiments and statistical analysis on packet delivery ratio, throughput, and end-to-end delay are performed under the straight road and urban road scenes, supported by the Vehicle in Network Simulation (Veins). The results show that the maximum routing hop count parameter is an important impact factor on the communication quality of the network. It is found that MRSHA proposed in this paper can improve the packet delivery ratio by about 9.1% at most in straight road scenarios, which indicates that MRHSA will contribute to the improvement of the communication quality of VANET.

Vehicular Ad Hoc Network (VANET) is an extension to Mobile Ad Hoc Network (MANET) technology. VANET differs from MANET because it contains high mobility of nodes and large scale of networks. In this paper, real-time maps of certain areas in Shah Alam had been chosen and edited using JAVA Open Street Map editor (JOSM). Mobility Model Generator for VANET (MOVE) and Simulation of Urban Mobility (SUMO) are used to create the scenarios and traffics for urban and rural area network. The simulation is done in NS-2 with DSRC and Wi-Fi Direct standard using AODV routing protocol to evaluate various Quality of Service (QoS) parameters such as throughput, end-to-end delay, and packet delivery ratio (PDR) for the selected areas. The main discoveries of this paper are that the throughput and end-to-end delay increases as the number of mobile nodes increases. PDR does not get affected by the number of mobile nodes but instead depends on other factors including coverage of standards and traffic pattern. To summarize, VANET in rural scenario gives better performance as compared to the urban scenario.

A vehicular ad-hoc network (VANET) is a type of ad-hoc network that has gained high attention over the past few years and is extensively used in safety critical applications in case of emergency like road accidents. The proper working of VANET in these safety critical applications requires the need of VANET supporting timely and reliable delivery of the data to the receiver vehicles. However, supporting both timely and reliable delivery of the data messages to the receiver has become highly challenging in VANET because vehicle mobility, dynamic mobility pattern of the vehicles, dynamic network topology, and error-prone wireless communication channel. In this paper, this challenge is addressed by proposing Relia-MAC framework that adds timing properties to the novel Adaptive Byte-Hybrid Automatic Repeat request (AB-HARQ) method. The uniqueness of this paper lies in developing a single framework which when implemented in a vehicular ad-hoc network can assure both timely and reliable delivery of the data packets. Both analytic model and simulation studies are used in this paper to evaluate the effectiveness of proposed framework. The simulation studies have identified the effectiveness of Relia-MAC framework in recording higher ring throughput value and packet delivery ratio.

The availability of more realistic road conditions and dynamics provides sound ground to study the issues of Vehicular ad-hoc Network (VANET). In this chapter a new heterogeneous traffic flow based mathematical model is presented, to gain the time and space dynamics of vehicles. To achieve more accurate and realistic data about road conditions, microscopic parameters of varying safety distance between the vehicles and vehicular length are considered in the model. The density dynamics under different road scenarios are calculated under the influence of these constraints with the use of a defined mathematical model. The model is able to capture the impact of road constraints such as traffic lights and road incidents, on the traffic flow. The concept of Vehicular Ad-hoc Networks (VANET) has given mankind opportunities for secure and safe journeys on the roads. VANET is defined as a subclass of Mobile Ad-hoc Networks which holds the characteristics of ad-hoc networks. However due to the dynamic road conditions, traffic flow theory concepts, mobility constraints, human behaviours and vehicular characteristics VANET exhibits different dynamics. These factors have strong influences on the VANET architecture from physical to application layers. This highlights different areas of interest in VANET for researchers to investigate. This study aims to capture the impact of traffic flow theory constraints on the vehicular density under the heterogeneous traffic flow on the road. The microscopic and macroscopic characteristics of vehicles moving on the roads are utilized for the improvement of VANET connectivity dynamics.