Urban Vehicular Ad Hoc Networks Research Articles

Enhancing network stability in VANETs using nature inspired algorithm for intelligent transportation system.

The Internet of Vehicles (IoV) is one of the developing paradigms that integrates the automotive industry with the Internet of Things (IoT). The evolution of traditional Vehicular Ad-hoc Networks (VANETs), which are a layered framework for Intelligent Transportation Systems (ITS), is employed to provide Quality of Service (QoS) to end users in hazardous situations. VANETs can set up ad-hoc networks and share information among themselves using Peer-to-Peer (P2P) communication. Dynamic properties in VANETs such as dynamic topology, node mobility, sparse vehicle distribution, and bandwidth constraints can have an impact on scalability, routing, and security. This can result in frequent link failures, instability, reliability, and QOS concerns, as well as the inherent complexity of NP-hard problems. Researchers have proposed several techniques to achieve stability; the most prominent one is clustering, which relies on mobility metrics. However, existing clustering techniques generate overwhelming clusters, resulting in greater resource consumption, communication overhead, and hop count, which may lead to increased latency. Therefore, the primary objective is to achieve stability by increasing cluster lifetime, which is accomplished by generating optimal clusters. A nature-inspired meta-heuristic algorithm titled African Vulture Optimization Based Clustering Algorithm (AVOCA) is implemented to achieve it. The proposed algorithm can achieve load optimization with efficient resource utilization by mitigating hidden node challenges and ensuring communication proficiency. By maintaining an equilibrium state between the exploration and exploitation phases, AVOCA avoids local optima. The paper explores a taxonomy of the techniques used in Cluster Head (CH) selection, coordination, and maintenance to achieve stability with lower communication costs. We evaluated the effectiveness of AVOCA using various network grid sizes, transmission ranges, and network nodes. The results show that AVOCA generates 40% less clusters when compared to the Clustering Algorithm Based on Moth-Flame Optimization for VANETs (CAMONET). AVOCA generates 45% less clusters when compared to Self-Adaptive Multi-Kernel Clustering for Urban VANETs (SAMNET), AVOCA generates 43% less clusters when compared to Intelligent Whale Optimization Algorithm (i-WOA) and AVOCA generates 38% less clusters when compared to Harris Hawks Optimization (HHO). The results show that AVOCA outperforms state-of-the-art algorithms in generating optimal clusters.

Improved junction-based routing for VANETs using a Bio-inspired route stability approach

The Junction-Based Routing (JBR) is established as the adequate solution to data packet routing within an urban Vehicular Ad Hoc Network (VANET). The latter is characterized by radio obstacles, unreadable traffic density change, and unstable vehicular mobility speed. Existing JBR routing protocols have not defined specific evaluation mechanisms to anticipate and detect stable road segments in large urban areas yet. Consequently, the connectivity of selected streets for data forwarding may not be regularly reliable for long periods, especially for remote destinations. As a matter of fact, stable long-lifespan JBR paths cannot be discovered; hence, generating low Packet Delivery Ratio (PDR) performances. In this paper, we introduce swarm-inspired optimization as a novel solution to reduce the number of lost data packets on the basis of a new route stability notion. A bio-inspired metaheuristic technique named the Intelligent Water Drops (IWD) algorithm is applied to track reactively and proactively the routing consistency of road segments. IWD seeks to gather accurately unreachable road segments’ up-to-date connectivity information in order to predict progressively their stability degree. The latter is deduced according to predefined routing parameters featuring the history of route traffic and data forwarding, and vehicles’ speed. These parameters are utilized to trace direct JBR paths to data packets’ destinations with minimum disconnected road segments following IWD-inspired Dijkstra JBR paths. The proposed bio-inspired JBR protocol is compared to a few notable JBR schemes in a city map scenario. The simulation results showed a consistent mean PDR progress between 2.55% and 33.47% of all tested simulation variants.

Efficient algorithms for urban vehicular Ad Hoc networks quality based on average network flows

Efficient algorithms for urban vehicular Ad Hoc networks quality based on average network flows

An RSU-Assisted Hybrid Emergency Message Broadcasting Protocol for VANETs

In vehicular ad hoc networks (VANETs), emergency messages broadcasting has been considered as one of the important parts for safety related applications. The efficiency and reliability of the emergency message broadcasting are severely affected by the network structure, message redundancy, channel contention, etc. To address this problem, in this paper, we propose an RSUs-assisted hybrid emergency message broadcasting (RA-HEMB) protocol for two-way grid roads in urban VANETs. In doing so, the broadcasting target region is first generated based on the instantaneous traffic status and types of the emergency messages. To balance the deliver latency and the reliability, an adaptive forwarding nodes selection scheme based on position is proposed to dynamically determine the forwarding area according to different vehicle densities and vehicle-to-vehicle (V2V) communication ranges. Then, based on the forwarding nodes selection scheme and roadside unit (RSU) deployment, an RA-HEMB protocol is established by properly utilizing both the wired links via RSUs and the wireless links to broadcast the emergency message in hybrid vehicular networks. Simulation results show that the proposed RA-HEMB can greatly shorten the broadcasting time needed to notice the nodes within the target region performance compared to the benchmark protocols.

Predictive Modeling of Signal Degradation in Urban VANETs Using Artificial Neural Networks

In urban Vehicular Ad Hoc Network (VANET) environments, buildings play a crucial role as they can act as obstacles that attenuate the transmission signal between vehicles. Such obstacles lead to multipath effects, which could substantially impact data transmission due to fading. Therefore, quantifying the impact of buildings on transmission quality is a key parameter of the propagation model, especially in critical scenarios involving emergency vehicles where reliable communication is of utmost importance. In this research, we propose a supervised learning approach based on Artificial Neural Networks (ANNs) to develop a predictive model capable of estimating the level of signal degradation, represented by the Bit Error Rate (BER), based on the obstacles perceived by moving emergency vehicles. By establishing a relationship between the level of signal degradation and the encountered obstacles, our proposed mechanism enables efficient routing decisions being made prior to the transmission process. Consequently, data packets are routed through paths that exhibit the lowest BER. To collect the training data, we employed Network Simulator 3 (NS-3) in conjunction with the Simulation of Urban MObility (SUMO) simulator, leveraging real-world data sourced from the OpenStreetMap (OSM) geographic database. OSM enabled us to gather geospatial data related to the Two-Dimensional (2D) geometric structure of buildings, which served as input for our Artificial Neural Network (ANN). To determine the most suitable algorithm for our ANN, we assessed the accuracy of ten learning algorithms in MATLAB, utilizing five key metrics: Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Correlation Coefficient (R), and Maximum Prediction Error (MaxPE). For each algorithm, we conducted fifteen iterations based on ten hidden neurons and gauged its accuracy against the aforementioned metrics. Our analysis highlighted that the ANN underpinned by the Conjugate Gradient With Powell/Beale Restarts (CGB) learning algorithm exhibited superior performance in terms of MSE, RMSE, MAE, R, and MaxPE compared to other algorithms such as Levenberg–Marquardt (LM), Bayesian Regularization (BR), BFGS Quasi-Newton (BFG), Resilient Backpropagation (RP), Scaled Conjugate Gradient (SCG), Fletcher–Powell Conjugate Gradient (CGF), Polak–Ribiére Conjugate Gradient (CGP), One-Step Secant (OSS), and Variable Learning Rate Backpropagation (GDX). The BER prediction by our ANN incorporates the TWO-RAY Ground (TRG) propagation model, an adjustable parameter within NS-3. When subjected to 300 new samples, the trained ANN’s simulation outcomes illustrated its capability to learn, generalize, and successfully predict the BER for a new data instance. Overall, our research contributes to enhancing the performance and reliability of communication in urban VANET environments, especially in critical scenarios involving emergency vehicles, by leveraging supervised learning and artificial neural networks to predict signal degradation levels and optimize routing decisions accordingly.

A Multi-Objective Roadside Unit Deployment Model for an Urban Vehicular Ad Hoc Network

Vehicular ad hoc networks (VANETs) are a type of mobile ad hoc network that forms a unified wireless communication network between vehicles and roadside nodes. Roadside units (RSUs), as the infrastructure and key component of VANETs, play a critical role in improving the performance of VANETs. Their deployment can effectively improve the communication performance of the network. The goal of the RSU deployment (RSUD) problem is to install as few RSUs as possible on both sides of roads or intersections so that they can cover most areas and achieve better communication performance. This paper proposes a multi-objective optimization model to solve the RSUD problem using the characteristics of RSUDs on urban roads. Our optimized target includes three performance indicators, which are the deployment cost of RSUs, their coverage area, and communications. Since these three indicators cannot achieve consensus, this paper proposes a multi-objective evolutionary algorithm, the NSGA-II Pareto optimal solution, to solve the RSUD problem. The simulation results show the effectiveness of the multi-objective model and method. Finally, we present an experiment featuring RSU deployment that is based on a real traffic environment and uses OpenStreetMap; this experiment proves that our proposed method is practical.

Connectivity Analysis with Co-Channel Interference for Urban Vehicular Ad Hoc Networks

In urban vehicular ad hoc networks (VANETs), the complex channel environment and co-channel interference resulted in the uncertain delay of inter-vehicle packet transmission, which causes serious delay jitter. Connectivity is proposed as a key metric to describe this uncertainty. However, existing works lack a discussion of inter-vehicle connectivity in urban VANETs, particularly with regards to the process of transmitting packets between vehicles. In this paper, we analyze the connectivity probability of urban VANETs under co-channel interference with both complete and incomplete information. When the information is complete, we model the time-varying nature of co-channel interference and channel fading as delay jitter and analyze inter-vehicle connectivity in a time-varying environment. Then, when complete information is unavailable, we estimate the probability distribution of co-channel interference by combining the distribution of multiple parameters with the free space propagation model (Friss) model and Nakagami-m fading model. The expression for the connectivity performance of vehicle-to-vehicle (V2V) links is derived from the signal interference plus noise ratio (SINR) of the destination V2V link. Finally, we analyze the implications of various factors on connectivity, such as the transmit power of the signal, the arrival rate of packets, the number of channels and vehicles, and the distance between the transmitting vehicle and the receiving vehicle. The numerical analysis shows that co-channel interference and signal fading significantly affect inter-vehicle connectivity.

Novel Emergency Message Dissemination in Vehicular Networks

The number of vehicles has increased proportionally over the last couple of times and this number is rising due to the increase in population extension and the number of vehicles that are manufactured every day. The high business viscosity leads to several problems, from which effectively propagating emergency messages is a major concern. VANETs (Vehicular Ad-hoc Networks), it is a vehicle networks of digital communication between cars, trucks, and also roadside units like antennas & buildings. In VANETs, significant challenges are faced, while disseminating the message across the network. The major challenges are the broadcast storm problem, hidden node problem, and packet collisions. We propose an Effective Emergency Message Dissemination Scheme (EEMDS) for urban VANETs. The scheme is grounded on our mobility metrics to escape communication outflow and to maintain the stability of the cluster structure. Every vehicle takes into account its direction and path loss factor for opting appropriate cluster head. Also, we introduce estimated link stability to choose a suitable dependent vehicle (an intermediary that communicates between multiple clusters) that reduces the number of retransmits and communication traffic in the network. Simulation results covey that NEMDS provides an acceptable end-to-end detention, information coverage, & packet delivery ratio compared to the eminent Emergency Messages dissemination schemes.

Enhanced UAV-aided vehicular delay tolerant network (VDTN) routing for urban environment using a bio-inspired approach

The evolution of VDTN routing came to solve the problem of routing in sparse Vehicular Ad-hoc Networks (VANETs). Recently, the implication of Unmanned Aerial Vehicles (UAVs) in VANET communication has gathered quicker information dissemination than Roadside Units (RSUs) in urban VANETs, where ground vehicles’ mobility is restricted by the topology of city roads. Gradually, UAVs are emerging for VDTNs: UAV-aided VDTN (UVDTN) routing field has been introduced for sparse areas in order to reduce the network gaps between Vehicle-to-Vehicle (V2V) connections. Meanwhile, the conventional UVDTN routing protocols expose the short contact opportunity time in the case of Vehicle-to-UAV (V2U) and UAV-to-Vehicle (U2V) connections. This constraint entails more congested bundles’ flooding rates and a higher number of lost bundle copies compared to V2V-based forwarding. In this paper, a bio-inspired UVDTN routing protocol is conceived to improve the bundles’ forwarding between ground vehicles and UAVs in terms of flooding optimization and Quality-of-Service (QoS) performances for urban VANET environments. For this purpose, a swarm-inspired approach called the Social Spider Optimization (SSO) is proposed. SSO seeks to find a better selection of next Store-Carry-and-Forward (SCF) relay nodes specifically for V2U and U2V connections. In order to control the bundle replication rate and enhance bundles’ delivery ratio and delay, the proposed bio-inspired UVDTN protocol adjusts the SCF selection decision. The latter is based on predefined historical knowledge-based forwarding parameters and urban geographic topology information. The proposed bio-inspired routing protocol is simulated using the Opportunistic Network Environment (ONE) simulator and compared to a few VDTN and UVDTN routing protocols.

A Robust Emergency Messages Routing Scheme for Urban VANETs

Vehicular ad-hoc networks (VANETs) play an essential role in enhancing transport infrastructure by making vehicles intelligent and proficient in preventing traffic fatalities. Direction-based greedy protocols pick the next route vehicle for transmitting emergency messages (EMs) depending upon the present location of adjacent vehicles towards sink vehicles by using an optimal uni-directional road traffic approach. Nevertheless, such protocols suffer performance degradation by ignoring the moving directions of vehicles in bi-directional road traffic where topological changes happen continuously. Due to the high number of vehicles, it is essential to broadcast EMs to all vehicles to prevent traffic delays and collisions. A cluster-based EM transmitting technique is proposed in this paper. For urban VANETs, this paper pioneers the clustering of bi-directional road traffic for robust and efficient routing of EMs. In this regard, this paper introduces a routing protocol, namely, the bi-directional urban routing protocol (BURP). In addition to the paths and relative locations of vehicles, BURP takes account of the distance parameter by using the Hamming distance function to determine the direction of motion of vehicles and communicates EMs through the cluster head (CH). A modified k-medoids algorithm is presented for the clustering of bi-directional road traffic. A median method is presented for selecting CH to ensure the long-running of a cluster. Simulation results show that BURP provides enhanced throughput, a maximized packet delivery ratio, low energy consumption, and network delay relative to eminent routing protocols.

Payoff-based Dynamic Segment Replication and Graph Classification Method with Attribute Vectors Adapted to Urban VANET

Due to the number of constraints and the dynamic nature of vehicular ad hoc networks (VANET), effective video broadcasting always remains a difficult task. In this work, we proposed a quality of video visualization guarantee model based on a feedback loop and an efficient algorithm for segmenting and replicating video segments using the Payoff-based Dynamic Segment Replication Policy (P-DSR). In the urban VANET environment, P-DSR is defined by taking into account the position of the vehicles, the speed, the direction, the number of neighboring vehicles, and the reputation of each node to stabilize the urban VANET topology. However, the management of various load control parameters between the different components of the urban VANET network remains a problem to be studied. This work uses a multi-objective problem that takes the parameters of our algorithm based on the Graph Classification Method with Attribute Vectors (GCMAV) as input. This algorithm aims to provide an improved class lifetime, an improved video segment delivery rate, a reduced inter-class overload, and an optimization of a global criterion. A scalable algorithm is used to optimize the parameters of the GCMAV. The simulations were carried out using the NetSim simulator and Multi-Objective Evolutionary Algorithms framework to optimize parameters. Experiments were carried out with realistic maps of Open Street Maps and its results were compared with other algorithms such as Seamless and Authorized Multimedia Streaming and P-DSR. The survey suggests that the proposed methodology works well concerning the average lifetime of the inter-classes and the delivery rate of video segments.

Multiple intersection selection routing protocol based on road section connectivity probability for urban VANETs

An efficient routing protocol is of great significance to improve vehicular ad hoc networks (VANETs) performance. However, due to complex road conditions, intermittent connectivity among vehicles and rapid changes of network topology, how to design an efficient routing protocol in an urban environment to transmit the data packet to the destination remains a challenging problem. In this paper, we propose a multiple intersection selection based on road section connectivity probability routing protocol for vehicle–vehicle (V2V) communication in urban VANETs, which considers the vehicle distribution influenced by traffic lights. First, we present a method to calculate the road section connectivity probability of a two-way lane with traffic lights consideration. Then, we establish an optimization model to select the optimal road path from the source node to the destination node based on the road section connectivity probability. Furthermore, we analyze the relay node selection on the road section after the optimal road path is determined, which discusses the number of neighbor vehicles in the communication range of the vehicle carrying packets and jointly considers the position, speed and direction of vehicles. Simulation results demonstrate that our proposed routing protocol increases the packet delivery rate and reduces the end-to-end delay.

Stable coalitions for urban-VANET: A hedonic game approach

This paper tackles the problem of improving the coalitions' stability for Quality of Service Optimized Link State Routing (QoS-OLSR) protocol in urban Vehicular Ad-hoc Networks (VANETs). VANETs have introduced communication among vehicles for the Intelligent Transportation System (ITS) allowing several safety and user-oriented applications to be implemented in an ad-hoc manner. The routing protocols in VANET play a significant role in the delivery of data packets for such applications. However, the rapid changes in the topology of urban-VANET affect the relative stability among moving vehicles and consequently cause a high drop in the network performance. Several works considered urban metrics and game theory models for stable relay selection and cluster formation where the stability of a relay is measured compared to all the neighbor vehicles rather than selection based on relative stability between a vehicle and its relay. In addition, some works proposed matching theory that focuses on the individual preferences of players, to introduce stability. Alternatively, the Hedonic game considers preferences and enhances stability through joining coalitions to improve the overall utility of all participating members in each coalition. Therefore, in this paper, we propose a two-phase Hedonic game model that improves the coalitions' stability for QoS-OLSR in urban-VANET by considering the urban characteristics such as traffic lights, intersections, and lanes' directions. Players play the game in an ad-hoc manner by exchanging a set of messages and join coalitions that include relatively more stable members. Hence, the relative stability among coalition members is the utility of the coalition. A coalition utility depends on the urban characteristics which affect several metrics such as the time to leave the street and the probability of the direction to leave the nearest intersection. Simulations, that are conducted using SUMO and NS3, show high network performance in terms of packet delivery ratio, throughput, and end-to-end delay compared to benchmark protocols.

EEMDS: An Effective Emergency Message Dissemination Scheme for Urban VANETs.

In Vehicular Adhoc Networks (VANETs), disseminating Emergency Messages (EMs) to a maximum number of vehicles with low latency and low packet loss is critical for road safety. However, avoiding the broadcast storm and dealing with large-scale dissemination of EMs in urban VANETs, particularly at intersections, are the challenging tasks. The problems become even more challenging in a dense network. We propose an Effective Emergency Message Dissemination Scheme (EEMDS) for urban VANETs. The scheme is based on our mobility metrics to avoid communication overhead and to maintain a stable cluster structure. Every vehicle takes into account its direction angle and path loss factor for selecting a suitable cluster head. Moreover, we introduce estimated link stability to choose a suitable relay vehicle that reduces the number of rebroadcasts and communication congestion in the network. Simulation results show that EEMDS provides an acceptable end-to-end delay, information coverage, and packet delivery ratio compared to the eminent EM dissemination schemes.

A New QoS Adaptive Multi-path Routing for Video Streaming in Urban VANETs Integrating Ant Colony Optimization Algorithm and Fuzzy Logic

The multi-path transmission is an appropriate transmission method for high data rate packets like video streaming. To provide video streaming with high quality, the video packets are divided into different frames for transmitting through various paths. Nevertheless, regarding the results of numerous inherent features of vehicular ad hoc networks (VANETs), designing a stable and efficient routing protocol is difficult for various applications of VANETs. In particular, the dynamic nature of topology and intermittent connectivity make maintaining the quality of service (QoS) task very difficult. To provide QoS to entertainment applications and traffic safety in VANET, we offer a routing protocol based on the adaptive junction with QoS support regarding packet delivery ratio (PDR), connectivity probability, and delay. To establish the best QoS routes, we considered the equivalent routing problem as the optimization problem and then proposed an algorithm based on ant colony optimization for solving it. Moreover, a fuzzy logic-based algorithm was employed to select the best next-hop vehicle by incorporating multiple metrics associated with the vehicle’s position, link quality, and vehicle mobility. The transmission control protocol (TCP) and user datagram protocol (UDP) are the two most known transference layer protocols. In this study, we provide an adaptation of TCP and UDP protocols for video streaming in VANET. To indicate the behavior of our suggested method, the network simulator NS-2 is used for the simulation. The simulation findings show the efficiency of our proposed approach in comparison with the existing research works in terms of the average packet delivery ratio, end-to-end delay, overhead, and peak signal to noise ratio.

Clustering method and symmetric/asymmetric cryptography scheme adapted to securing urban VANET networks

Due to the number of constraints and the dynamic nature of vehicular ad hoc networks (VANET), effective information exchange always remains a difficult task. Management of various load control parameters between the different nodes of the urban VANET (UVANET) network makes the optimization is difficult. In this work, we use a multi-objective problem that takes the parameters of our algorithm based on the Graph Classification Method with Attribute Vectors (GCMAV) as input. This algorithm aims to provide an improved class lifetime, an improved information delivery rate, a reduced inter-class overload, and an optimization of a global criterion. A scalable algorithm is used to optimize the parameters of the GCMAV. Then, to address the performance and security challenges in the UVANET environment, we introduce an Efficient Key Management Scheme (KMSUNET) based on symmetric and asymmetric encryption. Our KMSUNET diagram takes into account the position of the vehicle nodes, the speed, the direction, the number of neighboring vehicle nodes, and the reputation of each node. The simulations were carried out using the NetSim simulator and Multi-Objective Evolutionary Algorithms (MOEA) framework to optimize parameters. Experiments were carried out with realistic maps of Open Street Maps and its results were compared with other algorithms. The survey suggests that the proposed methodology works well concerning the average lifetime of the inter-classes and the information's delivery rate.

A New Deployment Schema Using Dynamic Relay Vehicle to Improve VANETs Connectivity in Urban Environment

Vehicular ad-hoc network (VANETs) have emerged as promising technology to support traffic safety applications of intelligent transportation system (ITS). One of the most important challenges facing VANET is the connectivity, due to obstacles, high mobility, dynamic topology which leads to disconnection problem. Deploying road Sid unite (RSU) to improves VANET connectivity is considered as a highly cost solution. Previous researches suggested diverse RSU deployment schemes and algorithms to solve the RSU deployment issue in order to achieve better network connectivity with minimum number of RSU. In this paper we propose dynamic relay node as replacement to RSU with zero infrastructure. It’s Using key metrics of interest (such as connection duration, re-healing time, receiving time) we provide thorough visualization for network connectivity of urban VANETs with dynamic relay node. It is not only a low-cost solution, but it is practical solution since it does not require RSU installation or maintenance. Simulations are carried out in ns2 to evaluate the performance of dynamic relay node in urban environment. The proposed scheme proves its efficiency through increasing the vehicle density in the road and by increasing relay vehicle velocity. The result shows that the proposed scheme improve the network connectivity as the number of relays increased up to four dynamic relay nodes.

Road network layout based multi-hop broadcast protocols for Urban Vehicular Ad-hoc Networks

In recent years, the decentralized wireless Vehicular Ad hoc Networks (VANETs) have emerged as a key technology for Intelligent Transportation Systems (ITS). The need for an efficient and reliable broadcast protocol, mainly in urban VANETs, is of great importance to support different services such as road safety, traffic efficiency, entertainment and advertisement. This paper proposes two new routing broadcast protocols: the Enhanced Counter-based broadcast protocol in Urban VANET (ECUV) and the Enhanced distance-based broadcast protocol in Urban VANET (EDUV). Both of them improve the distribution of data on urban VANETs. ECUV and EDUV use a road-network-topology-based approach to select a set of relay nodes with enhanced coverage capabilities during the data delivery in urban Vehicle to Vehicle (V2V) scenarios. They also improve the performance of the receiver-based protocols by alleviating the negative effect of their stochastic behavior. We study the behavior of these protocols with an analytical model, which shows that the enhanced versions reduce the transmission probability in high vehicle density to avoid the broadcast storm problem. Moreover, the obtained results proved that these proposed protocols increase the transmission probability in low vehicle density to satisfy the reachability requirement of data broadcasting. The network simulation results show clearly that ECUV and EDUV outperform other methods in terms of coverage capacity and efficiency.

A Novel Collaborative IoD-Assisted VANET Approach for Coverage Area Maximization

Internet of Drones (IoD) is an efficient technique that can be integrated with vehicular ad-hoc networks (VANETs) to provide terrestrial communications by acting as an aerial relay when terrestrial infrastructure is unreliable or unavailable. To fully exploit the drones’ flexibility and superiority, we propose a novel dynamic IoD collaborative communication approach for urban VANETs. Unlike most of the existing approaches, the IoD nodes are dynamically deployed based on current locations of ground vehicles to effectively mitigate inevitable isolated cars in conventional VANETs. For efficiently coordinating IoD, we model IoD to optimize coverage based on the location of vehicles. The goal is to obtain an efficient IoD deployment to maximize the number of covered vehicles, i.e., minimize the number of isolated vehicles in the target area. More importantly, the proposed approach provides sufficient interconnections between IoD nodes. To do so, an improved version of succinct population-based meta-heuristic, namely Improved Particle Swarm Optimization (IPSO) inspired by food searching behavior of birds or fishes flock, is implemented for IoD assisted VANET (IoDAV). Moreover, the coverage, received signal quality, and IoD connectivity are achieved by IPSO’s objective function for optimal IoD deployment at the same time. We carry out an extensive experiment based on the received signal at floating vehicles to examine the proposed IoDAV performance. We compare the results with the baseline VANET with no IoD (NIoD) and Fixed IoD assisted (FIoD). The comparisons are based on the coverage percentage of the ground vehicles and the quality of the received signal. The simulation results demonstrate that the proposed IoDAV approach allows finding the optimal IoD positions throughout the time based on the vehicle’s movements and achieves better coverage and better quality of the received signal by finding the most appropriate IoD position compared with NIoD and FIoD schemes.

Fire Controlling Under Uncertainty in Urban Region Using Smart Vehicular Ad hoc Network

Every year thousands of urban and industrial fires occur, which leads to the destruction of infrastructure, buildings, and loss of lives. One of the reasons behind this is the delayed transmission of information to the fire station and the nearer hospitals for ambulance service as the transmission of information is dependent on observer at the location where the fire is caught and cellular network. This paper proposed an automated routing protocol for the urban vehicular ad-hoc network to send the information from the location where the fire is caught to the nearest fire stations and hospitals with optimum service time. This transmission of information involves Road Side Unit (RSU) at the junction and the vehicles present in the transmission path. Selection of route to transmit faulty vehicle information from the RSU to the required faulty vehicle is based on a parameter called path value. The computation of path value is done by the attributes such as expected End To End (E2E) delay, the shortest distance to destination, the density of vehicle between the junctions, and attenuation. From the current junction, the selection of the next junction is based on minimum path value. The proposed routing protocol considers the performance parameters such as E2E delay, total service time (TST), number of network fragments or network gaps, number of hops, and attenuation for the propagation path for the evaluation of the proposed methodology. The proposed routing algorithm is implemented through OmNet++ and SUMO. Results obtained for the proposed routing protocol is compared with three existing VANET protocols (GSR, A-STAR, and ARP) in terms of End To End delay, number of hops, number of vehicular gaps, and Total Service Time (TST).