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Vehicular Ad Hoc Networks (VANETs), Past Present and Future: A survey
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Vehicular Ad Hoc Networks (VANETs) are classified as a subset of Mobile Ad Hoc Networks (MANETs). VANETs have the potential of improving road safety and providing travelers comfort. This network rehearses moving cars as nodes in a network to create a mobile network. As a component and concrete application of an ITS inter vehicle communication gained attention from researchers, academics and industry leaders, especially in US, EU and Ja-pan [7]. Intelligent Transportation System (ITS) enables coordinated traffic management, like advanced traveler information services, Vehicle tracking and Autonomous vehicle safety audits etc. In this research paper we tried to present a thorough survey of VANETs.
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... However, the EECP-MFO algorithm considers two additional factors, namely the energy level and the distance between the neighbors, to select the ideal CH. EECP-MFO extends the lifetime of a cluster while simultaneously reducing its energy usage [14][15][16]. It also saves energy by efficiently choosing the transmission power of nodes according to operational needs, reducing the network load [16][17][18][19]. ...
... EECP-MFO extends the lifetime of a cluster while simultaneously reducing its energy usage [14][15][16]. It also saves energy by efficiently choosing the transmission power of nodes according to operational needs, reducing the network load [16][17][18][19]. In terms of cluster construction time, cluster longevity, the chance of success [20][21][22][23][24], and energy consumption, EECP-MFO beats the ant colony optimization [17,20], PSO-particle swarm optimization [18], and grey wolf optimization-based clustering models [14,25]. ...
... 1. Due to the high mobility of FANET nodes, the network's topology changes more frequently than the network itself [16,19,23]. A typical MANET or VANET network topology is shown in Figure 4. 2. There are now many ad hoc networks striving to connect. ...
FANET (flying ad-hoc networks) is currently a trending research topic. Unmanned aerial
vehicles (UAVs) have two significant challenges: short flight times and inefficient routing due to low battery power and high mobility. Due to these topological restrictions, FANETS routing is considered more complicated than MANETs or VANETs. Clustering approaches based on artificial intelligence (AI) approaches can be used to solve complex routing issues when static and dynamic routings fail. Evolutionary algorithm-based clustering techniques, such as moth flame optimization, and ant colony optimization, can be used to solve these kinds of problems with routes. Moth flame optimization gives excellent coverage while consuming little energy and requiring a minimum number of cluster
heads (CHs) for routing. This paper employs a moth flame optimization algorithm for network building and node deployment. Then, we employ a variation of the K-Means Density clustering approach to choosing the cluster head. Choosing the right cluster heads increases the cluster’s lifespan and reduces routing traffic. Moreover, it lowers the number of routing overheads. This step is followed by MRCQ image-based compression techniques to reduce the amount of data that must be transmitted. Finally, the reference point group mobility model is used to send data by the most optimal path. Particle swarm optimization (PSO), ant colony optimization (ACO), and grey wolf optimization (GWO) were put to the test against our proposed EECP-MFO. Several metrics are used to gauge the efficiency of our proposed method, including the number of clusters, cluster construction time, cluster lifespan, consistency of cluster heads, and energy consumption. This paper demonstrates that our proposed algorithm performance is superior to the current state-of-the-art approaches using experimental results.
... A new function has been proposed in [21] to guarantee better communication between vehicle nodes without loops. The proposed BABC (binary artificial bee colony) structure has been evaluated to give better results compared to Kruskal's algorithm [22], but only the V2R mode is tested. ...
... The increase in traffic generally leads to frequent changes in the network topology, however, SAMNET creates stable Initialize the regression function given in (23). 4ŵ (1) = 1 5 for t=2 to P do 6 N ← card ξ t 7 for j=1 to N do 8 Use equation (21) to calculate the similarity rate τ t, j 9 if τ t, j < λ th then Adapt new parameters of R t S as shown in (29) 20ŵ (t) ← S 21 else if card ξ S ≥ 2 then 22 As shown in expression (31), calculate χ merg clusters 23 For all traffic data in ξ S , use the SKR method to calculate R merg 24 Adjust ξ t , X t and T t based on expression (33) clusters that can guarantee sufficient connectivity and a reliable connection. ...
Nowadays, vehicle ad hoc networks (VANET) are becoming one of the trends that motivate many service providers in urban areas. In this work, we take into account the random and continuous evolution of traffic in the VANET environment. We adopt a system to model the mode of evolution based on commutation. The proposed system is defined as a finite collection of linear submodels. Thus, for each subsystem, it is necessary to identify the discrete state and to establish a specific sub-model to model the overall system. However, according to recent studies, the adoption of an efficient VANET clustering algorithm can promote road safety, provide a means of entertainment for passengers, and promote message routing. In this article, a clustering algorithm based on a Self-Adaptative Multi-Kernel clustering for urban VANET (SAMNET) is also provided. SAMNET is based on a set of measurement data, representing the unpredictable density of vehicle nodes, acceleration or deceleration, and the limited radio range of the communication scheme used. The proposed algorithm takes advantage of the concept of identifying these data generated by linear sub-models which communicate through an unpredictable dynamic switching. It is a self-adapting clustering algorithm that consists of modeling each sub-model based on a linear regression function. SAMNET is broken down into three stages: (i) initialization of clusters, (ii) adaptation of clusters, (iii) fusion of clusters. To assess the comparative effectiveness of SAMNET, many experiments are carried out. The results obtained show that the proposed methodology provides almost optimal results and works well with regard to the average lifetime of the clusters and the data delivery rate.
... Point-to-point or local communication, however, is ineffective when a vehicle needs to communicate with out-ofrange vehicles or obtain information about distant events; as a result, the vehicle should use V2I communication. Therefore, RSUs collaborate with OBUs and other infrastructures to improve all vehicles' VANET communication capabilities [17] [18]. ...
... Il fournit une faible latence avec un débit de La génération sans fil cellulaire (G) se réfère généralement à un changement de la nature du système, de la vitesse, de la technologie et de la fréquence. Chaque génération a des normes, des capacités, des techniques et de nouvelles caractéristiques qui la différencie de la précédente[25]. Les réseaux cellulaires sans fil sont développés depuis les premiers systèmes de téléphonie mobile. Depuis l'introduction du premier système 1G en 1981, les connexions mobiles ont atteint des milliards, avec une nouvelle génération mobile apparaissant tous les dix ans environ[26]. ...
Les réseaux ad hoc véhiculaires (VANETs) sont constitués par un ensemble de véhicules qui échangent des données de sécurité et de confort même s’ils ne sont pas toujours directement à portée radio.Les problèmes liés aux réseaux VANETs ne sont pas encore tous résolus. Dans ce contexte, et dans le but de maximiser la stabilité dans ce type de réseaux, nous proposons différentes contributions pour assurer le routage en combinant les métaheuristiques et la technique de clustérisation.Tout d’abord, nous présentons un modèle de routage utilisant l’algorithme de clustérisation le plus efficace k-medoids. Ensuite, nous proposons plusieurs améliorations en utilisant les métaheuristiques, plus précisément les algorithmes génétiques, la recherche tabou et la recherche par dispersion. Enfin, nous proposons une application réelle de communication entre trois robots mobiles dans les zones non couvertes par le réseau VANET.A l’aide de diverses métriques, des simulations extensives montrent que nos contributions donnent de bons résultats par rapport à d’autres modèles conçus dans le même but.
... A node with the highest weight will be elected as a CH. Bilal et al. [13] and Rizwan et al. [14] also discussed the future direction of ad-hoc networks by using the different nature of algorithms. These suggestions are also based on the mobility pattern of nodes. ...
Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.
Vehicular ad hoc network (VANET), a subclass of mobile ad hoc networks (MANETs), is a promising approach for future intelligent transportation system (ITS). These networks have no fixed infrastructure and instead rely on the vehicles themselves to provide network functionality. However, due to mobility constraints, driver behavior, and high mobility, VANETs exhibit characteristics that are dramatically different from many generic MANETs. This article provides a comprehensive study of challenges in these networks, which we concentrate on the problems and proposed solutions. Then we outline current state of the research and future perspectives. With this article, readers can have a more thorough understanding of vehicle ad hoc networking and the research trends in this area
Recent advances in wireless communications technology and car industry made it possible to consider wireless Ad-hoc (or mixed Ad-hoc/infrastructure) networks, providing connectivity among vehicles on the road. Such network, often referred to as VANET (Vehicular Ad-hoc Network) is seen to be one of the most valuable concept for improving efficiency and safety of the future transportations, as well as boosting operators' revenue. Thus, several ongoing research projects supported by industry, governments and academia, establishing standards for VANET networks. This paper covers current research challenges and future applications for such networks, discusses possible deployment scenarios and provides some insights to the state-of-the-art of the current standardization of interfaces and protocols on a global scale.
Some of the significant advancements and challenges faced in intelligent vehicle area networks (VAN) in the US are discussed. The main focus is on the latest developments of intelligent transportation systems (ITS) for intra-vehicle and inter-vehicle-area-networks to assist driver safety. Intra (In-Vehicle) VAN are becoming necessary components of smart vehicle system research. These networks deal with the data communication network of onboard equipment (OBE) for assessing a driver's behavior or a vehicle's performance. Two vehicle safety techniques, such as passive and active are being employed and devised in vehicles to achieve these objectives. Passive vehicle safety includes a set of tools or devices such as seatbelts or air bags that improve safety in the event of an accident. Active vehicle safety techniques consist of a variety of techniques such as on-board driver assistance tools, lane-keeping or congestion control tools, and others.
This article presents a comprehensive survey of the state-of-the-art for vehicle ad hoc networks. We start by reviewing the possible applications that can be used in VANETs, namely, safety and user applications, and by identifying their requirements. Then, we classify the solutions proposed in the literature according to their location in the open system interconnection reference model and their relationship to safety or user applications. We analyze their advantages and shortcomings and provide our suggestions for a better approach. We also describe the different methods used to simulate and evaluate the proposed solutions. Finally, we conclude with suggestions for a general architecture that can form the basis for a practical VANET.
Inter-vehicle communication (IVC) systems (i.e., systems not relying on roadside infrastructure) have the potential to radically improve the safety, efficiency, and comfort of everyday road travel. Their main advantage is that they bypass the need for expensive infrastructure; their major drawback is the comparatively complex networking protocols and the need for significant penetration before their applications can become effective. In this article we present several major classes of applications and the types of services they require from an underlying network. We then proceed to analyze existing networking protocols in a bottom-up fashion, from the physical to the transport layers, as well as security aspects related to IVC systems. We conclude the article by presenting several projects related to IVC as well as a review of common performance evaluation techniques for IVC systems.
Intervehicle communication (IVC) networks, a subclass of mobile ad hoc networks (MANETs), have no fixed infrastructure and instead rely on the nodes themselves to provide network functionality. However, due to mobility constraints, driver behavior, and high mobility, IVC networks exhibit characteristics that are dramatically different from many generic MANETs. This paper elicits these differences through simulations and mathematical models and then explores the impact of the differences on the IVC communication architecture, including important security implications.
As a component of the intelligent transportation system (ITS) and one of the concrete applications of mobile ad hoc networks, inter-vehicle communication (IVC) has attracted research attention from both the academia and industry of, notably, US, EU, and Japan. The most important feature of IVC is its ability to extend the horizon of drivers and on-board devices (e.g., radar or sensors) and, thus, to improve road traffic safety and efficiency. This paper surveys IVC with respect to key enabling technologies ranging from physical radio frequency to group communication primitives and security issues. The mobility models used to evaluate the feasibility of these technologies are also briefly described. We focus on the discussion of various MAC protocols that seem to be indispensable components in the network protocol stack of IVC. By analyzing the application requirements and the protocols built upon the MAC layer to meet these requirements, we also advocate our perspective that ad hoc routing protocols and group communication primitives migrated from wired networks might not be an efficient way to support the envisioned applications, and that new coordination algorithms directly based on MAC could be designed for this purpose.
In this paper, we survey recent results in vehicular ad hoc networks (VANETs) data dissemination. We describe methods proposed to enforce dissemination scope such as geocast/broadcast and multicast. A growing category consisting of methods designed to achieve disruption tolerance in vehicular networks is presented. We describe the key ideas of representative technologies in each category. In addition, we consider location service and security issues that are crucial for data dissemination in VANET. We conclude by sharing our thoughts on further challenges. Copyright (C) 2009 John Wiley & Sons, Ltd.
In this paper, we survey recent results in VANET data dissemination. We structure the survey into three broad categories: geocast/broadcast, multicast, and unicast approaches; and describe key ideas of representative technologies in each category. In addition, we consider location service and security issues that are crucial for data dissemination in VANET. We conclude by sharing our thoughts on further challenges.
NCTUns is a novel network simulator and emulator that has many unique features over traditional network simulators and emulators. It is an open-source software running on Linux and is being used by many researchers in the world. According to the NCTUns official Web site (http://NSL.csie.nctu.edu.tw/nctuns.html), as of June 1, 2008, more than 11,546 people from 124 countries have registered and downloaded this software and these numbers are still fast increasing. In its 5.0 release, NCTUns provides a complete implementation of the IEEE 802.11(p)/1609 standards defined for wireless vehicular networks. In this paper, we present the capabilities of NCTUns 5.0 focusing on its uses for IEEE 802.11(p)/1609 wireless vehicular network researches.