Dynamic Vehicular Ad Hoc Networks Research Articles

Intelligent defense strategies: Comprehensive attack detection in VANET with deep reinforcement learning

Vehicular Ad Hoc Network (VANET) facilitates the exchange of vehicular information through Vehicle-to-Vehicle (V2V) communication, contributing to Cooperative Intelligent Transportation Systems (C-ITS). The transmitted messages among vehicles are vulnerable to various security threats executed by malicious insider nodes. The dynamic VANET necessitates context-aware solutions for detecting various security attacks. Existing learning and deterministic mechanisms showed high detection accuracy for attacks on which they were trained explicitly for large datasets. Therefore, we propose an intelligent framework utilizing Deep Reinforcement Learning (DRL) for attack detection in evolving scenarios and mitigate the need for extensive training datasets. Our approach employs a Deep Q Network (DQN) trained on a compact dataset encompassing multiple attacks. The trained model is then applied to an unknown and extensive dataset, detecting various attacks with high accuracy. Notably, the model autonomously updates itself upon observing changes in the network context. This framework represents a promising security solution that is effective and adaptable for V2V communication in VANET.

An Emergency Message Routing Protocol for Improved Congestion Management in Hybrid RF/VLC VANETs

Unexpected traffic incidents cause safety concerns and intense traffic congestion on crowded urban road networks. Vehicular ad-hoc network (VANET)-aided Intelligent Transport Systems (ITS) aim to mitigate these risks through timely dissemination of alert messages. However, conventional Radio frequency (RF) mobile ad-hoc routing protocols are ill-suited for dynamic VANET environments due to high mutual interference, packet collisions, high end-to-end delay from frequent route discoveries, and periodic beaconing requirements. Fortunately, the quickly emerging Visible Light Communications (VLC) provide complementary short-range connectivity with high bandwidth and low interference. This paper proposes an efficient adaptive routing protocol for emergency messages in dense VANET scenarios leveraging a hybrid RF/VLC system. When an incident or congestion happens, the source vehicle disseminates the information to the incoming vehicles as quickly as possible using a combination of VLC and RF communication networks. Multi-hop relays extend the connectivity if the direct links are blocked. The coverage area is partitioned into zones based on road segments, intersections, and traffic flows. The Road Side Units (RSU)s are intelligently assigned to zones and they analyze the historical traffic data to characterize each zone and decide a response strategy. We also propose a congestion detection scheme that utilizes traffic simulations to forecast the clearance times under different response strategies. The highest-scoring strategy is selected based on the predicted impacts on travel time, emissions, and driver stress levels. The proposed algorithm adaptively uses the selected strategy to proactively alleviate the predicted congestion through optimized routing and control. Overall, the protocol maximizes safety and efficiency during emergencies by leveraging the hybrid RF/VLC, incorporating real-time congestion forecasting and dynamic rerouting into the response strategies.

Environment-Aware Adaptive Reinforcement Learning-Based Routing for Vehicular Ad Hoc Networks.

With the rapid development of the intelligent transportation system (ITS), routing in vehicular ad hoc networks (VANETs) has become a popular research topic. The high mobility of vehicles in urban streets poses serious challenges to routing protocols and has a significant impact on network performance. Existing topology-based routing is not suitable for highly dynamic VANETs, thereby making location-based routing protocols the preferred choice due to their scalability. However, the working environment of VANETs is complex and interference-prone. In wireless-network communication, the channel contention introduced by the high density of vehicles, coupled with urban structures, significantly increases the difficulty of designing high-quality communication protocols. In this context, compared to topology-based routing protocols, location-based geographic routing is widely employed in VANETs due to its avoidance of the route construction and maintenance phases. Considering the characteristics of VANETs, this paper proposes a novel environment-aware adaptive reinforcement routing (EARR) protocol aimed at establishing reliable connections between source and destination nodes. The protocol adopts periodic beacons to perceive and explore the surrounding environment, thereby constructing a local topology. By applying reinforcement learning to the vehicle network's route selection, it adaptively adjusts the Q table through the perception of multiple metrics from beacons, including vehicle speed, available bandwidth, signal-reception strength, etc., thereby assisting the selection of relay vehicles and alleviating the challenges posed by the high dynamics, shadow fading, and limited bandwidth in VANETs. The combination of reinforcement learning and beacons accelerates the establishment of end-to-end routes, thereby guiding each vehicle to choose the optimal next hop and forming suboptimal routes throughout the entire communication process. The adaptive adjustment feature of the protocol enables it to address sudden link interruptions, thereby enhancing communication reliability. In experiments, the EARR protocol demonstrates significant improvements across various performance metrics compared to existing routing protocols. Throughout the simulation process, the EARR protocol maintains a consistently high packet-delivery rate and throughput compared to other protocols, as well as demonstrates stable performance across various scenarios. Finally, the proposed protocol demonstrates relatively consistent standardized latency and low overhead in all experiments.

Inspecting VANET with Various Critical Aspects – A Systematic Review

Due to its strategic significance in the area of smart transportation to facilitate Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication, Vehicular Ad Hoc Networks (VANETs) have grown very popular in recent years. The rapid increase in the number of vehicles on the road has also led to the development of heterogeneous, large-scale, and highly dynamic VANETs, which introduce difficulty to fulfill the stringent requirements, which include low latency, high mobility, top security, and massive connectivity of the 5G network. Research works in VANETs mainly focus on message transmission within strict delay requirements based on different applications, data privacy and security. In this respect, a number of studies have been carried out by the researchers that propose models and solutions linked to the enhancement of VANET from several aspects, including applications, Quality of Service (QoS), security, physical layer fading, Artificial Intelligence (AI) techniques, Medium Access Control (MAC), and routing protocols. These factors serve as the driving force for this study's thorough examination of VANETs, which includes information on specific applications, QoS, channel fading, MAC protocols, channel access mechanisms, routing protocols, security, and difficulties. None of the surveys in existence today address all critical aspects of VANET in a single survey. In this paper, a complete taxonomy of VANETs has been provided based on various issues. First, an overview of VANET is presented with different applications. Then, QoS in VANETs and different proposed MAC protocols are discussed. Channel fading and access mechanisms are presented. After that, routing protocols, security, and clustering in VANETs are provided. AI approaches proposed in VANET are also summarized. Finally, a discussion of future research direction for all aspects is presented. This article might be used as a guide or a point of reference while designing and creating applications, networking and communication systems, and data security for VANETs.

SPHA-VC: Secure passengers health assessment via vehicular communications

Passenger health evaluation is a vital aspect of smart city applications. Remotely monitoring driver and passenger health save lives. Vehicular Ad Hoc Network (VANET)-assisted Internet of Things (IoT) will be an excellent option in that periodic vehicle health information will be sent to a nearby medical Base Station (BS). VANET communications are in an open wireless channel, making them subject to attacks against patient privacy. VANET-based healthcare monitoring systems must provide timely supervision with end-to-end security. Providing cost-effective healthcare utilizing dynamic and vulnerable VANET connections is a smart city research challenge. We propose novel Secure Passengers Health Assessment via Vehicular Communications (SPHA-VC) protocol to provide Quality of Service (QoS) efficient emergency medical information transmission with high security and privacy preservation. The SPHA-VC is consisting of security and privacy preservation-aware routing algorithms for IoT-based passenger health assessment connected with the VANETs. First, we design a reliable route formation algorithm using Artificial Intelligence (AI). Second, we propose a lightweight cryptography mechanism to achieve secure end-to-end medical data transmission. The reliable routing formation algorithm using Fuzzy Logic (FL) is integrated with Elliptic Curve Cryptography (ECC)-based secure data transmission mechanism. SPHA-VC's purpose is to accomplish secure communications in IoT-enabled VANETs and vehicle privacy reserving to guard against various cyber security threats using new FL-based reliable route formation and ECC-based secure data transfer. The simulation results revealed the efficiency of the SPHA-VC compared to state-of-the-art methods.

A novel and lightweight wireless communication scheme for Vehicular Ad hoc Networks

Vehicular Ad hoc Network (VANET) has attracted more and more attention from academia and industry because of its self-organization, dynamics, and scalability. However, since the overwhelming majority of communication in VANET adopt wireless communication, which is vulnerable to attack, coupled with the high requirements of communication efficiency for dynamic VANET, the wide application of VANET still faces great challenges. In this paper, we propose a lightweight communication scheme (LWCS) suitable for VANET. The proposed scheme includes a lightweight authentication scheme and a one-to-many wireless communication scheme. The authentication model is based on ECDLP and message authentication code (MAC), which realizes mutual authentication and improves efficiency. The one-to-many communication model is different from the existing scheme using bilinear pairing. Instead, we take advantage of Chinese remainder theorem (CRT), so that the receiver can quickly reconstruct the key. Besides, the length of the ciphertext is not affected by the number of receivers. Security analysis shows that our scheme is secure under the assumptions that the IFP and ECDLP are intractable. Meanwhile, the proposed scheme satisfies multiple security requirements such as forward security, backward security and common attacks resistance. The performance analysis demonstrates theoretically and experimentally that our scheme is efficient compared with related schemes.

A VANET Collision Warning System with Cloud Aided Pliable Q-Learning and Safety Message Dissemination

Ease of self-driving technological developments revives Vehicular Adhoc Networks (VANETs) and motivates the Intelligent Transportation System (ITS) to develop novel intelligent solutions to amplify the VANET safety and efficiency. Collision warning system plays a significant role in VANET due to the avoidance of fatalities in vehicle crashes. Different kinds of collision warning systems have been designed for diverse VANET scenarios. Among them, reinforcement-based machine learning algorithms receive much attention due to the dispensable of explicit modeling about the environment. However, it is a censorious task to retrieve the Q-learning parameters from the dynamic VANET environment effectively. To handle such issue and safer the VANET driving environment, this paper proposes a cloud aided pliable Q-Learning based Collision Warning Prediction and Safety message Dissemination (QCP-SD). The proposed QCP-SD integrates two mechanisms that are pliable Q-learning based collision prediction and Safety alert Message Dissemination. Firstly, the designing of pliable Q-learning parameters based on dynamic VANET factors with Q-learning enhances collision prediction accuracy. Further, it estimates the novel metric named as Collision Risk Factor (CRF) and minimizes the driving risks due to vehicle crashes. The execution of pliable Q-learning only at RSUs minimizes the vehicle burden and reduces the design complexity. Secondly, the QCP-SD sends alerts to the vehicles in the risky region through highly efficient next-hop disseminators selected based on a multi-attribute cost value. Moreover, the performance of QCP-SD is evaluated through Network Simulator (NS-2). The efficiency is analyzed using the performance metrics that are duplicate packet, latency, packet loss, packet delivery ratio, secondary collision, throughput, and overhead.

PAS: Privacy-Preserving Authentication Scheme Based on SDN for VANETs

Privacy disclosure has become a key challenge in vehicular ad hoc networks (VANETs). Although IEEE, ERSI, etc. suggest that a pseudonym-based scheme is a solution, how to support pseudonym management and vehicle authentication is still an open issue. In this paper, a secure VANETs authentication scheme (PAS) is proposed, where software-defined network (SDN) is integrated as a suitable infrastructure to support anonymous authentication and pseudonym management, while removing the requirement for pseudonym certification in the dynamic VANETs environment. The security and performance analysis indicate that PAS is able protect the privacy of vehicles and has a high efficiency.

Importance of the Static Infrastructure for Dissemination of Information within Intelligent Transportation Systems

Intelligent transportation systems (ITS) are a today´s hot topic, especially in the context of the development of information technologies, which can be employed in transportation. Although the scope and the technical solution of these systems may vary, they are frequently based on VANET (Vehicular ad hoc network), i.e. a communication network, which is primarily generated among the moving subjects, which form ITS. Given the highly dynamic VANET, the questions are raised as to the data transmission. This paper is aimed to make a detail analysis of the communications within VANET using the simulation model, which includes the static infrastructure of ITS and to experimentally verify the impact of this infrastructure on the dynamics of information spreading in ITS. The authors present the results obtained from a few different scenarios, which have been tested.

Congestion-free routing based on a hybrid meta-heuristic algorithm to provide an effective routing protocol by analyzing the significant impacts of QoS parameters in a dynamic VANET environment

Abstract A definitive form of Mobile Ad-hoc Network (MANET) is the Vehicular Ad-hoc Network (VANET), which delivers data communication using wireless transmission with the collection of vehicular nodes in a vehicular environment. The main goal of this VANET is to improve the Quality of Service (QoS) which is road safety, environmental kindliness, and logistics in intelligent transport. Moreover, mobility and routing play an important challenge for information interchange to the process in the VANET environment. In developing countries, smart cities are encountering problematic traffic congestion. Furthermore, in cluster communications, stable cluster formation and maintenance with the guarantying QoS has always remained a great challenge. In order to overcome the above-mentioned issue, this article proposes a congestion-free routing process ensuring QOS parameters. The main objective of the proposed scheme is to analyze the impact of QOS parameters while choosing the best routing path in Vehicular communication. The scheme also introduces the Hybrid-Harris Hawks Black Widow optimization-based VANET (H-HHBW-VANET) algorithm to improve QoS for routing between nodes. This algorithm differs from other algorithms in terms of optimal solution generation, which makes it more efficient. The proposed work is implemented in the working platform of NS2 to analyze the parameters such as Drop, Delay, Energy Consumption, Throughput, and Fairness Index. The simulation results provide better QOS service in terms of low energy consumption with higher throughput and low delay.

A Partitioned DAG Distributed Ledger with Local Consistency for Vehicular Reputation Management

Vehicular reputation maintenance with distributed ledger is aimed at establishing trust among vehicles randomly meeting in a Vehicular Ad-hoc Network (VANET). It is, however, challenging in VANET, as congested areas in road networks, brought by traffic tides or accidents, challenge the ledger performance. Meanwhile, the reputation update is highly dependent on transaction consensus of the distributed ledger. To solve the problem, this paper proposes deploying directed acyclic graph- (DAG-) based distributed ledgers on vehicles, which use the vehicular distribution to adapt the unpredictable reputation update. Specifically, we first propose a partitioned DAG-based distributed ledger to manage vehicular reputation in partitioned VANET. Secondly, we introduce a novel reputation evaluation method to encourage vehicles to contribute to VANET interaction and ledger consensus maintenance, which can remedy the topology churn of the ledger network due to the mobility of VANET. Finally, we design a reputation update method based on the consistency of transactions in the partition to facilitate trust establishment. Experimental results on a real-world dataset show that the proposed ledger and reputation update method is effective and feasible in the large-scale dynamic VANET.

ICDRP-F-SDVN: An innovative cluster-based dual-phase routing protocol using fog computing and software-defined vehicular network

Over time, wireless technology is evolving impulsively. For the most part, studies presently focused on the telecommunication field. Vehicular Ad-hoc Network (VANET) is one of the leading genuine and appealing areas for Intelligent Transportation Systems (ITS) originators and organizations. Essentially, VANET is an ad-hoc network consisting of several vehicles that flow on the same road. The existence of such networks revolutionizes the wireless communication field. The immense increase in the number of smart vehicles throughout time is the reason behind the massive evolution in VANET technologies. VANETs requirements are evolving quickly, therefore, having more flexible, scalable, and well-connected routes in VANETs is becoming essential in any new routing protocol. Antiquated VANETs routing protocols and designs encounter very challenging technical, employment, and control problems with the evolution of VANETs requirements. This paper presents a new efficient routing protocol for VANETs, namely, Innovative Cluster-Based Dual-Phase Routing Protocol Using Fog Computing and Software-Defined Vehicular Network (ICDRP-F-SDVN) which utilizes state-of-the-art technologies to overcome the drawbacks of traditional VANETs routing protocols. The use of fog computing and Software-Defined Networks (SDN) combined in our protocol presents a robust new architecture that meets all the new requirements and overcomes challenges arising from technological development and rapid escalation in the number of smart vehicles. Additionally, we propose a novel clustering algorithm mainly for the reason of lessening the long-distance communications in each cluster. In conjunction with this clustering algorithm, we propose an efficient control overhead reduction mechanism, thereby lowering the messages' exchanges imposed. Interestingly, our proposed protocol is a dual-phase protocol with a 90% of SDN packet delivery ratio. In other words, when the SDN fails to deliver packets, traditional Ad-hoc On-Demand Distance Vector (AODV) handles them as a fallback mechanism. In this paper, the performance of ICDRP-F-SDVN is evaluated in terms of throughput and end-to-end delay and further compared with four closely related routing protocols, that are, Intersection Dynamic VANET Routing (IDVR), Vehicle Density and Load Aware (VDLA), Intelligent Routing Protocol Using Real-Time Traffic Information in Urban Vehicular Environment (IRTIV), and Greedy Perimeter Coordinator Routing (GPCR). In terms of control overhead, the comparison is conducted with Control Overhead Reduction Algorithm (CORA), Moving Zone-Based Routing Protocol (MoZo), Beaconless Routing Algorithm for Vehicular Environment (BRAVE), and Cluster-Based Directional Routing Protocol (CBDRP). Our proposed protocol has achieved impressive simulation results compared to previously mentioned protocols. In particular, the throughput is increased by 8277%, 64309%, 76235%, and 96053% while the end-to-end delay is reduced by 77.5%, 82.5%, 87.2%, 95.6% over IDVR, VDLA, IRTIV, and GPCR, respectively. Finally, the control overhead is lowered by 42.3%, 87%, 93.5%, 96.7% over that of CORA, MoZo, BRAVE, and CBDRP, respectively.

Dynamic Vehicular Communication using Gaussian Interpolation of Cluster Head Selection (GI-CHS)

Decentralized and centralized vehicular communication is investigated in this work using Gaussian interpolation function with cluster head (CH) selection technique. The work uncovered that the best communication approach is to use both centralized and decentralized vehicular communication as combining them will achieve a much more uniform results as a function of communication radius values and vehicular speed. It is also found that vehicular speed contributes negatively to the efficiency of data communication if the relative speed of the vehicles to the communication radius is limited by their ratios. Mathematical expression is presented that relates probability of successful transmission to communication radius for both centralized and decentralized techniques with data proving the importance of the spread parameter within the Gaussian interpolation in a tabulated form, and explained to prove the adaptability of the function used. It is also shown in this work that weights affecting CH selection, thus using Gaussian interpolation is proved to be important as a weighting function in an a adaptive and dynamic vehicular ad-hoc networks (VANETS) covering both vehicle to vehicle (V2V), and vehicle to infrastructure (V2I) communication through cluster head selection.

Strong key-insulated secure and energy-aware certificateless authentication scheme for VANETs

The rise of vehicular ad-hoc networks (VANETs) brings promise for guaranteeing road safety and improving traffic efficiency. Nevertheless, the pity is that the problems, such as messages authentication and privacy-preserving, that come with it seriously threaten the security and stability of the VANETs. For addressing these problems, in this paper, a pairing-free certificateless signature work for VANETs that supports parallel key-insulated is constructed. On the one hand, the presented work is constructed utilizing the elliptic curve rather than the costly pairing operation. In this way, each vehicle can generate or verify authentication message in a low energy consumption manner. On the other hand, the mechanism of parallel key-insulated is introduced in our proposed work where two helpers alternately assist the users for the periodical key updates, which can not only resist the key exposure but also reduce the risk of the helper’s secret key exposure. Considering possible key exposure in the high dynamic VANETs scenarios, our scheme is more stable and feasible for VANETs environments compared with the existing works. Finally, our work is proved to be strongly key-insulated secure under the discrete logarithm assumption in the random oracle model. Meanwhile, the detailed performance comparisons demonstrate that our work is energy efficient and practical for VANET.

Towards Fast and Reliable Multihop Routing in VANETs

In Vehicular Ad-hoc Networks (VANETs), fast and reliable dissemination of safety messages is a key step toward improving the overall road safety. In a highly dynamic VANET environment, safety message dissemination in a multi-hop manner is a challenging and complex problem that has gained significant attention recently. Many protocols and schemes have been proposed to efficiently share safety messages among vehicles. However, most existing techniques do not perform well under real-world traffic conditions, or perform adequately only under very limited scenarios and traffic conditions. This research proposes a highly efficient and reliable multi-hop broadcasting protocol, Intelligent Forwarding Protocol (IFP), that exploits handshake-less communication, ACK Decoupling, and an efficient collision resolution mechanism. In this research, IFP has been extensively studied and evaluated to establish its robustness and superiority over existing schemes. A key contribution of this paper is to present an in-depth analysis and optimization of IFP using theoretical modeling, thorough simulations, and extensive real-world experimentation. With IFP, the message propagation delay is significantly reduced and packet delivery ratio is drastically improved.

A reliable and efficient forwarding strategy in vehicular named data networking

Vehicular named data networking (VNDN) has the data-centric and in-network caching advantages that are in line with the requirements of multi-hop content retrieval in vehicular ad hoc networks (VANETs). Some current restrictive forwarding strategies utilize single-path forwarding to mitigate the Interest broadcast storm in VNDN. However, these strategies do not provide any reliable mechanism for Interest and Data forwarding to address the problem of low performance caused by the dynamic and unreliable VANETs communication environment. In this paper, we propose a packet forwarding strategy based on optimal and backup (PFOB) for VNDN. For Interest, PFOB establishes a single-path forwarding with high reliability and reachability by increasing the signal strength and node-degree criterion and retransmission mechanism. For Data, PFOB provides a reliable multi-path backup forwarding mechanism without additional network overhead. Simulation results show that PFOB can effectively improve the Interest satisfaction ratio, reduce the number of application retransmissions, and reduce the Interest satisfaction delay compared to the current strategies.

Semi-Markov model for vehicular green transmission

To integrate the Fifth Generation (5G) Vehicular ad hoc network (VANET) based clustering in cellular networks is useful for improving the throughput, saving scarce spectrum resources and preventing network congestion, as well as reducing the packet loss. However, it is a challenging problem to find an optimized clustering algorithm that has efficient stability adapting to dynamic VANETs. Considering the advantages of software-defined networking (SDN), an the 5G VANET system is employed with an SDN-enabled social-aware adaptive clustering algorithm (SESAC) which exploits a social pattern (i.e., future route) of every vehicle to optimize the stability of each cluster. To design the homogeneous Semi-Markov model for discrete time, which is based on the movement of each vehicle. The state transition probability and exact time probability dissemination are inputs while social patterns of each vehicle’s are output. The anticipated social patterns are generally used to make groups(cluster); where the vehicles are in a similar cluster, the cluster head (CH) will share a similar way (similar route). The cluster heads (CHs) are selected by some specific metrics such as inter vehicle distance, relative speed, and attributes of vehicle. Finally the SESAC algorithm is analyzed and compared with the conventional clustering algorithm.

A Novel Coordinated Medium Access Control Scheme for Vehicular Ad Hoc Networks in Multichannel Environment

Vehicular ad-hoc networks (VANETs) aim to provide efficient safety and infotainment services. Wireless Access in Vehicular Environments (WAVE), which is a standard designed specifically for VANETs, stipulates seven 10-MHz channels: one control channel (CCH) for safety message transmission and six service channels (SCHs) for service message transmission. However, providing reliable broadcasting of safety messages on the CCH and efficient coordination of vehicles for service message transmission across the multiple SCHs in highly dynamic VANET environment is a nontrivial problem. In this paper, we propose a coordinated, adaptive, and reliable multichannel medium-access control scheme for the VANETs (VCAR-MAC). In VCAR-MAC, a novel time-division multiple access (TDMA)-based scheme that considers real-world environmental conditions is proposed to identify every vehicle quickly so that a time slot on the CCH can be allocated efficiently for reliable safety message transmission. On the SCHs, VCAR-MAC provides a multi-SCH coordination scheme, which adaptively adjusts the SCH reservation period in order to fully utilize the channel bandwidth. Furthermore, a dynamic contention window (CW) mechanism is proposed, in which the initial CW size is adaptively optimized to maximize the number of successful SCH reservations, thereby maximizing the service message throughput. It has been proven via the mathematical analysis and simulation experiment that VCAR-MAC can significantly improve throughput and reduce delay for both safety and service messages.

A distributed time-limited multicast algorithm for VANETs using incremental power strategy

Efficient information dissemination is the pinnacle of Vehicular Ad-hoc Networks (VANETs). In case of delay-sensitive information such as safety-related messages, it is imperative to minimize the transmission delay and increase the message reliability in VANETs. In a previous work, we proposed a Time-Limited Reliable Broadcast Incremental Power (TRBIP) algorithm, which is a centralized heuristic to reduce transmission interferences for safety message dissemination in VANETs. By reducing the total transmission energy and the number of hops, TRBIP is able to reduce the transmission interference and thus-forth maximizes the reliability. Furthermore, in TRBIP, VANETs’ features such as vehicle mobility and frequent network fragmentation are also taken into account through store-carry-and-forward and the periodic multicast tree reconstruction strategies. However, multicast tree management is hard to maintain in urban environments due to the high density of nodes in VANETs (large trees), and is affected by the city streets organizations (intersections, roundabout, ... etc.). To address the afore-mentioned issues, in this paper we propose a Distributed version of Time-Limited Reliable Broadcast Incremental Power (DTRBIP) based on a road segmentation technique. Our proposal is extended to handle both delay-sensitive and delay-tolerant applications, and also both low and high dynamic VANETs scenarios respectively urban and highway environments. The results of the simulation conducted using NS-2 simulator advocate for the efficiency of our proposed method in term of reducing the total emission energy (at least by 150 dBm), reducing the average delay by 52%, increasing the packet delivery ratio by more than to 5%, and reducing the protocol overhead up to 3%. Obtained results show a clear enhancement compared to the previous solutions (i.e, RGRP-SA, RBIP, and TRBIP).

An Efficent Distributed Medium Access Control for V2I VANET

<p>Provisioning smart intelligent transport for vehicular ad hoc networks (VANETs) depends on dissemination of safety-related messages. The performance of VANET are highly affected due vehicle density, mobility and environmental condition. Recently several research has been under development, the design of a rapid, flexible, efficient and reliable medium access control (MAC) which address the precise constraint of smart intelligent transport system in the highly dynamic VANET environment. Extensive survey carried out in this work shows TDMA (Time division medium access) based MAC approach outperform carrier sense medium access/ collision avoidance CSMA\CA based approach. However, TDMA based approach incurs bandwidth wastages. To utilize bandwidth more efficiently cognitive radio (CR) technique is adopted for designing efficient MAC. However, the existing CR model incurs computation overhead and is not evaluated under different environmental condition such as rural, highway and urban (RHU). To overcome research challenges, this work present efficient decentralized distributed MAC (DMAC) that minimize collision and maximize throughput. Experiment are conducted to evaluate the performance of DMAC over state-of-art model in terms of throughput, success transmission and collision achieved. The outcome shows significant performance over state-of-model.</p>