Emergency Message Dissemination Research Articles

A hybrid-trust-based emergency message dissemination model for vehicular ad hoc networks

The security of data transmission is one of the focus issues in vehicular ad hoc networks (VANETs). The timely and effective dissemination of emergency messages can help drivers make intelligent decisions and improve road safety and traffic efficiency. However, malicious nodes in the network seriously interfere with the proper judgement of vehicles via data tampering or spreading false messages, which brings significant risks to traffic safety. In order to guarantee the security and reliability of data transmission, this paper proposes a hybrid-trust-based emergency message dissemination (HTEMD) model that effectively integrates entity trust into the data consistency evaluation. In the proposed model, for emergency messages from different sources, the receiver first calculates the probability of the event based on the sender’s entity trust and event status. Then, it uses the principle of information entropy to conduct consistent analysis of the results to help the vehicle make correct decisions. Afterwards, a series of simulations are conducted in four typical scenarios. The results show that the HTEMD model has strong environmental adaptability and robustness. Moreover, compared with other classical message dissemination models, the correct decision rate of the HTEMD model always remains above 80%, while other models drop to 75.5%, 63.2%, and 40.2%. The model proposed in this paper significantly outperforms the baseline model with a higher correct decision rate and resistance to attack.

Position-Based Emergency Message Dissemination Schemes in the Internet of Vehicles: A Review

Position-Based Emergency Message Dissemination Schemes in the Internet of Vehicles: A Review

Sdn based emergency message dissemination protocol for IoV-Fog networks

Sdn based emergency message dissemination protocol for IoV-Fog networks

A new delay-based broadcast suppression mechanism for efficient emergency messages dissemination in CAVs environment

Network congestion is a major issue affecting communications in Connected and Autonomous Vehicles (CAVs) under high vehicle density scenarios. The common idea used by emergency message broadcast protocols to overcome this challenge is to reduce the number of retransmissions. This is achieved by suppressing redundant retransmissions while maintaining broadcast reliability. In this paper, we analyze the problem of inaccurate suppression of redundant retransmissions in delay-based broadcast protocols and propose uHBS (unHurried Broadcast Suppression), a new more efficient broadcast suppression mechanism. uHBS avoids inaccurate decisions to suppress or forward an emergency message by considering the occurrence of duplicate receptions of this message and using an indication about the channel’s busy status. Next, we use the proposed uHBS mechanism as a basis for designing uHBS-DP (uHBS based Dissemination Protocol), a novel delay-based protocol for broadcasting emergency messages in urban vehicular networks. The simulation results show that uHBS-DP, using the proposed broadcast suppression mechanism, significantly improves the efficiency of emergency message broadcasting by ensuring high reliability with low broadcasting overhead, compared to two other variants of uHBS-DP that use conventional suppression mechanisms. Furthermore, the results show a substantial improvement, compared to a well known protocol, in terms of reduced collision ratio (up to 36.57%), lower dissemination delay (up to 19.17%) and reduced broadcast overhead (up to 19.28%).

Federated Learning-based Misbehaviour detection on an emergency message dissemination scenario for the 6G-enabled Internet of Vehicles

Federated Learning-based Misbehaviour detection on an emergency message dissemination scenario for the 6G-enabled Internet of Vehicles

Multi-hop emergency message dissemination through optimal cooperative forwarder in grid-based 5G-VANETs

Multi-hop emergency message dissemination through optimal cooperative forwarder in grid-based 5G-VANETs

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.

BEMD: Beacon-oriented Emergency Message Dissemination scheme for highways

Internet of Vehicle (IoV) dominates the traditional concept of Vehicular Ad-hoc Network (VANET) to boost the capabilities of Intelligent Transportation System (ITS). Frequent deployment of high-speed vehicles with more enhanced features by vehicle manufacturers expands the variety of challenges for ITS. This technological enhancement enables vehicles to exchange information across other vehicles and existing communication infrastructures. When a vehicle detects any critical trouble, it transmits an emergency message (EM) to nearby vehicles and to the traffic control office as an alert message to take necessary actions. The main issue is congestion if each vehicle is authorized to broadcast warning messages constantly. This congestion may lead to delays in the transmission of critical emergency messages with the redundant receiving of the same EM at the traffic control office. In our proposed scheme, called Beacon-oriented Emergency Message Dissemination (BEMD), we proposed a novel technique to enhance coverage and distribution of EM with the least delay. We aim to implement beacon-oriented communication for traffics with high mobility and sparse density on highways. We furthermore fixated on the least dependence of density on EM dissemination. As compared to the latest existing schemes, BEMD shows enhanced simulated results of more than 13%, 26% and 4% in terms of information coverage, delay and packet distribution ratio (PDR) respectively.

Mobile Edge-Based Information-Centric Network for Emergency Messages Dissemination in Internet of Vehicles: A Deep Learning Approach

Mobile Edge-Based Information-Centric Network for Emergency Messages Dissemination in Internet of Vehicles: A Deep Learning Approach

A scalable time-division-based emergency messages broadcast scheme for connected and autonomous vehicles in urban environment

Connected and Autonomous Vehicles (CAVs) technology promises to revolutionize the transportation sector by solving many safety and traffic efficiency challenges while significantly enhancing passengers' and drivers' comfort. Most of these applications are built upon multi-hop broadcast of information among vehicles, leading to an increased contention and thus higher collision probability due to the limited bandwidth available for vehicular communications. In this paper, we propose a novel Time-Division-based Broadcast (TDB) scheme to mitigate interferences originating from hidden nodes (i.e., vehicles) to meet the stringent safety applications requirements. Then, we use this broadcast scheme as a basis for designing a new efficient and scalable protocol for emergency messages dissemination in urban vehicular networks (UV-TDB: an Urban, Vehicular and Time-Division-based Broadcast protocol). The simulation experiments show that UV-TDB significantly improves the performance of multi-hop broadcast and outperforms two state of the art protocols in terms of the achieved reduction in broadcast overhead (up to 77.9%), packet collisions ratio (up to 93.5%), interference rate (up to 43.5%) and increase in message reception rate (up to 337.7%). The results highlight also that UV-TDB adapts better to varying levels of vehicle density, making it more scalable.

Reliable and Efficient Message Dissemination by Adaptive Relay Selection in Vehicular Networks

Successful message reception of an emergency event is the key objective of emergency message dissemination protocols in vehicular networks. This research paper proposes a new multi-hop data dissemination protocol for relay node selection for emergency events in vehicular networks. The proposed protocol is dynamically adaptive to vehicular density and link quality during the data dissemination process. Thus making it a viable solution for both practical scenarios. The protocol is evaluated by considering different vehicle density and network size. Simulation outputs confirm considerable performance improvements over existing distance-dependent protocols. In urban traffic density scenarios, over 20% improvements are achieved in delay performance to the furthest distance-based protocol with increased reliability and scalability in vehicular networks.

VP-CAST: Velocity and Position-Based Broadcast Suppression for VANETs

In the vehicular ad hoc networks (VANETs), minimizing the broadcast storm that arises due to message rebroadcast during emergency message dissemination in extremely mobile environments under sparse or dense networks is a significant challenge. Proper selection of rebroadcasting vehicles guarantees acceptable end-to-end delay, high delivery ratio, and efficient bandwidth utilization. To date, many protocols have been proposed to select an appropriate rebroadcasting vehicles based on vehicle position information only. However, such approaches neglect the fact that both vehicle velocity and position information can be utilized efficiently to alleviate rebroadcast message collisions and control bandwidth consumption. In this work, we present a new broadcast suppression protocol, named, velocity and position-based broadcast suppression for VANETs (VP-CAST), which can work in both sparse and dense network situations. VP-CAST does rely on periodic beacon messages, rather the position and velocity information of broadcasting vehicle are included in a broadcast message. Moreover, the transmission range of broadcasting vehicle is divided into dynamic time slots based on velocity and position information of broadcasting and receiving vehicles.The proposed scheme assigns shorter and dynamic waiting time to the vehicles moving at high velocities and located farther from the sender vehicle that eventually reduces both the message re-transmission delay and the number of rebroadcasting vehicles. The proposed protocol is compared with the DV-CAST in terms of end-to-end delay, message delivery ratio, and message overhead.

An Enhance the Performance of Mining Vehicular and Machinery Security Systems Using Artificial Intelligence in VANET Cloud Computing

Over the recent decades, incorporating Vehicular Ad-hoc Network (VANET) into Cloud computing plays a vital role, since it provides a reliable safety journey to vehicular drivers, passengers, etc. However, attaining security and emergency message dissemination is still major bottleneck in VANET combined Cloud, due to the dynamic nature of vehicles and wireless communication. Our major intention is to provide high level security in VANET-Cloud environment. In addition to it, we also reduce delay in emergency dissemination. Our proposed Delay aware Emergency Message Dissemination and Data Retrieval in secure (DEMD22RS) VANET-Cloud is composed of four sequential processes: Authentication, Clustering, Data Retrieval and Data dissemination. In regard to maintaining security for both Road Side Unit (RSU) and Vehicles, we propose Hash based Credential Authentication Scheme (HCAS) that affords authentication using Secure Hash Algorithm-3 (SHA-3) and Elliptic Curve Points (ECP). To sustain a stable cluster, Firm Aware Clustering Scheme (FACS) is pursued where Stud Krill Herd (SKH) algorithm is exploited. In the data retrieval process, cloud provides requested information to the RSU in encrypted form using the Twofish algorithm. RSU discover the path to deliver received data through executing Artificial Neural Network (ANN) algorithm. In order to diminish delay in emergency message dissemination, best disseminator is selected by cluster head using Fuzzy-Topsis (FT) algorithm. Our DEMD22RS VANET-Cloud network is implemented in Network Simulator 3 tool. Finally, the evaluation of DEMD22RS work performance is achieved by computing consequent metrics that are Throughput, Packet Delivery Ratio, Transmission delay, Average delay, Key generation time, Encryption time and Decryption time.

A novel energy aware cluster based routing protocol for emergency message dissemination in vehicular adhoc networks

In Vehicular Adhoc Network (VANET), the typical topology variations produced by the highly mobile nature of vehicle poses major issues in data transmission. The mobility and location based data dissemination techniques could satisfy the requirements of emergency message (EM) dissemination. It faces several issues in highway as well as urban roadways like minimum latency, highly secure, and scalable, which needs to be resolved. Generally, broadcasting protocols for VANET make use of beacon signals, which are distributed amongst the vehicles to attain information about the neighboring vehicles. With this motivation, this paper presents an energy aware cluster based routing protocol for the critical message dissemination (EAC-RPCMD) technique for VANET. The goal of the EAC-RPCMD technique aims to disseminate the EMs in the cluster based VANET environment. The EAC-RPCMD technique primarily designs an equilibrium optimizer based clustering (EOC) technique for the organization of vehicles into clusters. Besides, the manta ray foraging optimization (MRFO) algorithm based route selection (RS) technique, named MRFO-RS technique for optimal choice of routes to destination. Moreover, the EM dissemination scheme is also employed in the VANET. The performance validation of the EAC-RPCMD technique takes place and the results are inspected under several aspects.

PPTM: A Privacy-Preserving Trust Management Scheme for Emergency Message Dissemination in Space–Air–Ground-Integrated Vehicular Networks

Vehicular networks have tremendous potential to improve the road safety and traffic efficiency, and the adoption of the space–air–ground-integrated network (SAGIN) architecture in vehicular networks can greatly improve the performance of vehicular networks by leveraging the respective advantages of the space, air, and ground segments on coverage, flexibility, reliability, and availability, which results in space–air–ground-integrated vehicular networks (SAGIVNs). Trust management is an important tool for constructing trustworthy SAGIVNs, and privacy preservation is also a primary concern in SAGIVNs. They have conflicting requirements and a satisfactory balance between them is urgently required. In this article, we propose a novel privacy-preserving trust management (PPTM) scheme for the emergency message dissemination in SAGIVNs. The proposed scheme can realize precise trust management and strong conditional privacy preservation simultaneously with low communication overhead, and can provide strong applicability, strong robustness, and multiple other attractive features. Furthermore, the exhaustive theoretical analysis and simulation evaluation are detailed. The results reveal that the proposed scheme is significantly superior to the existing schemes in several aspects.

Efficient Message Dissemination on Curve Road in Vehicular Networks

Effective emergency message dissemination is a great importance on a specific road in vehicular networks (VN). The existing methods are not most efficient solutions for message dissemination on the curve road, which primarily focus on highway and urban road. In order to improve the efficiency of message dissemination on the curved road, the paper proposed a message dissemination method based on bidirectional relay nodes. The message can be disseminated in two directions simultaneously. The paper designed a relay node selection method based on the neighbor nodes’ coverage length of the road. Different waiting delays are assigned to the neighbor nodes according to the cover capability of the road in which the message has not arrived. Simulation results demonstrated that the efficiency of the proposed method is superior to the common solutions in terms of the contention delay and the propagation velocity.

A Blockchain Based Federated Learning for Message Dissemination in Vehicular Networks

Message exchange among vehicles plays an important role in ensuring road safety. Emergency message dissemination is usually carried out by broadcasting. However, high vehicle density and mobility lead to challenges in message dissemination such as broadcasting storm and low probability of packet reception. This paper proposes a federated learning based blockchain-assisted message dissemination solution. Similar to the incentive-based Proof-of-Work consensus in blockchain, vehicles compete to become a relay node (miner) by processing the proposed Proof-of-Federated-Learning (PoFL) consensus which is embedded in the smart contract of blockchain. Both theoretical and practical analysis of the proposed solution are provided. Specifically, the proposed blockchain based federated learning results in more vehicles uploading their models in a given time, which can potentially lead to a more accurate model in less time as compared to the same solution without using blockchain. It also outperforms other blockchain approaches in reducing 65.2% of time delay in consensus, improving at least 8.2% message delivery rate and preserving privacy of neighbor vehicle more efficiently. The economic model to incentivize vehicles participating in federated learning and message dissemination is further analyzed using Stackelberg game. The analysis of asymptotic complexity proves PoFL as the most scalable solution compared to other consensus algorithms in vehicular networks.

Speed and Position Aware Dynamic Routing for Emergency Message Dissemination in VANETs

Vehicular Ad hoc Networks (VANETs) can help reduce traffic-related accidents by broadcasting Emergency Messages (EMs) in advance between vehicles. Due to the high-speed mobility of VANETs and attenuation of the wireless signal, reliable and fast transmission of EMs is a challenging task. Such as the chosen next-hop vehicle may have driven away from the neighborhood of the sender before receiving the EM, and rerouting may increase the delay when the EMs encounter transmission failure. To this end, we propose a Speed and Position aware Dynamic Routing (SPDR) for EM dissemination in VANETs. First, we introduce a speed metric dynamic greedy routing to provide a dynamic hop-by-hop rebroadcast of the EM. SPDR dynamically shrinks the Routing Decision Area (RDA) range based on the velocity variance of candidate neighbors and prioritizes the farthest vehicle in the shrunk RDA as the optimal next-hop, enhancing the reliable transmission of EMs. Then, we present a collaborative forwarding strategy to enable candidate neighbors to collaborate in communication. In case of transmission failure, SPDR elects the candidate vehicle close to the destination as the forwarder to reduce rerouting. Simulations in a practical motorway scenario using NS-2 and VanetMobiSim show that SPDR outperforms the existing protocols in terms of message delivery ratio, network throughput, and average dissemination delay.

QoE Aware Video Streaming and Optimal Relay for Emergency Message Dissemination in Graph Based VANET

Vehicular Ad hoc Network (VANET) is a dynamic network environment that supports the transmission of any type of data that varies with size and delay constraints. VANET also enables to aid safety message forwarding in case of emergency by means of data dissemination. The major problematic issues in routing and data dissemination are delay and broadcast storm. With the advancements in VANET technology not only normal traffic data transmission but also video streaming is transmitted while the delay constraint has to be very less for video streaming. This article addresses these two problems by designing a graph aware network management for emergency message dissemination by selecting an optimal relay using multi-objective shuffled shepherd optimization algorithm that computes degree, goodness, waiting time, transmission range and link utility. Graph is constructed with the link stability, signal strength, distance and speed between vehicles. The selected relay vehicle from the graph is responsible to disseminate the safety message, which reduces the broadcast storm. The use of reinforcement learning is able to select the most suitable low delay neighbors for video streaming. In routing, the normal traffic data transmission is performed which is tolerable to delay, so Type-2 fuzzy logic is used with dynamic belief entropy that defines routes with the computation of quality of forwarding, bandwidth, distance and hop counts. This proposed work is implemented on OMNeT++ simulator and the results show better performances than the existing work in terms of packet delivery ratio, end-to-end delay, duplicate packets, throughput, and frame loss.

A trust management framework using forest fire model to propagate emergency messages in the Internet of Vehicles (IoV)

Internet of Vehicles (IoV) finds a prime application in road safety via emergency message transmission which helps drivers take an intelligent decision on the road. However, as malicious nodes can pose serious challenges, particularly on highway traffic, trust management is essential for excluding malicious nodes from the network. In order to transfer emergency messages efficiently, we consider different communities among the nodes in the network based on their social activities and interests. In this paper, we propose a novel nature-inspired forest fire model for the selection of minimum number of broadcaster nodes in the network for the dissemination of emergency messages. The proposed model maps the spread of emergency messages in the network to the spread of wildfire in a forest, and the key factors for message transmission are established by analyzing the forest fire model. Finally, the proposed model decides whether or not to relay the message based on the nodes' trust value, which is calculated using behavioral parameters. Thus, all the nodes with less trust value can be considered as malicious nodes and effectively excluded from the network using the trust values. Experiments were carried out, and the findings revealed that the proposed system was very resilient to a variety of network conditions, and that the selected minimal number of special nodes was better capable of propagating the emergency message throughout the network.