A stable clustering algorithm based on affinity propagation for VANETs

Message dissemination issue in Vehicular ad hoc networks (VANETs) has been extensively studied both by computer simulations and experimental testbeds. Dedicated Short Range Communications (DSRC) technology has been standardized and used extensively as the main mechanism to support the message dissemination in VANETs. Nevertheless, other alternatives such as 3G/4G and WLAN have also been proposed to further assist with the message dissemination in VANETs. Due to the ubiquity of the smartphones, in this paper, we propose to leverage the use of smartphone to disseminate message in VANETs. An android-based system that uses WLAN ad-hoc technology is proposed. The feasibility and performance of the proposed system are investigated by simulations and the evaluation results show that given the high penetration of smartphones, the message dissemination can be done via the smartphones. Although the delay performance of the proposed system is inferior to DSRC-based system, the proposed system could still be very useful especially during the deployment stage of the DSRC technology (when the penetration rate of the technology is low).

Clustering is an effective mechanism to handle the fast changes in the topology of vehicular ad hoc networks (VANET) by using local coordination. Constructing stable clusters by determining the vehicles sharing similar mobility pattern is essential in reducing the overhead of clustering algorithms. In this paper, we introduce VMaSC: Vehicular Multi-hop algorithm for Stable Clustering. VMaSC is a novel clustering technique based on choosing the node with the least mobility calculated as a function of the speed difference between neighboring nodes as the cluster head through multiple hops. Extensive simulation experiments performed using ns-3 with the vehicle mobility input from the Simulation of Urban Mobility (SUMO) demonstrate that novel metric used in the evaluation of the least mobile node and multi-hop clustering increases cluster head duration by 25% while decreasing the number of cluster head changes by 10%.

IEEE- and ASTM-adopted Dedicated Short Range Communications (DSRC) vehicle safety-related communication services, which require reliable and fast message delivery, usually demand broadcast communications in vehicular ad hoc networks (VANETs). In this paper, we propose and justify a distributive robust scheme for DSRC one-hop safety-critical services. The new scheme enhances broadcast reliability using dynamic receiver-oriented packet repetitions and mini-slot within DIFS in IEEE 802.11 for one-hop emergency warning message dissemination. In addition, we investigate the reliability and performance of the proposed broadcast scheme for DSRC VANET safety-related services on highway analytically and by simulations. The analytic model accounts for the impact of the beacon message broadcast and the fading channel conditions on the reliability and performance.

Intelligent transportation system (ITS) is becoming an important part of our society. Vehicular ad hoc networks (VANETs), as one of the most fundamental technologies in ITS, have attracted great interests in both industry and academia. Due to ever-increasing data demands in VANETs, it is challenging to meet the requirements of ITS, especially for safety-critical applications. Fog computing is an emerging paradigm with the vision of supporting low communication latency, enhancing quality of service, and improving efficiency of network. Meanwhile, collision warning (CW) is critical for enhancing driving safety, which has stringent timing requirement. This work is dedicated to addressing safety issues in VANETs by designing and implementing a fog computing based collision warning system. Distinguishing from conventional cloud-based solutions, where vehicles have to communicate with servers resided in the backbone network via cellular network, the fog computing based system offloads communication and computation workloads to the infrastructures which are closer to end users (i.e., vehicles). In particular, the road-side unit (RSU) with dedicated short range communication (DSRC) interface and local computation unit is acted as the fog node, and it is installed at the road intersection. Then, vehicles approaching to the intersection will periodically report their status including positions, speed, driving direction and acceleration, to the RSU via DSRC. Based on the collected real-time status of surrounding vehicles, a collision prediction algorithm is designed and implemented in the computation unit of the fog node. The warning message will be triggered if potential collision is detected, and it will be transmitted to corresponding vehicles. For performance evaluation, we have implemented the system in realistic VANETs scenario. In addition, we have also implemented a cloud computing based CW system for performance comparison, where the LTE interface is adopted for transmitting messages to the cloud server, where the collision prediction algorithm is executed. Based on the field testing, we have demonstrated the superiority of the fog computing based CW system in terms of enhancing driving safety by providing real-time communication and distribute computation capabilities.

Vehicular ad hoc network (VANET) is a spontaneous creation of wireless network among vehicles to exchange data. Breakdown or interruption of communication is one of the most immediate and significant impacts of natural disasters. Clustering is one of the most common networking protocols for data propagation in those networks. The application of the clustering algorithm is effective in VANET because the algorithm makes it a more robust and scalable network. For stable cluster formation in VANET, some constraints such as vehicles' velocity and vehicles' separation distance must be considered while selecting the cluster head which is the node responsible for data propagation to the infrastructure. In damaged VANET, the cluster head might be unable to successfully transmit the packets to the infrastructure. In such cases, overlapping clusters with double cluster heads is one of the best solutions to guarantee successful packet delivery to the destination. One of the major challenges in clustering is the cluster head (CH) election since the CH has a critical role in data routing. This chapter discusses a new clustering algorithm based on a weighted formula for cluster head election. The weighted formula is based on three parameters: the trust, the distance, and the velocity. This protocol will elect two cluster heads to ensure an end-to-end communication path between source and destination.

Clustering is expected to be one of the most efficient and promising solutions for data transmission in Vehicular Ad hoc NETworks (VANET). The particular characteristics of VANET, including highly dynamic network topology, unstable transmission channel, and various service requirements, pose challenges and difficulties on clustering algorithm design. In this paper, a clustering algorithm based on utility function is proposed for VANET. The utility function of vehicles is formulated which jointly considers current state of vehicles characterized by the vehicle degree, relative velocity and position between adjacent vehicles, and long-term transmission performance of vehicles, defined as credit history function, which is characterized by the average available bandwidth, queue length and the duration for being a cluster head (CH) in a past period. The process of cluster forming is presented, and the vehicles with large utility function are selected as CHs successively. Numerical simulations demonstrate that comparing to previously proposed algorithms, the proposed algorithm offers better performance in terms of packet delivery rate, average transmission delay and total throughput.

Intelligent Transportation System (ITS) employ Vehicular Ad Hoc Network (VANET) to increase road safety and decrease thenumber of accidents. VANET uses Dedicated Short-Range Communications (DSRC) to allow drivers to obtain reasonable awareness of surrounding vehicles. VANET reliability is affected by any degradation in the communication channel or any lack of exchanged information between vehicles. Moreover, it is vulnerable to a wide range of malicious attacks due to its nature. Such issues might cause a complete failure in VANET services and hence cause accidents, injuries, or death. Thus, VANET reliability and security are very critical. This paper discusses briefly different types of malicious attacks in VANET and some of their detection techniques. It gives more attention to position falsification attack as it has a severe impact on different VANET services. Furthermore, it explores previously proposed detection approaches for this attack using either traditional or machine learning techniques. Finally, attention will be drawn to unresolved challenges and potential future research directions.

A special type of Mobile Ad-hoc Networks (MANETs) which has frequent changes of topology and higher mobility is known as Vehicular Ad-hoc Networks (VANETs). In order to divide the network into groups of mobile vehicles and improve routing, data gathering, clustering is applied in VANETs. A stable clustering scheme based on adaptive multiple metric combining both the features of static and dynamic clustering methods is proposed in this work. Based on a new multiple metric method, a cluster head is selected among the cluster members which is taken from the mobility metrics such as position and time to leave the road segment, relative speed and Quality of Service metrics which includes neighborhood degree, link quality of the RSU and bandwidth. A higher QoS and cluster stability are achieved through the adaptive multiple metric. The results are simulated using NS2 and shows that this technique provides more stable cluster structured with the other methods.

In recent years, vehicular ad-hoc networks (VANETs) have received considerable attentions. As a promising approach to future Intelligent Transportation System (ITS), VANET is capable of providing safety related applications, Internet accessing and various user applications for drivers and passengers. To support efficient data interaction among vehicles, clustering based topology can be applied which groups vehicle nodes in geographical vicinity together, supports direct interaction inside one cluster and inter-cluster data interaction through cluster heads (CHs). Both K-means and K-Harmonic Means (KHM) algorithms are commonly-used clustering algorithms for wireless sensor networks, however, these algorithms cannot be applied to VANETs directly due to the specific characteristics of VANETs. In this paper, we propose an improved KHM algorithms, called Adaptive K-Harmonic Means (AKHM) clustering algorithm for VANETs, which jointly considers the available bandwidth of candidate CHs, and relative distance and velocity between cluster members (CMs) and CHs. To perform the proposed algorithm, the initial values of the number of clusters and the positions of each centroids are chosen and the weighted distance between vehicles and centroids is defined, based on which the objective function can be formulated, and the optimal CHs and the association between CMs and CHs can then be determined. The simulation results demonstrate the efficiency of AKHM algorithm.

The Industrial Internet of Things (IIoT) is the use of Internet of Things (IoT) technologies in manufacturing. The vehicular ad hoc networks (VANETs) are a typical application of IIoT. Benefiting from Dedicated Short‐Range Communication (DSRC) technology, vehicles can communicate with each other through wireless manner. Therefore, road safety is able to be greatly improved by the broadcast of safety messages, which contain vehicle’s real‐time speed, position, direction, etc. In existing DSRC, safety messages are broadcasted at a fixed frequency by default. However, traffic conditions are dynamic. In this way, there are too many transmission collisions when vehicles are too dense and the wireless channel is underused when vehicles are too sparse. In this paper, we address broadcast congestion issue in DSRC and propose lightweight adaptive broadcast (LAB) control for DSRC safety message. The objectives of LAB are to make full use of DSRC channel and avoid congestion. LAB meets two key challenges. First, it is hard to adopt a centralized method to control the communication parameters of distributed vehicles. Furthermore, the vehicle cannot easily acquire the channel conditions of other vehicles. To overcome these challenges, channel condition is attached with safety messages in LAB and broadcast frequency is adapted according to neighboring vehicles’ channel conditions. To evaluate the performance of LAB, we conduct extensive simulations on different roads and different vehicle densities. Performance results demonstrate that LAB effectively adjusts the broadcast frequency and controls the congestion.

Reliability is an important issue for safety-critical broadcast services in vehicular ad hoc networks (VANETs). So far, most investigations of such broadcast networks focus on multihop connectivity, taking all one-hop links for granted. In this paper, four reliability metrics for one-hop broadcast communication in VANETs, including the packet reception rate (PRR), the packet delivery ratio (PDR), the node successful packet delivery probability (PDP), and the effective range (ER), are introduced and evaluated analytically and by simulations. Expressions of these reliability metrics for one-hop broadcast in IEEE-802.11-based 1-D VANETs are derived with consideration of the IEEE 802.11 distributed coordination function (DCF), the hidden terminal problem, and collisions caused by concurrent transmissions. The impacts of network parameters such as distinct transmission, carrier sensing, and interference ranges; the density of nodes in the networks; the distances of receivers to the senders; the message generation rates; the backoff window sizes; and the channel data rates on the reliability of the broadcast communication in VANETs are investigated and discussed. As an example, the proposed model is applied to the evaluation of the dedicated short-range communication (DSRC) safety-critical message propagation in a highway setting. As a result, some important observations to the design and analysis of such communication systems are provided.

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.

According to car crash statistics, over sixmillionmotor vehicle crashes occur onU.S. highways each year. More than 42,000 people are killed in these accidents which injure three million others, and cost more than $230 billion each year. Astonishingly, five people die every hour in these crashes in the United States which is about one death every 12 minutes IVI (2001). In order to alleviate the threats of these crashes and improve the driving experience, car manufactures and the telecommunication industry have made great efforts to equip each vehicle with wireless devices that allow vehicles to communicate with each other as well as with the roadside infrastructure located in critical points of the road, such as intersections or construction sites. Misener (2005); VII (2011). Technologies built on 802.11p and IEEE 1609 standards, 5.9 GHz Dedicated Short Range Communications (DSRC) protocols 1 DSRC (1999), are proposed to support these advanced vehicle safety applications such as secure and effective vehicle-to-vehicle (V2V) (also known as Inter-Vehicle Communication (IVC)) and vehicle-to-infrastructure (V2I) communications, which are also known as Vehicle Safety Communications (VSC) technologies. As shown in Fig. 1, the wireless communication devices installed on vehicles, also known as onboard units (OBUs), and the roadside units (RSUs), form a self-organized Vehicular Ad Hoc Network (VANET) Lin (2008); Sun (2007). Furthermore, the RSUs are connected to the backbone network via the high speed network connections. In this way, VANETs inherently provide a way to collect traffic and road information from vehicles, and to deliver road services including warnings and traffic information to users in the vehicles. Thus, an increasing interest has been raised recently on the VANETs-based applications Bishop (2000), aiming to improve driving safety and traffic management by the method of providing drivers and passengers with Internet access.

With regard to the complex and varied urban scenes in Vehicular Ad-Hoc Network, such as the vehicle nodes with fast speed, unstable links and frequent changes in network topology, this paper proposed a stable clustering algorithm to establish routing for VANET. In this algorithm, clustering was first formed according to the Similar Neighbor Node Table. Then on the basis of the Highest Connectivity Algorithm, parameters such as position and speed of the node were introduced to calculate the Selection Priority which were used to produce the preferred and the alternative cluster head node. The introduction of alternative cluster head nodes improved the stability of clustering to a certain extent. Finally, the clustering was established and maintained for six special scenarios. Compared with the traditional clustering algorithm in VANET, it had the characteristics of lower end-to-end delay, higher packet delivery rate and lower change rate of preferred cluster head nodes, which greatly improved the communication quality of VANET.

Vehicular ad hoc network (VANET) is fastest growing technology that ensure safe and efficient road traffic management. Mobility management is the main challenge in VANET. So, adaptive and stable routing protocol is a vital issue in VANET technology. Cluster-based VANET is getting more attention day by day. However, finding a solution that ensure longer lifetime of a moving vehicle in a cluster is essential. In this paper, we propose a new routing protocol for cluster-based VANET called central lane-based lifetime routing (CLLTR) to improve the quality of services. In the CLLTR scheme, to ensure the longer lifetime in cluster the cluster heads (CHs) should be selected from the central lane of the road. Because, the central lane cars will travel longer distance, i. e., lifetime will be larger, than other lane cars as the shape of the cluster is circular. Here, the CHs will also act as a gateway node of the clusters. Numerical simulations are carried out to evaluate the performance of the proposed CLLTR scheme. Results confirm that the proposed CLLTR scheme provides better stability than the conventional cluster-based life time routing (CBLTR) schemes of VANET.