Strength Optimized Weight Balancing for Traffic Management in Vehicular Ad-hoc Networks

The Vehicular Ad Hoc Networks (VANETs) paradigm is a promising technology to enable the Internet of Vehicles (IoV) for future integration with 5G and 6G infrastructures in smart cities. However, VANET can be susceptible to wireless interference, like co-channel interference, which can cause communication quality and performance to deteriorate, threatening vehicular safety applications, including traffic management and accident prevention. Hence, VANET requires practical interference mitigation strategies, such as digital beamforming, that mitigate the signals from unwanted directions while improving the reception of signals from desired directions with adequate precision, which is helpful for VANET’s highly mobile environments. In this paper, a review of the literature on digital beamforming techniques is carried out that examines their advantages and limitations. Furthermore, an important contribution of this paper is the development of an experimental platform for a roundabout VANET based on simulations, where different digital beamforming algorithms, such as phase-shift and Minimum-Variance Distortionless-Response (MVDR), are tested. The results show that the MVDR algorithm leads to improvement due to its adaptability to ad hoc environments. Also, they show thatMVDRadaptive beamforming improves Signal-to-Interference-plus-Noise Ratio (SINR) and reduces outage event proportion compared to non-beamforming and conventional beamforming scenarios, highlighting their potential to mitigate co-channel interference in highly changing VANET environments. Therefore, adaptive digital beamforming can improve the performance and reliability of VANETs, offering the potential for advanced wireless network implementations in smart cities with 5G and 6G infrastructures.

A new concept such as smart city was introduced in the last years where the Intelligent Transportation system (ITS ) plays a critical role to provide road safety and manage Vehicular Ad Hoc Networks (VANETs) traffic. Nevertheless, VANETs have significant constraints like nodes high mobility, intermittent connectivity, variable network density and heterogeneity. However, the different types of traffic, the different Quality of Service requirements, the need to exchange mobile data, multi-services and data diversity leads mainly to load and time constraints in this specific and stringent type of networks. The main characteristic of this kind of networks is the very changing topology that poses supplementary constraints and makes achieving QoS constraints a very challenging task. In VANET network the vehicle generated traffic will be transferred to the data center from road side unit to the base station by using Long Term Evolution (LTE) in an urban area. Despite LTE has a larger system capacity and it provides a higher transmission speed, the network performance is affected by the implemented scheduling algorithm. In this context, we study the efficiency of LTE scheduler algorithms such as Proportional Fairness, Round Robin, Priority Set Scheduler, Maximum Throughput Scheduler and Throughput to Average Scheduler and Blind Equal Throughput mainly at the road side unit using Network Simulator 3(NS3) to determinate the most suitable scheduler for VANET traffic. Results demonstrate that the round robin algorithm is more effective for volumetric VANET traffic in terms of throughput, delay, packet loss rate and fairness.

VANET-Based Intelligent Traffic Light Control System by Detecting Congestion Using Fuzzy C-Means Clustering Technique in a Smart City

In Vehicular Ad hoc NETwork (VANET) vehicles equipped with wireless communication devices communicate with each other to share information or achieve some collaborative goal. Mobile agents because of their adaptability and mobility can be well utilized in designing VANET applications. In this paper, the vehicles in VANET are shown to collect environmental data. Here vehicles equipped with sensors to measure environmental data are sent from a monitoring center to some particular monitoring area. Each vehicle has mobile agent platform that may host one mobile agent. The mobile agent spawned at the monitoring center migrates from one vehicle to the other to reach the monitoring area. It (the agent) collects necessary data, processes it and brings back the result. This helps to measure environmental parameters in different areas without deploying fixed infrastructure and mobile agents ensure better utilization of network bandwidth. The application is simulated in OMNET++ with SUMO to generate road traffic. The results indicate scalability of the application for larger networks. With more no. of vehicles, more area can be covered.

Smart cities are increasingly playing a fundamental role in managing the city’s asset. Smart transportation is an important building block of a smart city as it can efficiently resolve many issues related to the traffic on the road. Vehicular ad hoc networks (VANETs) in smart cities may ensure wide inter-vehicle communication and disseminate data and safety-related information. VANETs have their specific characteristics such as long lifetime battery energy, high mobility, and large storage capabilities. In certain circumstances, VANETs may not ensure timely detection of road events and connectivity between vehicles due to their low density, high mobility, or low deployment of roadside unit (RSU) infrastructure. Wireless sensor networks (WSNs) are equipped with low processing and low storage capabilities but they ensure high detection of events. To overcome VANETs limitations, and as VANET and WSN have complementary characteristics, the combination of VANET and wireless sensor network (WSN) technologies into one hybrid architecture enables to identify new aspects and fields of intelligent transportation systems and may offer new services for the smart cities. In this kind of hybrid network, sensor nodes have small size and can be deployed densely inside the road to monitor traffic, roads status, and weather conditions. This chapter describes the hybrid vehicular sensor networks and discusses their deployed applications, communication paradigms, challenges, and existing architectural solutions. Moreover, a heterogeneous VANET-WSN architecture is proposed and open issues and future directions are discussed to help stimulating future studies in this emerging research field.

A new concept such as smart city was introduced in the last years where the Intelligent Transportation system (ITS ) plays a critical role to provide road safety and manage Vehicular Ad Hoc Networks (VANETs) traffic. Nevertheless, VANETs have significant constraints like nodes high mobility, intermittent connectivity, variable network density and heterogeneity. However, the different types of traffic, the different Quality of Service requirements, the need to exchange mobile data, multi-services and data diversity leads mainly to load and time constraints in this specific and stringent type of networks. The main characteristic of this kind of networks is the very changing topology that poses supplementary constraints and makes achieving QoS constraints a very challenging task. In VANET network the vehicle generated traffic will be transferred to the data center from road side unit to the base station by using Long Term Evolution (LTE) in an urban area. Despite LTE has a larger system capacity and it provides a higher transmission speed, the network performance is affected by the implemented scheduling algorithm. In this context, we study the efficiency of LTE scheduler algorithms such as Proportional Fairness, Round Robin, Priority Set Scheduler, Maximum Throughput Scheduler and Throughput to Average Scheduler and Blind Equal Throughput mainly at the road side unit using Network Simulator 3(NS3) to determinate the most suitable scheduler for VANET traffic. Results demonstrate that the round robin algorithm is more effective for volumetric VANET traffic in terms of throughput, delay, packet loss rate and fairness.

The availability of more realistic road conditions and dynamics provides sound ground to study the issues of Vehicular ad-hoc Network (VANET). In this chapter a new heterogeneous traffic flow based mathematical model is presented, to gain the time and space dynamics of vehicles. To achieve more accurate and realistic data about road conditions, microscopic parameters of varying safety distance between the vehicles and vehicular length are considered in the model. The density dynamics under different road scenarios are calculated under the influence of these constraints with the use of a defined mathematical model. The model is able to capture the impact of road constraints such as traffic lights and road incidents, on the traffic flow. The concept of Vehicular Ad-hoc Networks (VANET) has given mankind opportunities for secure and safe journeys on the roads. VANET is defined as a subclass of Mobile Ad-hoc Networks which holds the characteristics of ad-hoc networks. However due to the dynamic road conditions, traffic flow theory concepts, mobility constraints, human behaviours and vehicular characteristics VANET exhibits different dynamics. These factors have strong influences on the VANET architecture from physical to application layers. This highlights different areas of interest in VANET for researchers to investigate. This study aims to capture the impact of traffic flow theory constraints on the vehicular density under the heterogeneous traffic flow on the road. The microscopic and macroscopic characteristics of vehicles moving on the roads are utilized for the improvement of VANET connectivity dynamics.

Connectivity probability analysis of VANETs at different traffic densities using measured data at 5.9 GHz

Vehicular Ad Hoc Networks (VANETs) are composed of vehicles equipped with advanced wireless communication devices. As a paradigm of decentralized advanced traveler information systems (ATIS), VANETs have obtained interests of researchers in both communication and transportation fields. The research in this chapter investigates several fundamental issues, such as the connectivity, the reachability, the interference, and the capacity, with respect to information propagation in VANETs. The authors’ work is distinguished with previous efforts, since they incorporate the characteristics of traffic into these issues in the communication layer of VANETs; this mainly addresses the issue of the interference. Previous efforts to solve this problem only consider static network topologies. However, high node mobility and dynamic traffic features make the interference problem in VANETs quite different. To investigate this problem, this chapter first demonstrates the interference features in VANETs incorporating realistic traffic flow features based on a validated simulation model. Then, analytical expressions are developed to evaluate the interference under different traffic flow conditions. These analytical expressions are validated within the simulation framework. The results show that the analytical expressions perform very well to capture the interference in VANETs. The results from this work can facilitate the development of better algorithms for maximizing throughput in the VANETs.

Vehicular Ad Hoc Networks (VANETs) have a strategic goal to achieve service delivery in roads and smart cities, considering the integration and communication between vehicles, sensors and fixed road-side components (routers, gateways and services). VANETs have singular characteristics such as fast mobile nodes, self-organization, distributed network and frequently changing topology. Despite the recent evolution of VANETs, security, data integrity and users privacy information are major concerns, since attacks prevention is still open issue. One of the most dangerous attacks in VANETs is the Sybil, which forges false identities in the network to disrupt compromise the communication between the network nodes. Sybil attacks affect the service delivery related to road safety, traffic congestion, multimedia entertainment and others. Thus, VANETs claim for security mechanism to prevent Sybil attacks. Within this context, this paper proposes a mechanism, called SyDVELM, to detect Sybil attacks in VANETs based on artificial intelligence techniques. The SyDVELM mechanism uses Extreme Learning Machine (ELM) with occasional features of vehicular nodes, minimizing the identification time, maximizing the detection accuracy and improving the scalability. The results suggest that the suitability of SyDVELM mechanism to mitigate Sybil attacks and to maintain the service delivery in VANETs.

VANET (Vehicular Ad hoc Network) have become an exciting research going in the era of smart cities as a means for increasing traffic safety and comfort. Nevertheless, VANETs possess some particular characteristics such as very high mobility, encountering rapid changes of topology, frequent disconnected network and variable network density. Gathered VANET traffic will be transferred from road side unit to base station which is responsible of routing traffic to the data centre using long-range support like WiMax( Worldwide Interoperability for Microwave Access) in smart city solutions. As VANET have a special network behaviours and stringent traffic physiognomy, this work aims to determinate the most suitable WiMax scheduler to support VANET traffic characteristics. For this purpose, we used in this work a VANET traffic model as input to our NS3 simulation scenarios. In this paper, we evaluate three basic scheduling algorithms (simple scheduler, simple priority, based real time polling service scheduler and migration based uplink scheduler), mainly at the base station level in WiMax. We analyse their performance in the case of VANET traffic context in order to find the best suitable scheduler in terms of throughput, latency, and reliability. Results demonstrate that the simple priority based first come first served scheduler(simple scheduler) and a based real time polling service scheduler (scheduler RTPS) outperform the migration based uplink scheduler (scheduler MBQOS) when the number of nodes less than or equal to 20. On the other hand, the scheduler MBQOS is more effective for higher network density and favors the real-time traffic in terms of reliability and delay.

A vehicular ad hoc network (VANET) consists of vehicles (mobile nodes) and road side units which are equipped with the wireless devices such as wireless LANs. Mobile nodes exchange the information messages with each other so that VANETs are configured in a self-organized manner. As one of the application scenarios (use case) in VANETs, there is the information provision of the parking lots' situation in the city central to vehicles (mobile nodes). In this scenario, the road side unit (source node) deployed at the parking lot periodically disseminates the empty information to mobile nodes in VANETs. Therefore, we have proposed a mobile agent-based information dissemination scheme in the VANET environment. In this paper, we propose a location-based mobile agent migration mechanism which decides how to migrate mobile agents in the network. In addition, we conduct the simulation experiments in the VANET environment considering the entrance and exit of mobile nodes to evaluate the proposed information dissemination scheme.

Vehicular ad hoc networks (VANETs) are a fundamental component of intelligent transportation systems in smart cities. With the support of open and real-time data, these networks of inter-connected vehicles constitute an 'Internet of vehicles' with the potential to significantly enhance citizens' mobility and last-mile delivery in urban, peri-urban, and metropolitan areas. However, the proper coordination and logistics of VANETs raise a number of optimization challenges that need to be solved. After reviewing the state of the art on the concepts of VANET optimization and open data in smart cities, this paper discusses some of the most relevant optimization challenges in this area. Since most of the optimization problems are related to the need for real-time solutions or to the consideration of uncertainty and dynamic environments, the paper also discusses how some VANET challenges can be addressed with the use of agile optimization algorithms and the combination of metaheuristics with simulation and machine learning methods. The paper also offers a numerical analysis that measures the impact of using these optimization techniques in some related problems. Our numerical analysis, based on real data from Open Data Barcelona, demonstrates that the constructive heuristic outperforms the random scenario in the CDP combined with vehicular networks, resulting in maximizing the minimum distance between facilities while meeting capacity requirements with the fewest facilities.

BACKGROUND: Age-related changes in autonomic regulation and microcirculation may be substantially modified by urban environmental factors; however, comparative analyses of these processes in settlements with different levels of urbanization remain insufficiently studied. AIM: The work aimed to assess the effect of age on spectral parameters of heart rate variability and microcirculation among residents of cities with different levels of urbanization. METHODS: Volunteers from three age groups (group 1, 18–44 years; group 2, 45–59 years; group 3, 60–74 years) permanently residing in a large city (Nizhny Novgorod), an industrial city with a developed chemical industry (Dzerzhinsk), and a small tourist city (Semenov) were examined. Heart rate variability was analyzed using the Poly-Spectrum hardware–software system (Neurosoft, Russia). Microcirculation was assessed by laser Doppler flowmetry (LAZMA analyzer, Russia). Statistical comparisons were performed using Student’s t test with Bonferroni correction. RESULTS: With increasing age, a decrease in total spectral power of heart rate variability (p 0.05) and individual spectral components was observed. Age-related changes in the heart rate variability spectrum were universal: the greatest increase in the contribution of the very low-frequency component was recorded at the age of 45–59 years among residents of the large city (by 66%), the industrial city (by 38%), and the small city (by 29%) compared with group 1, followed by an increase in high-frequency power at the age of 60–74 years: by 3-fold in large city residents, by 1.4-fold in industrial city residents, and by 1.6-fold in small city residents compared with group 2. However, a very low-frequency component was persistently elevated only among residents of the industrial city aged 60–74 years, exceeding that in group 1 by 21% (p 0.05). In microcirculation, aging was associated with a decrease in cardiac rhythm amplitude and an increase in endothelial rhythm amplitude across all groups. In individuals aged 60–74 years living in the large city and the industrial center, a reduction in myogenic rhythm amplitude was observed, whereas in the tourist city, this parameter demonstrated an opposite trend. CONCLUSION: The type of settlement influences universal age-related changes associated with a reduction in the activity of autonomic regulatory mechanisms as a whole. The greatest strain on regulatory systems was observed in middle-aged individuals (45–59 years), with subsequent persistence in older individuals (60–74 years) residing in an industrial center with a developed chemical industry, compared not only with residents of a small tourist city but also with those of a large city. These findings are relevant for the assessment of prenosological conditions and are important for the development of preventive public health measures.

<p>The traffic congestion in vehicular adhoc networks (VANETs) is a vital problem due to its dynamic increase in traffic loads. VANETs undergo inefficient routing capability due to its increasing traffic demands. This has led to the need for intelligent transport system (ITS) to assist VANETs in enabling suitable traffic loads between vehicles and road side units (RSU). Most conventional systems offer distributed solution to manage traffic congestion but fail to regulate real-time traffic flows. In this paper, a dynamic traffic control in VANETs is offered by combining deep neural network (DNN) with mobile agents (MA). An experimental analysis is carried out to test the efficacy of the DNN-MA against conventional machine learning and a deep learning routing algorithm in VANETs. DNN-Mal is validated under various traffic congestion metrics like latency, percentage delivery ratio, packet error rate, and throughput. The results show that the proposed method offers reduced energy consumption and latency.</p>