Is SDN the solution for NDN-VANETs?

Software Defined Network (SDN) is getting popularity both from academic and industry. Lot of researches have been made to combine SDN with future Internet paradigms to manage and control networks efficiently. SDN provides better management and control in a network through decoupling of data and control plane. Named Data Networking (NDN) is a future Internet technique with aim to replace IPv4 addressing problems. In NDN, communication between different nodes done on the basis of content names rather than IP addresses. Vehicular Ad-hoc Network (VANET) is a subtype of MANET which is also considered as a hot area for future applications. Different vehicles communicate with each other to form a network known as VANET. Communication between VANET can be done in two ways (i) Vehicle to Vehicle (V2V) (ii) Vehicle to Infrastructure (V2I). Combination of SDN and NDN techniques in future Internet can solve lot of problems which were hard to answer by considering a single technique. Security in VANET is always challenging due to unstable topology of VANET. In this paper, we merge future Internet techniques and propose a new scheme to answer timing attack problem in VANETs named as Timing Attack Prevention (TAP) protocol. Proposed scheme is evaluated through simulations which shows the superiority of proposed protocol regarding detection and mitigation of attacker vehicles as compared to normal timing attack scenario in NDN based VANET.

This paper investigates the issue of multi-hop forwarding in Vehicular Ad hoc Networks (VANETs), which is suffering from rapidly changing topology, short-lived and intermittent connectivity. Designed to replace TCP/IP using named data, Named Data Networking (NDN) has natural advantages to greatly overcome those challenges because of its multi-source and in-network caching characteristics. However, in the wireless environment the Interest and Data, proposed in NDN, are usually flooded because of the absence of Forwarding Information Base (FIB). To tackle this problem, we propose HVNDN, a hybrid forwarding strategy through NDN. More specifically, HVNDN introduces opportunistic and probabilistic forwarding strategy for location-dependent and location-independent information, respectively, which takes full advantage of geographic information and the characteristics of named data in VANETs. To make Vehicle-to-Vehicle (V2V) communication more effective and reliable, we design elaborate Interest and Data packets formats, retransmission and acknowledgement mechanism in HVNDN. Simulation results from NS-3 demonstrate that the proposed forwarding strategy outperforms the state-of-art scheme with less end-to-end delay and overhead.

Boosting named data networking for data dissemination in urban VANET scenarios

Vehicular communication networks is a powerful tool that enables numerous vehicular data services and applications. The rapid growth in vehicles has also resulted in the vehicular network becoming heterogeneous, dynamic, and large-scale, making it hard to meet the strict requirements, such as extremely latency, high mobility, top security, and enormous connections of the fifth-generation network. Previous studies have shown that with the increase in the application of Software-Defined Networking (SDN) on Vehicular Ad-hoc Network (VANET) in industries, researchers have exerted considerable efforts to improve vehicular communications. This study presents an exhaustive review of previous works by classifying them based on based on wireless communication, particularly VANET. First, a concise summary of the VANET structure and SDN controller with layers and details of their infrastructure is provided. Second, a description of SDN-VANET applications in different wireless communications, such as the Internet of Things (IoT) and VANET is provided with concentration on the examination and comparison of SDN-VANET works on several parameters. This paper also provides a detailed analysis of the open issues and research directions accomplished while integrating the VANET with SDN. It also highlights the current and emerging technologies with use cases in vehicular networks to address the several challenges in the VANET infrastructure. This survey acts as a catalyst in raising the emergent robustness routing protocol, latency, connectivity and security issues of future SDN-VANET architectures.

Vehicular ad-hoc network (VANET) technology enables communication between vehicles, or vehicles and road-side units (RSUs) through wireless communication devices installed on the vehicles. One of the most important goals of VANETs is providing safety applications for passengers. In addition, VANETs provide comfort applications to users. Guaranteeing a reliable and stable routing protocol over VANETs is a very important step. The proposed research attempts to improve routing protocols that decrease the end-to-end delay to suit VANET communication characteristics. In addition, it proposes analysis of the end-to-end delay probability distribution. More specifically, we derive a closed-form expression for the probability distribution of the re-healing delay in a VANET conditioned on the distance between two VANET clusters. Furthermore, we propose a closed-form expression for the probability distribution of the unconditional re-healing delay. Moreover, we develop a mathematical model to calculate the probability distribution of the end-to-end delay. On the other hand, using Unmanned Aerial Vehicles (UAVs) or drones in wireless communications and Vehicular Ad-hoc Networks (VANETs) has started to attract attention. We propose a routing protocol that uses infrastructure drones for boosting VANET communications to achieve a minimum vehicle-to-drone packet delivery delay. In addition, we propose a closed-form expression for the probability distribution of the vehicle-to-drone packet delivery delay on a two-way highway. Moreover, based on that closed-form expression, we can calculate the minimum drone density (maximum separation distance between two adjacent drones) that stochastically limits the worst case of the vehicle-to-drone packet delivery delay. Furthermore, we propose a drones-active service (DAS) that is added to the location service in a VANET. This service dynamically and periodically obtains the required number of active drones based on the current highway connectivity state by obtaining the maximum distance between each two adjacent drones while satisfying a probabilistic constraint for vehicle-todrone packet delivery delay. Our analysis focuses on two-way highway VANET networks with low vehicular density. The simulation results show the accuracy of our analysis and reflect the relation between the drone density, vehicular density and speed, other VANET parameters, and the vehicle-to-drone packet delivery delay. In addition, we propose a new routing protocol called multi-copy intersection-based routing (MCIR) for vehicular ad-hoc networks (VANETs) in urban areas. MCIR is an intersectionbased routing protocol that forwards multiple copies of the packets in different road segments. Moreover, it is a beacon-less routing protocol with a carry-and-forward strategy. We show via simulation that the MCIR protocol is superior to other existing routing protocols, especially in low vehicular density scenarios. The results show that MCIR achieves a shorter end-to-end delay and a higher packet delivery ratio in urban VANET communications.

Named data networking (NDN) has been considered as a promising networking architecture for vehicular ad-hoc networks (VANETs). However, interest forwarding in NDN suffers severe issues in vehicular environment. Broadcast storms result in much packet loss and huge transmission overhead. Also, link disconnection caused by highly dynamic topology leads to low packet delivery ratio and extreme long delay in data retrieval. Thus, an efficient NDN forwarding strategy to retrieve data is urgently required. In this paper, we propose the density-aware delay-tolerant (DADT) interest forwarding strategy to retrieve traffic data in vehicular NDN. DADT specifically addresses data retrieval during network disruptions using delay tolerant networking (DTN). It makes retransmission decisions based on directional network density. Also, DADT mitigates broadcast storms by using a rebroadcast deferring timer. We compared DADT against other strategies through simulation and the results show that it can achieve a higher satisfaction ratio while maintaining low transmission overhead.

In Vehicular (Ad-hoc) Network (VANET), besides Vehicle-to-Vehicle communications (V2V), vehicles in VANET also exchange data with Road-Side-Units (RSUs) and Cellular Base Stations (Vehicle-to-Infrastructure communications (V2I)). With the introduction of Intelligent Transport Systems (ITS), VANETs possess a great potential in enabling surveillance services. The rapid development of wireless communication technologies recently results in empowering data exchange among vehicles, RSUs and Cellular Base Stations, improving various types of applications and services such as safety driving, route planning, traffic alert, and context-aware infotainment. However, the benefits offered by VANETs and ITS cannot be fully realized unless there is a mechanism to effectively defend against fake and erroneous information exchange from malicious or dysfunctional nodes to other vehicles and RSUs for their own purposes. In this regards, trust appears as one of the solutions for VANETs to establish secure connectivity and reliable services. The conceptual idea to tackle down this challenges is that only data from trusted vehicles is taken into account. Thus, the aim is to evaluate trust of a vehicle in exchanging high quality of information. This paper presents the trust concept, key characteristics, a trust evaluation model, and a prototype for trusted data exchange activities in VANETs.

Over the past few years, there has been significant research interest in field of vehicular ad hoc networks (VANETs). Wireless communication over VANETs supports vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) communication. Such innovation in wireless communication has improved our daily lives through road safety, comfort driving, traffic efficiency. As special version of MANETs, VANETs bring several new challenges including routing and security challenges in data communication due to characteristics of high mobility, dynamic topology. Therefore, academia and the auto mobile industry are taking interest in several ongoing research projects to establish VANETs. The work presented here focuses on communication in VANETs with their routing and security challenges along with major application of VANETs in several areas.

Vehicular communication ad hoc routing protocols: A survey

Vehicular Ad Hoc Network (VANET) is a multi-hop wireless network which involves vehicles acting as nodes to communicate with each other without infrastructural support. With the increase in Quality of Service (QoS) needs in evolving applications and the widespread use of wireless and mobile devices, it is desirable to support QoS in VANETs. The resource limitations and variability further add to the need for QoS support in such networks. However, the characteristics of these networks make QoS support a complex process due to rapid topology changes caused by high mobility of communicating nodes. Modulation scheme implemented in wireless network affect the data rate hence the throughput of the communicating nodes, this in turn affect QoS. The paper focuses on adaptive modulation to improve the data throughput and efficiency of channel spectrum in VANET. Through theoretical and simulation results, it was shown that adaptive modulation performs well and improves throughput than other modulations schemes when used singularly in dynamic changing network topology like VANET.

With the advancement of wireless communication technology, the intelligent transportation system (ITS) has attracted the attention of vehicle companies and academic researchers. Recently, vehicular ad hoc networks (VANETs) as a leading genuine technology have received serious attention as a kind of mobile ad hoc network (MANET) to ensure the safety of vehicles, drivers, and passengers. However, these networks face many challenges due to the mobility of vehicle nodes, wireless communication, and frequent topology changes. One of the crucial issues of these networks is a cluster-based routing scheme with the ability to provide quality of service (QoS) parameters. A clustering scheme is an appropriate method for increasing the scalability of VANETs. In a cluster-based routing scheme, the cluster head (CH) is responsible for receiving data from its member nodes, and aggregating and transferring data to the next CH node. On the other hand, providing a suitable clustering method is NP-hard problems and meta-heuristic algorithms are suitable for solving these problems. A scalable and reliable routing scheme is necessary and essential in VANETs. In this paper, a routing method based on the clustering technique is presented considering the moth-flame optimization (MFO) algorithm for clustering and the Firefly optimization algorithm (FoA) with a suitable fitness function for routing between CHs. The simulation of the proposed method with MATLAB software shows that the proposed RVMF method improves the parameters of packet delivery rate (PDR), latency, and throughput.

Named data networking (NDN) is one representation and implementation of information-centric networking (ICN) and is considered to be among the most promising designs for the next generation of network architecture. The introduction of NDN into vehicular ad-hoc networks (VANETs) and utilization of its content-centric characteristic to improve data transmission and distribution in VANETs has become a research hotspot in recent years. However, research on mobility support of NDN-based VANETs still faces many challenges. To solve the issue of data transmission path breaking due to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Consumer</i> mobility in NDN-based VANETs, this article proposes a novel vehicle tracking-based <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Data</i> packet forwarding scheme (VTDF) to improve the successful delivery rate of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Data</i> packets in mobile environments. In this approach, the urban road structure is divided into complex multi-junction and straight lane scenarios and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Data</i> packets are forwarded according to vehicle movement information. Simulations indicated that this vehicle tracking scheme provides a lower average data transmission delay, shorter handover delay between roadside units, and higher data delivery rate for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Consumers</i> compared to the standard methods.

&lt;p&gt;The vehicular ad hoc network (VANET) has emerged as a heterogeneous network with no fixed infrastructure. In VANET, vehicles are the mobile nodes that communicate with one another and with the infrastructure. One of the major challenges in VANET is to allocate resources efficiently due to environmental characteristics such as highly mobile vehicles, latency-sensitive and short connection times. The conventional resource management mechanisms are not very effective in such an environment. The data-driven Artificial Intelligence (AI) based techniques are a very efficient alternative to traditional statistical techniques. This project proposes an AI-empowered task offloading and computing resource allocation model which can dynamically organize the computing resources in VANET. The model is divided into two layers. First, the task offloading layer, where the Random Forest (RF) algorithm is used to determine whether the vehicle’s computing tasks should be offloaded to the cloud computing (CC) server or mobile edge computing (MEC) server or to be processed locally (in-vehicle computing). Second, the resource allocation layer, where the deep deterministic policy gradient (DDPG) algorithm is used to determine the computing platform again when the task is determined to be offloaded to either MEC servers or the cloud servers. To evaluate the performance of the RF classifier, we applied the model to a real-world driving trajectory dataset then compared the results with a different set of machine learning algorithms namely, K-nearest neighbour (KNN), Multilayer Perceptron (MLP) and Support Vector Machine (SVM). The results show the RF model outperformed other models in classification accuracy score of 99.83% for task offloading decision, where the KNN, MLP and SVM achieved 98%, 94.81% and 90.94%, respectively. Moreover, the DDPG based resource allocation scheme converges within 150 episodes. Thus, the proposed model can find the optimal offload decision and the computational resource allocation simultaneously and achieves a high delay to quality-of-service (QoS) satisfaction ratio.&lt;/p&gt;

Maintaining communication links of an established communication path that extends between source and destination nodes is a significant challenge in Vehicular Ad Hoc Networks (VANETs) due to movement of the vehicles. In emergency applications for vehicular networks, users only interest the content in the messages that are related to them. Therefore, Named Data Networking (NDN) is a perfect match for the emergency applications where it only focuses on “what” is the data instead of “where” is the data. In this paper, we proposed Emergency Application for Vehicle-to-Vehicle Communication using Named Data Networking (eVNDN). In eVNDN, generated packet names are based on different emergency broadcast applications and the location of the senders. This enables vehicles to communicate based on the contents of the messages and allows nearby neighbor vehicles quickly determine whether these messages fit for their interest. Based on the content in the packets that users (e.g., vehicles) send or receive, eVNDN will determine the optimal strategy. We give simulation results to demonstrate the effectiveness of our approach. With the experiment results, we showed that the eVNDN is able to improve the performance of the vehicular network for emergency applications.

A vehicular ad hoc network (VANET) is a special kind of mobile ad hoc networks (MANET) that supports cooperative driving among communicating cars on the roads. There are several technologies involved in implementation of wireless communication in VANETs. These technologies include 3G cellular systems, long-term evolution (LTE), LTE Advanced, IEEE 802.16, and IEEE 802.11. This chapter focuses on 802.11-based wireless communication in VANETs. It reviews some presented methods for vehicle movement path prediction, and explains some algorithms are explained for performance improvement in opportunistic networks based on the predicted vehicle movements. The chapter considers the fact that communication in VANETs can be infrastructure-based or infrastructureless. It also reviews some methods to apply the predicted vehicles' position for improving communication in infrastructure-based and infrastructureless VANETs, respectively. Opportunistic routing algorithms can be classified according to their dependency on roadside infrastructure. The chapter presents the taxonomy of opportunistic routing in VANETs.