Exploring VANET Using Edge Computing and SDN

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.

Vehicular Ad-hoc Networks (VANET) have emerged as a viable solution for the network related problems in Intelligent Transportation Systems (ITSs). However, with its current architecture, especially with the unavailability of the global network information, VANET has not been able to fulfill some of the necessities for efficient information dissemination and most critically, still lacks flexibility and programmability. Recently, Software Defined Networking (SDN) has been introduced into the vehicular domain in order to overcome the shortcomings in VANET. SDN is capable of handling the dynamic nature of networks with intelligent applications while lowering operational costs through simplified hardware and software. Yet, the architectural limitations of the presented Software Defined Vehicular Networks (SDVN), especially the centralization of control plane and its placement, have imposed doubts on its usability especially in the midst of stringent delay requirement of VANET applications.

<p>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.</p>

Vehicular ad hoc network (VANET) has attracted more attention for providing safe and efficient traffic management in the modern roads. Performance of the VANET depends on proper routing protocol, mobility management, and efficient inter-vehicular communications. To ensure the optimal data forwarding and energy efficiency in VANET, a suitable network hierarchy is required. In this paper, we propose a new optical network-based clustering hierarchy (ONCH) to improve the quality of services of the VANET. In the proposed scheme, the road side units (RSUs) of a VANET will be divided into several small groups called clusters. In each cluster, an RSU will act as gateway node and each gateway node will be connected to the WiMAX base station through optical fiber. We have analyzed the performance of the proposed ONCH scheme by numerical simulations. The simulated results prove that the ONCH scheme of VANET provides higher energy efficiency than the conventional wireless network-based clustering hierarchy (WNCH) scheme of VANET.

Digital twins and the Internet of Things (IoT) have gained significant research attention in recent years due to their potential advantages in various domains, and vehicular ad hoc networks (VANETs) are one such application. VANETs can provide a wide range of services for passengers and drivers, including safety, convenience, and information. The dynamic nature of these environments poses several challenges, including intermittent connectivity, quality of service (QoS), and heterogeneous applications. Combining intelligent technologies and software-defined networking (SDN) with VANETs (termed intelligent software-defined vehicular networks (iSDVNs)) meets these challenges. In this context, several types of research have been published, and we summarize their benefits and limitations. We also aim to survey stochastic modeling and performance analysis for iSDVNs and the uses of machine-learning algorithms through digital twin networks (DTNs), which are also part of iSDVNs. We first present a taxonomy of SDVN architectures based on their modes of operation. Next, we survey and classify the state-of-the-art iSDVN routing protocols, stochastic computations, and resource allocations. The evolution of SDN causes its complexity to increase, posing a significant challenge to efficient network management. Digital twins offer a promising solution to address these challenges. This paper explores the relationship between digital twins and SDN and also proposes a novel approach to improve network management in SDN environments by increasing digital twin capabilities. We analyze the pitfalls of these state-of-the-art iSDVN protocols and compare them using tables. Finally, we summarize several challenges faced by current iSDVNs and possible future directions to make iSDVNs autonomous.

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) is a backbone of intelligent transportation system that is envisaged to play a significant role in the futuristic smart cities for safety and traffic management. Designing an optimal multi‐hop routing protocol with lower transmission delay and reduced overhead has remained to be a challenge owing to the inability of existing VANET architecture to handle scalability and flexibility efficiently. The present work incorporates an emerging network paradigm called software defined network (SDN) in VANETs. The SDN provides a global view of the network topology and includes programmability to vehicular networks. The architecture manages the complex and highly dynamic vehicular network in an abstract and simplified way by decoupling the control plane from the data plane. The work introduces a SDN‐enabled connectivity‐aware geographical routing protocol (SCGRP), a performance‐enhanced protocol for an optimised transmission of data packets. The SCGRP is simulated using MININET‐Wi‐Fi and SUMO and the results are evaluated over the existing centralised routing protocol (CRP) routing protocol to prove its better performance.

Vehicular Ad Hoc Network (VANET) is a promising area of research and development as it has remarkable role in improving safety of vehicles on road, efficient traffic management, and providing comfort to commuters. The typical characteristics of VANET environment pose several challenges for VANET application developers. There is always a demand for scalable communication mechanisms suitable for low- and high-speed vehicles, information dissemination techniques that suit sparse and dense traffic conditions. Thus, the reliability of any VANET application strongly depends upon the robustness of the underlying communication architecture. Any VANET communication model shall strictly adhere to the wireless access standards and specifications laid down for vehicular communications. In this work, we have designed and implemented a basic VANET communication model that facilitates both Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication adhering to IEEE 802.11p standards. The Physical and Link Layer extensions of WAVE standard have been integrated to EXata5.1 (network emulator) to support IEEE 802.11p communication. Necessary Graphical User Interface and library level extensions were made to create VANET scenarios. To demonstrate and evaluate our communication model, urban scenarios with different node densities were created in EXata. The communication scenarios were emulated with predefined mobility of nodes, CBR as the traffic application and Bellman Ford as the default routing protocol. Using EXata analyzer, the performance metrics were analyzed and found that our basic VANET communication model offers good throughput at high vehicle densities with a soft delay constraint.

With the rising interest of expedient, safe, and high-efficient transportation, vehicular ad hoc networks (VANETs) have turned into a critical technology in smart transportation systems. Because of the high mobility of nodes, VANETs are vulnerable to security attacks. In this paper, we propose a novel framework of software-defined VANETs with trust management. Specifically, we separate the forwarding plane in VANETs from the control plane, which is responsible for the control functionality, such as routing protocols and trust management in VANETs. Using the on-demand distance vector routing (TAODV) protocol as an example, we present a routing protocol named software-defined trust based ad hoc on-demand distance vector routing (SD-TAODV). Simulation results are presented to show the effectiveness of the proposed software-defined VANETs with trust management.

Vehicular ad hoc networks (VANETs) have been widely recognized as a promising solution to improve traffic safety and efficiency for the ability to provide situation awareness even though the potential dangers and traffic anomalies are out of the visual range. In VANETs, time-division multiple access (TDMA) based overlay protocols can prevent transmission collisions, and play an important role in providing an efficient communication channel. However, due to high vehicle mobility and time-varying traffic flow, the existing TDMA-based slot allocation approaches cannot fully utilize the channel resources, which may result in high transmission delay and packet collision. To overcome these shortcomings, we propose a traffic-aware TDMA-based MAC (TA-MAC) protocol which utilizes the capability of mobile edge computing (MEC) in this paper. Specifically, based on MEC and vehicle-to-road-side-units (V2R) communications, a traffic-aware mechanism is first proposed to estimate the traffic condition on the road segment. Then, we propose a new slot assignment method that aims at guaranteeing the high channel utilization and low delay of safety message under dynamic traffic conditions. Finally, we conduct extensive experiments to demonstrate the effectiveness of the proposed protocol.

Road safety applications envisaged for vehicular ad hoc networks (VANETs) depend largely on the exchange of messages to deliver information to concerned vehicles. Safety applications as well as inherent VANET characteristics make data dissemination an essential service and a challenging task. We are developing a decentralized efficient solution for broadcast data dissemination through two game-theoretical mechanisms. Besides, VANETs can also include autonomous vehicles (AVs). AVs might represent a revolutionary new paradigm that can be a reality in our cities in the next few years. AVs do not need a driver to work; instead, they should copy a proper human behavior to adapt the driving according to the current circumstances, such as speed limit, pedestrian crossing street or wheather conditions. We will develop an AV software module including artificial intelligence (AI) techniques so that AVs can interact with the dynamic scenario throughout time. Finally, we also will include electrical vehicles (EV) in the VANET, so that special services such as finding and reserving an EV charging station place will be welcome. In addition, we are developing a multimetric geographic routing protocol for VANETs to transmit H.265 video (traffic accident, traffic state, commercial….) over VANETs.

Vehicular ad hoc networks (VANETs) are used in intelligent transportation systems to provide safety and security with a reduction in traffic jams using vehicle-to-vehicle (V2V) and vehicle-to-roadside (V2R) unit communications. During the communication, nodes are always under various security threads. In order to reduce the possibility of these attacks and to normalize traffic flow in the network, a software-defined network (SDN) is used. SDN will improve centralized visibility as all the underlying open flow switches are connected to the controller, which will reduce the routing load in the network. SDN doesn’t provide a high level of security to the network, hence protocols like encryption, hashing, etc. are applied to the VANET. In the paper, SDN based blockchain algorithm is applied, which coordinates network traffic and improves the overall security of the network. Security analysis of the proposed algorithm demonstrates that blockchain with encrypted SDN removes more than 90% of the network attacks as compared to its non- blockchain SDN.

Vehicular ad-hoc network (VANET) is the key component of intelligent transportation system (ITS) for various services like road safety and traffic efficiency. However, current VANET architectures provide less flexibility and scalability for vehicle-to-vehicle communication because of static underlying network infrastructure. Based on the software defined networking (SDN), open programmable networks through logically centralized control, this paper proposes a VANET monitoring system to provide a resilient and efficient routing for better services for communication between vehicles. It also provides the secure channels between the SDN controller and the network devices for reliable communication. Experimental results show that our proposed system selects the best path according less network latency in VANET.

Vehicular Ad hoc Networks (VANETs) become increasingly popular in academia and manufacturing businesses. The VANETs domain attracts massive attention from various authors all over the world on a large scale. However, substantial research efforts are expected in the VANETs field to solve the data congestion problem. For this, it is vital to state the current status of research in this domain. As the research publications have substantially increased since 2009, a bibliometric analysis is necessary for researchers to understand actual results and findings in this area. This paper examines and analyzes the status of research trends between 2010 and 2019 for the domain “Data congestion in VANETs” by applying various parameters. As extracted from the Scopus database till December 31, 2019, a total of 11,109 publications are associated with the VANETs domain. Moreover, 434 publications among the collection are related to data congestion in the VANETs field. Finally, a software tool named the VOSviewer is used to create and envision the selected field’s bibliometric networks. This analysis paper will help the researchers to catch the research trends of data congestion in VANETs.

In the last few years, the emerging network architecture paradigm of Software-Defined Networking (SDN), has become one of the most important technology to manage large scale networks such as Vehicular Ad-hoc Networks (VANETs). Recently, several works have shown interest in the use of SDN paradigm in VANETs. SDN brings flexibility, scalability and management facility to current VANETs. However, almost all of proposed Software-Defined VANET (SDVN) architectures are infrastructure-based. This paper will focus on how to enable SDN in infrastructure-less vehicular environments. For this aim, we propose a novel distributed SDN-based architecture for uncovered infrastructure-less vehicular scenarios. It is a scalable cluster-based architecture with distributed mobile controllers and a reliable fallback recovery mechanism based on self-organized clustering and failure anticipation.