Software-defined Vehicular Ad Hoc Networks Research Articles

S2DN: Design of robust authentication protocol with session key establishment in multi-controller based software-defined VANETs

Advancements in technology and the adoption of innovative developments have significantly simplified our lives. One notable innovation in the networking domain is Software Defined Networking (SDN), which revolutionizes the network layer by enabling centralized network administration and re-programmability. SDN technology finds application in diverse fields such as Vehicular Ad-hoc Networks (VANETs), Wireless Sensor Networks (WSNs), Internet of Things (IoT) communications, and cloud-fog computing. The integration of SDN technology into VANET systems has notably improved network performance but has also raised security concerns. To tackle this issue, this paper focuses on devising an authentication mechanism to facilitate secure communication across various VANET levels by establishing a shared session key. Moreover, the research proposes a method to mitigate the challenge of single points of failure, a typically difficult issue to address. To ensure the security of all confidential information during protocol execution, simulations are conducted using the Scyther tool. Additionally, an informal security analysis is performed, demonstrating the robustness of the proposed protocol. The proposed protocol also performs outstanding in terms of performance results

RC-LAHR: Road-Side-Unit-Assisted Cloud-Based Location-Aware Hybrid Routing for Software-Defined Vehicular Ad Hoc Networks.

The reliability of the communication link is quite common and challenging to handle as the topology changes frequently in vehicular ad hoc networks (VANETs). Another problem with VANETs is that the vehicles are from different manufacturers. Hence, the heterogeneity of hardware is obvious. These heterogeneity and reliability problems affect the message dissemination in VANETs. This paper aims to address these challenges by proposing a robust routing protocol capable of ensuring reliable, scalable, and heterogeneity-tolerant message dissemination in VANETs. We first introduced a hybrid hierarchical architecture based on software-defined networking (SDN) principles for VANETs, leveraging SDN's inherent scalability and adaptability to heterogeneity. Further, a road-side unit (RSU)-assisted cloud-based location-aware hybrid routing for software-defined VANETs (SD-VANETs) that we call RC-LAHR was proposed. RC-LAHR was rigorously tested and analyzed for its performance in terms of packet delivery ratio (PDR) and end-to-end delay (EED), along with a comprehensive assessment of network traffic and load impacts on cloud infrastructure and RSUs. The routing protocol is compared with state-of-the-art protocols, Greedy Perimeter Stateless Routing (GPSR) and Opportunistic and Position-Based Routing (OPBR). The proposed routing protocol performs well as compared to GPSR and OPBR. The result shows that the EED is reduced to 20% and the PDR is increased to 30%. The network reliability is also increased up to 5% as compared to the OPBR and GPSR.

Secure Computation Offloading in Vehicle Networks Based on Block Chains

Abstract: VANETs (vehicular ad hoc networks) have become an essential component of current intelligent transportation systems (ITS). However, under the influence of hostile mobile vehicles, security threats pose a threat to offloading vehicle duties to the cloud server. How to address the complicated computation offloading of vehicles while assuring the cloud server's high security is an essential research subject. We investigated the safety and offloading of a multi-vehicle ECCO system based on cloud blockchain in this research. To begin, we present a distributed hierarchical software-defined VANET (SDVs) framework to construct a security architecture in order to attain agreement in the vehicular context. Second, to increase offloading security, we suggest using blockchain-based access management, which protects the cloud from unauthorised offloading. Finally, we decide task offloading by jointly optimising offloading decisions, consensus mechanism decisions, computation resource allocation, and channel bandwidth to tackle the intense computing problem of approved vehicles.

FSAQoS

To ensure a successful transfer of messages in Vehicular Ad hoc Networks (VANETs), data communication channels between vehicles must meet specific standards. As a result, determining the Quality of Service (QoS) of the communication links established among vehicles is a critical task. In this paper, we present a Fuzzy System for Assessment of Quality of Service (FSAQoS), in which we consider two models (FSAQoS1 and FSAQoS2) to assess QoS in Software-Defined VANETs (SDN-VANETs). FSAQoS1 takes into consideration the latency of message transmission between neighboring vehicles, the reliability of data exchange, as well as the beacon signals disseminated across the network that inform vehicles about the state and location of their neighbors. In addition to these parameters, FSAQoS2 considers the interference of the concurrent transmission of nearby vehicles. We evaluate the proposed system by computer simulations. From the evaluation results, we see that FSAQoS2 shows better results than FSAQoS1, although its complexity is higher.

An Intelligent Approach for Cloud-Fog-Edge Computing SDN-VANETs Based on Fuzzy Logic: Effect of Different Parameters on Coordination and Management of Resources.

The integration of cloud-fog-edge computing in Software-Defined Vehicular Ad hoc Networks (SDN-VANETs) brings a new paradigm that provides the needed resources for supporting a myriad of emerging applications. While an abundance of resources may offer many benefits, it also causes management problems. In this work, we propose an intelligent approach to flexibly and efficiently manage resources in these networks. The proposed approach makes use of an integrated fuzzy logic system that determines the most appropriate resources that vehicles should use when set under various circumstances. These circumstances cover the quality of the network created between the vehicles, its size and longevity, the number of available resources, and the requirements of applications. We evaluated the proposed approach by computer simulations. The results demonstrate the feasibility of the proposed approach in coordinating and managing the available SDN-VANETs resources.

A QoS-Aware Fuzzy-Based System for Assessment of Edge Computing Resources in SDN-VANETs

Vehicular ad hoc networks (VANETs) face resource management challenges due to their dynamic network topology and massive amount of data generated by the ever-increasing number of vehicles. In this paper, the authors implement a fuzzy-based system for assessment of neighboring vehicles processing capability (FS-ANVPC), in which they consider two models (FS-ANVPC1 and FS-ANVPC2) to assess the available edge computing resources in software-defined VANETs. The proposed system determines the processing capability of each neighboring vehicle, and based on the final value, it can be decided whether the edge layer can be used by the vehicles in need of additional resources. FS-ANVPC1 takes into consideration the available resources of the neighboring vehicles and the predicted contact duration between them and the vehicle in need, while FS-ANVPC2 includes in addition the quality of service of the communication link among vehicles. The authors evaluate the proposed system by computer simulations. From the evaluation results, they see that FS-ANVPC2 shows better results than FS-ANVPC1 although its complexity is higher.

A fuzzy-based approach for resource management in SDN-VANETs: Effect of trustworthiness on assessment of available edge computing resources

Vehicular Ad hoc Networks (VANETs) aim to improve the efficiency and safety of transportation systems by enabling communication between vehicles and roadside units, without relying on a central infrastructure. However, since there is a tremendous amount of data and significant number of resources to be dealt with, data and resource management become their major issues. Cloud, Fog and Edge computing, together with Software Defined Networking (SDN) are anticipated to provide flexibility, scalability and intelligence in VANETs while leveraging distributed processing environment. In this paper, we consider this architecture and implement and compare two Fuzzy-based Systems for Assessment of Neighboring Vehicles Processing Capability (FS-ANVPC1 and FS-ANVPC2) to determine the processing capability of neighboring vehicles in Software Defined Vehicular Ad hoc Networks (SDN-VANETs). The computational, networking and storage resources of vehicles comprise the Edge Computing resources in a layered Cloud-Fog-Edge architecture. A vehicle which needs additional resources to complete certain tasks and process various data can use the resources of the neighboring vehicles if the requirements to realize such operations are fulfilled. The proposed systems are used to assess the processing capability of each neighboring vehicle and based on the final value, it can be determined whether the edge layer can be used by the vehicles in need. FS-ANVPC1 takes into consideration the available resources of the neighboring vehicles and the predicted contact duration between them and the present vehicle, while FS-ANVPC2 includes in addition the vehicles trustworthiness value. Our systems take also into account the neighboring vehicles’ willingness to share their resources and determine the processing capability for each neighbor. We evaluate the proposed systems by computer simulations. The evaluation results show that FS-ANVPC1 decides that helpful neighboring vehicles are the ones that are predicted to be within the vehicle communication range for a while and have medium/large amount of available resources. FS-ANVPC2 considers the same neighboring vehicles as helpful neighbors only if they have at least a moderate trustworthiness value ( VT = 0.5). When VT is higher, FS-ANVPC2 takes into consideration also neighbors with less available resources.

Blockchain-Based Secure Computation Offloading in Vehicular Networks

Vehicular ad hoc networks (VANETs) has become an important part of modern intelligent transportation systems (ITS). However, under the influence of malicious mobile vehicles, offloading vehicle tasks to the cloud server is threatened by security attacks. Edge cloud offloading (ECCO) has considered a promising approach to enable latency-sensitive VANET. How to solve the complex computation offloading of vehicles while ensuring the high security of the cloud server is an issue that needs urgent research. In this paper, we studied the safety and offloading of multi-vehicle ECCO system based on cloud blockchain. First, to achieve consensus in the vehicular environment, we propose a distributed hierarchical software-defined VANET (SDVs) framework to establish a security architecture. Secondly, to improve the security of offloading, we propose to use blockchain-based access control, which protects the cloud from illegal offloading actions. Finally, to solve the intensive computing problem of authorized vehicles, we determine task offloading via jointly optimizing offloading decisions, consensus mechanism decisions, allocation of computation resources and channel bandwidth. The optimization method is designed to minimize long-term system of delays, energy consumption, and flow costs for all vehicles. To better resolve the proposed offloading method, we develop a new deep reinforcement learning (DRL) algorithm via utilizing extended deep Q-networks. We evaluate the performance of our framework on access control and offloading through numerical simulations, which have significant advantages over existing solutions.

Security and design requirements for software-defined VANETs

The evolving of Fifth Generation (5G) networks is becoming more readily available as a significant driver of the growth of new applications and business models. Vehicular Ad hoc Networks (VANETs) and Software Defined Networking (SDN) represent the critical enablers of 5G technology with the development of next-generation intelligent vehicular networks and applications. In recent years, researchers have focused on the integration of SDN and VANET, and looked at different topics related to the architecture, the benefits of software-defined VANET services, and the new functionalities to adapt them. However, the security and robustness of the complete architecture is still questionable and have been largely neglected by the research community. Moreover, the deployment and integration of different entities and several architectural components drive new security threats and vulnerabilities.In this paper, first, we survey the state-of-the-art SDN based Vehicular ad-hoc Network (SDVN) architectures for their networking infrastructure design, functionalities, benefits, and challenges. Then we discuss these architectures against major security threats that violate the key security services such as availability, privacy, authentication, and data integrity. We also discuss different countermeasures for these threats. Finally, we present the lessons learned with the directions of future research work towards provisioning stringent security solutions in new SDVN architectures. To the best of our knowledge, this is the first work that presents a comprehensive survey and security analysis on SDVN architectures, and we believe that it will help researchers to address various challenges (e.g., flexible network management, control and high resource utilization, and scalability) in vehicular communication systems which are required to improve the future Intelligent Transportation Systems (ITS).

Blockchain-Based Distributed Software-Defined Vehicular Networks: A Dueling Deep ${Q}$ -Learning Approach

Vehicular ad hoc networks (VANETs) have become an essential part in smart transportation systems of modern cities. However, because of dynamicity and infrastructure-less of VANETs, the ever increasing number of network security issues become obstacles for the realization of smart cities. Software-defined VANETs have provided a reliable way to manage VANETs dynamically and securely. However, the traditionally centralized control plane makes it vulnerable to malicious nodes and results in performance degradation. Therefore, a distributed control plane is necessary. How to reach a consensus among multiple controllers under complex vehicular environment is an essential problem. In this paper, we propose a novel blockchain-based distributed software-defined VANET framework (block-SDV) to establish a secure architecture to overcome the above issues. The trust features of blockchain nodes, the number of consensus nodes, trust features of each vehicle, and the computational capability of the blockchain are considered in a joint optimization problem, which is modeled as a Markov decision process with state space, action space and reward function. Since it is difficult to be solved by traditional methods, we propose a novel dueling deep ${Q}$ -learning (DDQL) with prioritized experience replay approach. Simulation results are presented to show the effectiveness of the proposed block-SDV framework.

A Hierarchical Routing Scheme With Load Balancing in Software Defined Vehicular Ad Hoc Networks

The vast majority of routing approaches for vehicular ad hoc networks (VANETs) are distributed, which are ineffective to exploit the global networking information and easily lead to local optimum, appearing as sparse connectivity and network congestion. Recently, by combining software-defined network architecture together with VANETs, software-defined VANETs (SDVN) is widely concerned, which shows the benefits of centralized control. In this paper, we propose a hierarchical geography routing protocol for SDVN. First, the protocol divides a large region into multiple small grids according to the geographical location and finds a series of grids with good connectivity based on real-time grid vehicle density and historical vehicle transfer probability between grids. Second, we construct a path cost function with load balancing and keep two paths with minimal costs from the selected grids. Finally, a series of relay nodes on each selected path are filtered for routing according to node utility. Simulation results show that the proposed routing algorithm achieves significant gains in terms of delivery ratio, throughput, average delay, and average hop count compared with several existing routing protocols.

Exploiting Interference for Capacity Improvement in Software-Defined Vehicular Networks

Vehicular ad hoc networks (VANETs), which are deployed along roads, make traffic systems safer and more efficient. The existing theoretical results on capacity scaling laws provide insights and guidance for designing and deploying VANETs. As a new paradigm of VANETs, software-defined vehicular ad hoc networks (SDVANETs) separate the data plane from the control plane. For many prospective applications, software-defined technology will be used in VANETs to achieve some general targets, such as network management. Therefore, a capacity analysis is critical and necessary for SDVANETs. In this paper, we propose a new fundamental framework named real vehicular wireless network model (RVWNM), which enables a more realistic capacity analysis in SDVANETs. We first introduce a Euclidean planar graph that can be constructed from any real map of an urban area and that represents the practical geometry structure of the urban area. Then, an interference relationship graph is abstracted from the Euclidean planar graph, which considers the transmission interference relations among the nodes in the network. Finally, we theoretically analyze the interference relationships in the interference relationship graph. A practical geometrical structure is used to calculate the asymptotic capacity of SDVANETs. To verify the feasibility of RVWNM, we calculate the asymptotic capacity of social-proximity urban networks. We also consider the social-proximity-based mobility of vehicles, and we derive asymptotic capacity bounds for sparse SDVANETs and constant bounds for high-density SDVANETs.

Control Plane Optimization in Software-Defined Vehicular Ad Hoc Networks

The vehicle ad hoc network (VANET) is an emerging network technology that is expected to be cost-effective and adaptable, making it ideal to provide network connection service to drivers and passengers on today's roads. In the next generation of VANETs with fifth-generation (5G) networks, software-defined networking (SDN) technology will play a very important role in network management. However, for infotainment applications, high latency in VANET communication imposes a great challenge for network management, whereas direct communication through the cellular networks brings high cost. In this paper, we present an optimizing strategy to balance the latency requirement and the cost on cellular networks, in which we encourage vehicles to send the SDN control requests through the cellular networks by rebating network bandwidth. Furthermore, we model the interaction of the controller and vehicles as a two-stage Stackelberg game and analyze the game equilibrium. From the experimental results, the optimal rebating strategy provides smaller latency than other control plane structures.