Showing papers on "Wireless ad hoc network published in 2020"

Named Data Networking in Vehicular Ad Hoc Networks: State-of-the-Art and Challenges

Abstract: Information-centric networking (ICN) has been proposed as one of the future Internet architectures. It is poised to address the challenges faced by today’s Internet that include, but not limited to, scalability, addressing, security, and privacy. Furthermore, it also aims at meeting the requirements for new emerging Internet applications. To realize ICN, named data networking (NDN) is one of the recent implementations of ICN that provides a suitable communication approach due to its clean slate design and simple communication model. There are a plethora of applications realized through ICN in different domains where data is the focal point of communication. One such domain is intelligent transportation system realized through vehicular ad hoc network (VANET) where vehicles exchange information and content with each other and with the infrastructure. Up to date, excellent research results have been yielded in the VANET domain aiming at safe, reliable, and infotainment-rich driving experience. However, due to the dynamic topologies, host-centric model, and ephemeral nature of vehicular communication, various challenges are faced by VANET that hinder the realization of successful vehicular networks and adversely affect the data dissemination, content delivery, and user experiences. To fill these gaps, NDN has been extensively used as underlying communication paradigm for VANET. Inspired by the extensive research results in NDN-based VANET, in this paper, we provide a detailed and systematic review of NDN-driven VANET. More precisely, we investigate the role of NDN in VANET and discuss the feasibility of NDN architecture in VANET environment. Subsequently, we cover in detail, NDN-based naming, routing and forwarding, caching, mobility, and security mechanism for VANET. Furthermore, we discuss the existing standards, solutions, and simulation tools used in NDN-based VANET. Finally, we also identify open challenges and issues faced by NDN-driven VANET and highlight future research directions that should be addressed by the research community.

Survey on the Internet of Vehicles: Network Architectures and Applications

Abstract: The vehicular ad hoc network (VANET) has been widely used as an application of mobile ad hoc networking in the automotive industry. However, in the 5G/B5G era, the Internet of Things as a cutting-edge technology is gradually transforming the current Internet into a fully integrated future Internet. At the same time, it will promote the existing research fields to develop in new directions, such as smart home, smart community, smart health, and intelligent transportation. The VANET needs to accelerate the pace of technological transformation when it has to meet the application requirements of intelligent transportation systems, vehicle automatic control, and intelligent road information service. Based on this context, the Internet of Vehicles (IoV) has come into being, which aims to realize the information exchange between the vehicle and all entities that may be related to it. IoV's goals are to reduce accidents, ease traffic congestion, and provide other information services. At present, IoV has attracted much attention from academia and industry. In order to provide assistance to relevant research, this article designs a new network architecture for the future network with greater data throughput, lower latency, higher security, and massive connectivity. Furthermore, this article explores a comprehensive literature review of the basic information of IoV, including basic VANET technology, several network architectures, and typical application of IoV.

BPAS: Blockchain-Assisted Privacy-Preserving Authentication System for Vehicular Ad Hoc Networks

Abstract: If all vehicles are connected together through a wireless communication channel, vehicular ad hoc networks (VANETs) can support a wide range of real-time traffic information services, such as intelligent routing, weather monitoring, emergency call, etc. However, the accuracy and credibility of the transmitted messages among the VANETs are of paramount importance as life may depend on it. In this article we introduce a novel framework called blockchain-assisted privacy-preserving authentication system (BPAS) that provides authentication automatically in VANETs and preserves vehicle privacy at the same time. This design is highly efficient and scalable. It does not require any online registration centre (except for system initialization and vehicle registration), and allows conditional tracing and dynamic revocation of misbehaving vehicles. In this article, we conduct an in-depth security analysis and a comprehensive performance evaluation (which is based on the Hyperledger Fabric platform) for our proposed framework. The results demonstrate that our framework is an efficient solution for the development of a decentralized authentication system in VANETs.

A Blockchain-SDN-Enabled Internet of Vehicles Environment for Fog Computing and 5G Networks

Abstract: The goal of intelligent transport systems (ITSs) is to enhance the network performance of vehicular ad hoc networks (VANETs). Even though it presents new opportunities to the Internet of Vehicles (IoV) environment, there are some security concerns including the need to establish trust among the connected peers. The fifth-generation (5G) communication system, which provides reliable and low-latency communication services, is seen as the technology to cater for the challenges in VANETs. The incorporation of software-defined networks (SDNs) also ensures an effective network management. However, there should be monitoring and reporting services provided in the IoV. Blockchain, which has decentralization, transparency, and immutability as some of its properties, is designed to ensure trust in networking platforms. In that regard, this article analyzes the combination of blockchain and SDN for the effective operation of the VANET systems in 5G and fog computing paradigms. With managerial responsibilities shared between the blockchain and the SDN, it helps to relieve the pressure off the controller due to the ubiquitous processing that occurs. A trust-based model that curbs malicious activities in the network is also presented. The simulation results substantially guarantee an efficient network performance, while also ensuring that there is trust among the entities.

Routing in Flying Ad Hoc Networks: A Comprehensive Survey

Abstract: The use of unmanned aerial vehicles (UAVs) is attracting considerable interest in academic research, commercial, and military applications. Multi-UAV systems organized in an ad hoc fashion called a flying ad hoc network (FANET) can cooperatively and collaboratively accomplish complex missions more efficiently compared to single large UAV systems. However, the unique features of FANETs such as high mobility, low node density, and high frequency of topology changes introduce challenges to the communication design, especially routing. Thus, the routing requirements of FANETs surpass those of MANETs or VANETs. In this paper, we present UAV classification, communication and application architectures, and an exhaustive survey of the existing routing protocols for flying ad hoc networks. Furthermore, we highlight the key features, strengths and weaknesses, and different mobility models used for the performance evaluation of the existing FANET routing protocols. More importantly, a proposed taxonomy and a review on the existing FANET routing protocols are presented. Finally, we highlight the existing challenges and open research issues.

Edge Computing in VANETs-An Efficient and Privacy-Preserving Cooperative Downloading Scheme

Abstract: With the advancements in social media and rising demand for real traffic information, the data shared in vehicular ad hoc networks (VANETs) indicate that the size and amount of requested data will continue increasing. Vehicles in the same area often have similar data downloading requests. If we ignore the common requests, the resource allocation efficiency of the VANET system will be quite low. Motivated by this fact, we propose an efficient and privacy-preserving data downloading scheme for VANETs, based on the edge computing concept. In the proposed scheme, a roadside unit (RSU) can find the popular data by analyzing the encrypted requests sent from nearby vehicles without having to sacrifice the privacy of their download requests. Further, the RSU caches the popular data in nearby qualified vehicles called edge computing vehicles (ECVs). If a vehicle wishes to download the popular data, it can download it directly from the nearby ECVs. This method increases the downloading efficiency of the system. The security analysis results show that the proposed scheme can resist multiple security attacks. The performance analysis results demonstrate that our scheme has reasonable computation and communication overhead. Finally, the OMNeT++ simulation results indicate that our scheme has good network performance.

Smart IoT Control-Based Nature Inspired Energy Efficient Routing Protocol for Flying Ad Hoc Network (FANET)

Abstract: The increasing demand of routing in the field of communication is the most important subject in ad hoc networks now a days. Flying Ad Hoc Network (FANET) is one of the emerging areas that evolved from Mobile Ad Hoc Networks. Selecting the best optimal path in any network is a real challenge for a routing protocol. Because the network performance like throughput, Quality of Service (QoS), user experience, response time and other key parameters depend upon the efficiency of the algorithm running inside the routing protocol. The complexity and diversity of the problem is augmented due to dynamic spatial and temporal mobility of FANET nodes. Due to these challenges the performance and efficiency of the routing protocol becomes very critical. This paper presents a novel routing protocol for FANET using modified AntHocNet. Ant colony optimization technique or metaheuristics in general has shown better dependability and performance as compared to other legacy best path selection techniques. Energy stabilizing parameter introduced in this study improves energy efficiency and overall network performance. Simulation results show that the proposed protocol is better than generic Ant Colony Optimization (ACO) and other traditional routing protocols utilized in FANET.

IGAN-IDS: An imbalanced generative adversarial network towards intrusion detection system in ad-hoc networks

Abstract: With the emergence of ever-advancing network threats, the guarantee of system security becomes increasingly crucial, especially in the dynamic and decentralized ad-hoc networks. One essential part of cybersecurity is intrusion detection, which identifies anomalous activities according to traffic patterns. However, the class-imbalanced data have caused a challenging problem where the number of abnormal samples is significantly lower than that of the normal ones. This class imbalance problem confines the performance of intrusion classifiers and results in low robustness to unknown anomalies. In this paper, we propose a novel Imbalanced Generative Adversarial Network (IGAN) to tackle the class imbalance problem. In the primary novelty of our model, we introduce an imbalanced data filter and convolutional layers to the typical GAN, generating new representative instances for minority classes. Further, an IGAN-based Intrusion Detection System, namely IGAN-IDS, is established to cope with class-imbalanced intrusion detection, using the instances generated by IGAN. Concretely, IGAN-IDS consists of three modules: feature extraction, IGAN, and deep neural network. First, we utilize a feed-forward neural network (FNN) to transform raw network attributes into feature vectors. Then, the IGAN generates new samples expressed in the latent space. Finally, the deep neural network, composed of convolutional layers and fully-connected layers, executes the final intrusion detection. We conduct experiments on three benchmark datasets to evaluate the performance of IGAN-IDS, comparing against 15 other methods. The experimental results demonstrate that our proposed IGAN-IDS outperforms the state-of-the-art approaches.

Reliable Data Transmission Model for Mobile Ad Hoc Network Using Signcryption Technique

Abstract: In recent years, the need for high security with reliability in the wireless network has tremendously been increased. To provide high security in reliable networks, mobile ad hoc networks (MANETs) play a top role, like open network boundary, distributed network, and fast and quick implementation. By expanding the technology, the MANET faces a number of security challenges due to self-configuration and maintenance capabilities. Besides, traditional security solutions for wired networks are ineffective and inefficient because of the nature of highly dynamic and resource-constrained MANETs. In this paper, the researchers focus on improving reliable data transmission with high security in the MANET using an optimization technique. In the proposed MANET system, the nodes are clustered by utilizing an energy-efficient routing protocol. Then, the modified discrete particle swarm optimization is used to select the optimal cluster head. A secured routing protocol and a signcryption model can be used to improve the transmission security of the reliable MANET. The signcryption algorithm encrypts the digital signature, which can enhance the overall efficiency and confidentiality. The security-based analysis is performed on the basis of packet delivery ratio, energy consumption, network lifetime, and throughput. Finally, the result demonstrates that the MANET with optimization techniques achieves a high transmission rate and improves the reliable data security.

Physical Layer Security in Vehicular Networks with Reconfigurable Intelligent Surfaces

Abstract: This paper studies the physical layer security (PLS) of a vehicular network employing a reconfigurable intelligent surface (RIS). RIS technologies are emerging as an important paradigm for the realisation of smart radio environments, where large numbers of small, low-cost and passive elements, reflect the incident signal with an adjustable phase shift without requiring a dedicated energy source. Inspired by the promising potential of RIS-based transmission, we investigate two vehicular network system models: One with vehicle-to-vehicle communication with the source employing a RIS-based access point, and the other model in the form of a vehicular adhoc network (VANET), with a RIS-based relay deployed on a building. Both models assume the presence of an eavesdropper to investigate the average secrecy capacity of the considered systems. Monte-Carlo simulations are provided throughout to validate the results. The results show that performance of the system in terms of the secrecy capacity is affected by the location of the RIS-relay and the number of RIS cells. The effect of other system parameters such as source power and eavesdropper distances are also studied.

Security and privacy in vehicular ad hoc network and vehicle cloud computing : a survey

Abstract: Vehicular networks are becoming a prominent research field in the intelligent transportation system (ITS) due to the nature and characteristics of providing high-level road safety and optimized traffic management. Vehicles are equipped with the heavy communication equipment which requires a high power supply, on-board computing device, and data storage devices. Many wireless communication technologies are deployed to maintain and enhance the traffic management system. The ITS is capable of providing services to the traffic authorities and precautionary measures to the drivers and passengers. Several methods have been proposed for discussing the security and privacy issues for the vehicular ad hoc networks (VANETs) and vehicular cloud computing (VCC). They receive a great deal of attention from researchers around the world since they are new technologies, and they can improve road safety and enhance traffic flow by utilizing the vehicles resources and communication system. Firstly, the VANETs are presented, including the basic overview, characteristics, threats, and attacks. The location privacy methodologies are elaborated, which can protect the confidential information of the vehicle, such as the location detail and driver information. Secondly, the trust management models in the VANETs are comprehensively discussed, followed by the comparison of the cryptography and trust models in terms of different kinds of attacks. Then, the simulation tools and applications of the VANETs are discussed, and the evolution is presented from the VANETs to VCC in the vehicular network. Thirdly, the VCC is discussed from its architecture and the security and privacy issues. Finally, several research challenges on the VANETs and VCC are presented. In sum, this survey comprehensively covers the location privacy and trust management models of the VANETs and discusses the security and privacy issues in the VCC, which fills the gap of existing surveys. Also, it indicates the research challenges in the VANETs and VCC.

Federated Learning-Based Cognitive Detection of Jamming Attack in Flying Ad-Hoc Network

Abstract: Flying Ad-hoc Network (FANET) is a decentralized communication system solely formed by Unmanned Aerial Vehicles (UAVs). In FANET, the UAV clients are vulnerable to various malicious attacks such as the jamming attack. The aerial adversaries in the jamming attack disrupt the communication of the victim network through interference on the receiver side. Jamming attack detection in FANET poses new challenges for its key differences from other ad-hoc networks. First, because of the varying communication range and power consumption constraints, any centralized detection system becomes trivial in FANET. Second, the existing decentralized solutions, disregarding the unbalanced sensory data from new spatial environments, are unsuitable for the highly mobile and spatially heterogeneous UAVs in FANET. Third, given a huge number of UAV clients, the global model may need to choose a sub-group of UAV clients for providing a timely global update. Recently, federated learning has gained attention, as it addresses unbalanced data properties besides providing communication efficiency, thus making it a suitable choice for FANET. Therefore, we propose a federated learning-based on-device jamming attack detection security architecture for FANET. We enhance the proposed federated learning model with a client group prioritization technique leveraging the Dempster-Shafer theory. The proposed client group prioritization mechanism allows the aggregator node to identify better client groups for calculating the global update. We evaluated our mechanism with datasets from publicly available standardized jamming attack scenarios by CRAWDAD and the ns-3 simulated FANET architecture and showed that, in terms of accuracy, our proposed solution (82.01% for the CRAWDAD dataset and 89.73% for the ns-3 simulated FANET dataset) outperforms the traditional distributed solution (49.11% for the CRAWDAD dataset and 65.62% for the ns-3 simulated FANET dataset). Moreover, the Dempster-Shafer-based client group prioritization mechanism identifies the best client groups out of 56 client group combinations for efficient federated averaging.

Routing Protocols for Unmanned Aerial Vehicle-Aided Vehicular Ad Hoc Networks: A Survey

Abstract: In intelligent transportation systems, a vehicular ad hoc network (VANET) has a significant impact in enhancing road safety, traffic management efficiency, and in-vehicle infotainment features. Routing in a VANET is hampered by frequent link disconnection for non-line-of-sight communication due to roadside obstacles, high mobility, and frequent topological changes. With the help of three-dimensional movement capability, an unmanned aerial vehicle (UAV) can drastically improve the routing experience of a VANET, by increasing the line-of-sight probability, better connectivity, and efficient store-carry-forward mechanism. As a result, various routing protocols with different objectives have been reported for UAV-aided VANETs. Several surveys have been conducted based on different routing protocols for VANETs so far. However, to the best of the authors’ knowledge, no survey exists till now that dedicatedly covers routing protocols for UAV-aided VANETs. This survey paper presents a comprehensive review on state-of-the-art routing protocols for UAV-aided VANETs. The protocols are categorized into seven groups in terms of their working mechanism and design principles. The shortcomings of the protocols are identified individually by critically analyzing them with regard to their advantages, disadvantages, application areas, and future improvements. The routing protocols are qualitatively compared with each other in tabular format as well on the basis of various design aspects and system parameters. In particular, not only performance and special features but also optimization criteria and techniques are extensively discussed in addition to the tabular comparison. Furthermore, open research issues and challenges are summarized and discussed.

A Review of Applications, Characteristics and Challenges in Vehicular Ad Hoc Networks (VANETs)

Abstract: The density of traffic is increasing daily in the world. As a result, congestion, accidents, and pollution are also increasing. Vehicular ad hoc network VANET, a subclass of mobile ad hoc networks MANETs, is a promising approach for future intelligent transportation system its. These networks have no fixed infrastructure and instead rely on the vehicles themselves to provide network functionality. In this review paper, we present an overview of the concept of vehicular ad hoc networks, applications, characteristics. also, we will provide discuss some of the issues and challenges in VANET.

StabTrust—A Stable and Centralized Trust-Based Clustering Mechanism for IoT Enabled Vehicular Ad-Hoc Networks

Abstract: Vehicular Ad-hoc Network (VANET) is a modern era of dynamic information distribution among societies. VANET provides an extensive diversity of applications in various domains, such as Intelligent Transport System (ITS) and other road safety applications. VANET supports direct communications between vehicles and infrastructure. These direct communications cause bandwidth problems, high power consumption, and other similar issues. To overcome these challenges, clustering methods have been proposed to limit the communication of vehicles with the infrastructure. In clustering, vehicles are grouped together to formulate a cluster based on certain rules. Every cluster consists of a limited number of vehicles/nodes and a cluster head (CH). However, the significant challenge for clustering is to preserve the stability of clusters. Furthermore, a secure mechanism is required to recognize malicious and compromised nodes to overcome the risk of invalid information sharing. In the proposed approach, we address these challenges using components of trust. A trust-based clustering mechanism allows clusters to determine a trustworthy CH. The novel features incorporated in the proposed algorithm includes trust-based CH selection that comprises of knowledge, reputation, and experience of a node. Also, a backup head is determined by analyzing the trust of every node in a cluster. The major significance of using trust in clustering is the identification of malicious and compromised nodes. The recognition of these nodes helps to eliminate the risk of invalid information. We have also evaluated the proposed mechanism with the existing approaches and the results illustrate that the mechanism is able to provide security and improve the stability by increasing the lifetime of CHs and by decreasing the computation overhead of the CH re-selection. The StabTrust also successfully identifies malicious and compromised vehicles and provides robust security against several potential attacks.

Secure Authentication and Key Management With Blockchain in VANETs

Abstract: Nowadays, with rapid advancements of vehicular telematics and communication techniques, proliferation of vehicular ad hoc networks (VANETs) have been witnessed, which facilitates the construction of promising intelligent transportation system (ITS). Due to inherent wireless communicating features in open environment, secure transmission among numerous VANET entities remains crucial issues. Currently, lots of research efforts have been made, while most of which tend to allocate the universal group key to the verified devices for both vehicle-to-vehicle (V2V) and vehicle-to-RSU (V2R) communications. However, in heterogeneous VANET environment with large numbers of devices in same vehicular group, complicated and variable topologies lead to continuous key updating in every moment, causing interference to regular V2R data exchange, which is not reliable and efficient for resource-constrained VANET environment. Moreover, group membership recording and detecting mechanisms are necessary for real time vehicle revocation and participation, which has not been further studied so far. In this paper, we address the above issues by proposing a secure authentication and key management scheme. In our design, novel VANET system model with edge computing infrastructure is adopted so as to offer adequate computing and storing capacity compared to traditional VANET structure. Note that our certificateless authentication scheme applies the independent session key for each vehicle for interference avoidance. Furthermore, consortium blockchain is employed for V2V group key construction. Real time group membership arrangement with efficient group key updating is accordingly provided. Formal security proofs are presented, demonstrating that the proposed scheme can achieve desired security properties. Performance analysis is conducted as well, proving that the proposed scheme is efficient compared with the state-of-the-arts.

Internet of Vehicles

Abstract: Vehicular communication networks have emerged to enable numerous vehicular data services and applications. Conventional vehicular ad hoc networks (VANETs) are often operated in the ad hoc mode and mainly focus on road safety applications based on the connection between vehicles and roadside units (RSUs). To support vehicular communications, dedicated shortrange communication (DSRC) and car-to-car communication consortium (C2C-CC) have been initiated in the United States and Europe, respectively. With the new era of the Internet of Things (IoT), the conventional VANETs have evolved to the Internet of Vehicles (IoV). In IoV, each vehicle is envisioned as an intelligent object, equipped with sensing platforms, computing facilities, control units, and storages and is connected to any entity (other vehicles, RSUs, charging/gas stations, cloud, and so on) via vehicle-to-everything (V2X) communications. Intelligent vehicles can take different roles, i.e., being both a client and a server, taking and providing big data services, leading to numerous new IoV applications, from assisted/autonomous driving and platooning, secure information sharing and learning to traffic control and optimization.

Traffic Differentiated Clustering Routing in DSRC and C-V2X Hybrid Vehicular Networks

Abstract: Vehicles equipped with sensors can participate in mobile crowdsourcing applications. Vehicular Ad Hoc Networks (VANETs) based on Dedicated Short Range Communication (DSRC) are used to carry sensing data. However, multi-hop transmissions for gathering data to Road Side Units (RSUs) in VANETs suffer from low data rate and long end-to-end delay, which can hardly meet the QoS requirements of delay-sensitive services. This triggers the consideration of constituting a DSRC and Cellular-Vehicle-to-Everything (C-V2X) hybrid vehicular network. Nevertheless, using cellular links to carry traffic can cause high cellular bandwidth costs. In this paper, we propose a Traffic Differentiated Clustering Routing (TDCR) mechanism in a Software Defined Network (SDN)-enabled hybrid vehicular network. The proposed mechanism includes a centralized one-hop clustering approach and a data delivery optimization method. Particularly, the optimization is to make a tradeoff between cellular bandwidth cost and end-to-end delay, for Cluster Heads (CHs) delivering their aggregated data either by multi-hop Vehicle-to-Vehicle (V2V) transmissions or by cellular networks. Since the problem is proven to be NP-hard, a two-stage heuristic algorithm is designed. We carry out simulations to evaluate the performance of our data collection scheme and the results show that it performs better than traditional mechanisms.

RSU-Assisted Traffic-Aware Routing Based on Reinforcement Learning for Urban Vanets

Abstract: In urban vehicular ad hoc networks (VANETs), the high mobility of vehicles along street roads poses daunting challenges to routing protocols and has a great impact on network performance. In addition, the frequent network partition caused by an uneven distribution of vehicles in an urban environment further places higher requirements on the routing protocols in VANETs. More importantly, the high vehicle density during the traffic peak hours and a variety of natural obstacles, such as tall buildings, other vehicles and trees, greatly increase the difficulty of protocol design for high quality communications. Considering these issues, in this paper, we introduce a novel routing protocol for urban VANETs called RSU-assisted Q-learning-based Traffic-Aware Routing (QTAR). Combining the advantages of geographic routing with the static road map information, QTAR learns the road segment traffic information based on the Q-learning algorithm. In QTAR, a routing path consists of multiple dynamically selected high reliability connection road segments that enable packets to reach their destination effectively. For packet forwarding within a road segment, distributed V2V Q-learning (Q-learning occurs between vehicles) integrated with QGGF (Q-greedy geographical forwarding) is adopted to reduce delivery delay and the effect of fast vehicle movements on path sensitivity, while distributed R2R Q-learning (Q-learning occurs between RSU units) is designed for packet forwarding at each intermediate intersection. In the case of a local optimum occurring in QGGF, SCF (store-carry-forward) is used to reduce the possibility of packet loss. Detailed simulation experimental results demonstrate that QTAR outperforms the existing traffic-aware routing protocols, in terms of 7.9% and 16.38% higher average packet delivery ratios than those of reliable traffic-aware routing (RTAR) and greedy traffic-aware routing (GyTAR) in high vehicular density scenarios and 30.96% and 46.19% lower average end-to-end delays with respect to RTAR and GyTAR in low vehicular density scenarios, respectively.

Malicious node detection using heterogeneous cluster based secure routing protocol (HCBS) in wireless adhoc sensor networks

Abstract: In wireless, every device can moves anywhere without any infrastructure also the information can be maintained constantly for routing the traffic. The open issues of wireless Adhoc network the attacks which are chosen the forwarding attack that is dropped by malicious node to corrupt the network performance then the information integrity exposure. Aim of the problem that existing methods in Adhoc network for malicious node detection which cannot assure the traceability of the node as well as the fairness of node detection. In this paper, the proposed heterogeneous cluster based secure routing scheme provides trust based secure network for detection of attacks such as wormhole and black hole caused by malicious nodes presence in wireless Adhoc network. The simulation result shows that the proposed model is detect the malicious nodes effectively in wireless Adhoc networks. The malicious node detection efficiency can be achieved 96% also energy consumption also 10% better than existing method.

Reinforcement Learning Based PHY Authentication for VANETs

Abstract: Mobile edge computing in vehicular ad hoc networks (VANETs) suffers from rogue edge attacks due to the vehicle mobility and the network scale. In this paper, we present a physical authentication scheme to resist rogue edge attackers whose goal is to send spoofing signals to attack VANETs. This authentication scheme exploits the channel states of the shared ambient radio signals of the mobile device and its serving edge such as the onboard unit during the same moving trace and applies reinforcement learning to select the authentication modes and parameters. By applying transfer learning to save the learning time and applies deep learning to further improve the authentication performance, this scheme enables mobile devices in VANETs to optimize their authentication modes and parameters without being aware of the VANET channel model, the packet generation model, and the spoofing model. We provide the convergence bound such as the mobile device utility, evaluate the computational complexity of the physical authentication scheme, and verify the analysis results via simulations. Simulation and experimental results show that this scheme improves the authentication accuracy with reduced energy consumption against rogue edge attacks.

Toward Swarm Coordination: Topology-Aware Inter-UAV Routing Optimization

Abstract: Swarm unmanned aerial vehicles (UAVs) is an approach to the coordination of multiple UAVs as a system, which has huge advantages on mission capabilities, such as cooperative search, border surveillance, and situation awareness. For better swarm coordination, a robust inter-UAV network, especially in ad hoc mode, is needed. Due to the dynamic nature of UAV networks owing to mobility and topology change, adapting routing quickly to topology changes is one of the key components of UAV networks. Based on investigating the relationship between the swarm formation control and the network topology, we propose a proactive topology-aware scheme to track the network topology change. Through simulations on Qualnet and real-world experiments with five quadrotors, the results confirmed that the proposed scheme reduces the average delay and improves routing performance significantly.

Hybrid opportunistic and position-based routing protocol in vehicular ad hoc networks

Abstract: Vehicular ad hoc networks (VANETs) are kind of mobile ad hoc networks (MANETs) which are used to provide communications between mobile vehicles in urban and highway scenario. Due to special characteristics of VANETs such as dynamic topology, frequent disconnection, high vehicular speed and propagation model, designing an efficient routing scheme is one of the most important key issues. In this paper, we propose a hybrid opportunistic and position-based routing protocol in VANETs by considering parameters such as position of nodes, link quality and node density. The proposed method uses a greedy forwarding scheme, in which a sender vehicle chooses a neighbor node with the highest geographical progress to increase the least number of hops between source node and destination vehicle node. Based on opportunistic and position based strategy, the proposed scheme selects optimal candidate nodes and determines appropriate priority for transmitting data. Also, the proposed scheme determines and removes the expired nodes from the routing process. The simulation results in ns-2 indicate performance improvement in terms of packet delivery rate (PDR), throughput and end-to-end delay.

Privacy-Preserving Cloud Establishment and Data Dissemination Scheme for Vehicular Cloud

Abstract: Vehicular cloud (VC) extends cloud computing to vehicles participating in vehicular ad hoc networks, aiming to provide computing and storage services at low cost to vehicles, improve traffic efficiency and safety, ensure real-time services, etc. Due to the highly dynamic nature of VC, it is challenging to efficiently form a dynamic VC securely and anonymously or to securely deliver messages to the dynamic VC without potentially violating the privacy of cloud users. In this paper, we present a concrete secure and privacy-preserving communication scheme for VC establishment and data dissemination. Our scheme allows a group of vehicles that are geographically close to each other to form a VC securely, anonymously and dynamically. This allows vehicle resources to be integrated and shared securely. Once a VC is formed, any cloud user may deliver messages to be securely and anonymously processed in the VC.

Energy Efficient Optimal Routing for Communication in VANETs via Clustering Model

Abstract: Vehicular Ad Hoc Network (VANET) is a kind of extraordinary remote ad hoc network, which has high node portability and quick topology changes Clustering is a system for gathering nodes, making the network increasingly vigorous With no consciousness of nodes, at some point, it comes up short on energy which causes execution issues in network and topology changes At that point, it emerges a primary issue of energy in routing protocol, which endeavor node lifetime and link lifetime issues in the network To broaden the energy effectiveness of V2V communication, proposed a clustering based optimization technique This paper presents K-Medoid Clustering model to cluster the vehicle nodes and after that, energy efficient nodes are recognized for compelling communication With the expectation of accomplishing energy efficient communication, efficient nodes are recognized from each cluster by a metaheuristic algorithm, for example, Enhanced Dragonfly Algorithm (EDA) which optimizes the parameter as minimum consumption of energy in VANET The outcome exhibits that the V2V communication improves the energy efficiency in all vehicle nodes additionally it accomplishes less execution time contrasted with existing algorithms