The feasibility of obstacle awareness forwarding scheme in a visible light communication vehicular network

A vehicular-to-vehicular (V2V) communication is a part of a vehicular ad-hoc network (VANET) that emerges recently due to the heavy traffic environment. V2V is a frequently changing network since it implements vehicles as mobile nodes. The challenges in implementing V2V are the relatively short duration of possible communication and the uneven city environment caused by high rise buildings or other objects that distract the signal transmission. The limited transmitting duration between vehicles requires efficient coordination and communication. This work focuses on the utility of visible light communication in vehicular network (VLC-VN) in data transmitting and the obstacle awareness in the forwarding scheme based on our knowledge in previous researches. The result of evaluating the feasibility of VLC-VN forwarding in a freeway environment the transmission delay is lower than 1 second in 500 byte data transmission, however it reaches to only about 4% in throughput as a drawback

RESP: Relay suitability-based routing protocol for video streaming in vehicular Ad Hoc Networks

Video streaming in Vehicular Ad Hoc Networks (VANETs) is a fundamental requirement for a roadside emergency and smart video surveillance services. However, vehicles moving at a high speed usually create unstable wireless links that drop video frames qualities. In a high-density network, network collision between vehicles is another obstacle in improving the scalability of unicast routing protocols. In this paper, the RElay Suitability-based Routing Protocol (RESP) which makes a routing decision based on the link stability measurement was proposed for an uninterrupted video streaming. The RESP estimates the geographic advancement and link stability of a vehicle towards its destination only in the small region. To ensure the reliability while extending the scalability of routing, the relay suitability metric integrates the packet delay, collision dropping, link stability, and the Expected Transmission Count (ETX) in the weighted division algorithm, and selects a high-quality forwarding node for video streaming. The experimental results demonstrated the proposed RESP outperformed the link Lifetime-aware Beacon-less Routing Protocol (LBRP) and other traditional geographical streaming protocols in providing a high packet delivery ratio and packet delay with various network densities, and proved the scalability support of RESP for video streaming

Cooperative inter-vehicle communication protocol with low cost differential GPS

This paper describes a cooperative MANET protocol dedicated to intelligent transport systems, named CIVIC (Communication Inter Véhicule Intelligente et Coopérative). The CIVIC protocol is an auto-configuration inter-vehicle communication protocol, which supports adhoc and infrastructure networks, contains reactive and proactive routing components, and adapts different wireless standards. It is a context-aware protocol reacting to vehicle status, road traffic, and geographic environment. It supports location-based communication. To improve the accuracy of GPS, it integrates a localization solution called LCD-GPS (Low Cost Differential GPS). It has been implemented and experimented on the LiveNode sensor developed by our lab. At the end of this paper, an application project MobiPlus is introduced

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Towards Cyber Security for Low-Carbon Transportation: Overview, Challenges and Future Directions

In recent years, low-carbon transportation has become an indispensable part as sustainable development strategies of various countries, and plays a very important responsibility in promoting low-carbon cities. However, the security of low-carbon transportation has been threatened from various ways. For example, denial of service attacks pose a great threat to the electric vehicles and vehicle-to-grid networks. To minimize these threats, several methods have been proposed to defense against them. Yet, these methods are only for certain types of scenarios or attacks. Therefore, this review addresses security aspect from holistic view, provides the overview, challenges and future directions of cyber security technologies in low-carbon transportation. Firstly, based on the concept and importance of low-carbon transportation, this review positions the low-carbon transportation services. Then, with the perspective of network architecture and communication mode, this review classifies its typical attack risks. The corresponding defense technologies and relevant security suggestions are further reviewed from perspective of data security, network management security and network application security. Finally, in view of the long term development of low-carbon transportation, future research directions have been concerned.Comment: 34 pages, 6 figures, accepted by journal Renewable and Sustainable Energy Review

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Situational Awareness Enhancement for Connected and Automated Vehicle Systems

Recent developments in the area of Connected and Automated Vehicles (CAVs) have boosted the interest in Intelligent Transportation Systems (ITSs). While ITS is intended to resolve and mitigate serious traffic issues such as passenger and pedestrian fatalities, accidents, and traffic congestion; these goals are only achievable by vehicles that are fully aware of their situation and surroundings in real-time. Therefore, connected and automated vehicle systems heavily rely on communication technologies to create a real-time map of their surrounding environment and extend their range of situational awareness. In this dissertation, we propose novel approaches to enhance situational awareness, its applications, and effective sharing of information among vehicles.;The communication technology for CAVs is known as vehicle-to-everything (V2x) communication, in which vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) have been targeted for the first round of deployment based on dedicated short-range communication (DSRC) devices for vehicles and road-side transportation infrastructures. Wireless communication among these entities creates self-organizing networks, known as Vehicular Ad-hoc Networks (VANETs). Due to the mobile, rapidly changing, and intrinsically error-prone nature of VANETs, traditional network architectures are generally unsatisfactory to address VANETs fundamental performance requirements. Therefore, we first investigate imperfections of the vehicular communication channel and propose a new modeling scheme for large-scale and small-scale components of the communication channel in dense vehicular networks. Subsequently, we introduce an innovative method for a joint modeling of the situational awareness and networking components of CAVs in a single framework. Based on these two models, we propose a novel network-aware broadcast protocol for fast broadcasting of information over multiple hops to extend the range of situational awareness. Afterward, motivated by the most common and injury-prone pedestrian crash scenarios, we extend our work by proposing an end-to-end Vehicle-to-Pedestrian (V2P) framework to provide situational awareness and hazard detection for vulnerable road users. Finally, as humans are the most spontaneous and influential entity for transportation systems, we design a learning-based driver behavior model and integrate it into our situational awareness component. Consequently, higher accuracy of situational awareness and overall system performance are achieved by exchange of more useful information