Cognitive radio (CR) technology is envisaged to solve the problems in wireless networks resulting from the limited available spectrum and the inefficiency in the spectrum usage by exploiting the existing wireless spectrum opportunistically. CR networks, equipped with the intrinsic capabilities of the cognitive radio, will provide an ultimate spectrum-aware communication paradigm in wireless communications. CR networks, however, impose unique challenges due to the high fluctuation in the available spectrum as well as diverse quality-of-service (QoS) requirements. Specifically, in cognitive radio ad hoc networks (CRAHNs), the distributed multi-hop architecture, the dynamic network topology, and the time and location varying spectrum availability are some of the key distinguishing factors. In this paper, intrinsic properties and current research challenges of the CRAHNs are presented. First, novel spectrum management functionalities such as spectrum sensing, spectrum sharing, and spectrum decision, and spectrum mobility are introduced from the viewpoint of a network requiring distributed coordination. A particular emphasis is given to distributed coordination between CR users through the establishment of a common control channel. Moreover, the influence of these functions on the performance of the upper layer protocols, such as the network layer, and transport layer protocols are investigated and open research issues in these areas are also outlined. Finally, a new direction called the commons model is explained, where CRAHN users may independently regulate their own operation based on pre-decided spectrum etiquette.

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CRAHNs: Cognitive radio ad hoc networks

Providing various wireless connectivities for vehicles enables the communication between vehicles and their internal and external environments. Such a connected vehicle solution is expected to be the next frontier for automotive revolution and the key to the evolution to next generation intelligent transportation systems (ITSs). Moreover, connected vehicles are also the building blocks of emerging Internet of Vehicles (IoV). Extensive research activities and numerous industrial initiatives have paved the way for the coming era of connected vehicles. In this paper, we focus on wireless technologies and potential challenges to provide vehicle-to-x connectivity. In particular, we discuss the challenges and review the state-of-the-art wireless solutions for vehicle-to-sensor, vehicle-to-vehicle, vehicle-to-Internet, and vehicle-to-road infrastructure connectivities. We also identify future research issues for building connected vehicles.

http://bbcr.uwaterloo.ca/~xshen/paper/2015/cvsac.pdf

Connected Vehicles: Solutions and Challenges

A vehicular ad hoc network (VANET) is a mobile ad hoc network in which network nodes are vehicles—most commonly road vehicles. VANETs present a unique range of challenges and opportunities for routing protocols due to the semi-organized nature of vehicular movements subject to the constraints of road geometry and rules, and the obstacles which limit physical connectivity in urban environments. In particular, the problems of routing protocol reliability and scalability across large urban VANETs are currently the subject of intense research. Clustering can be used to improve routing scalability and reliability in VANETs, as it results in the distributed formation of hierarchical network structures by grouping vehicles together based on correlated spatial distribution and relative velocity. In addition to the benefits to routing, these groups can serve as the foundation for accident or congestion detection, information dissemination and entertainment applications. This paper explores the design choices made in the development of clustering algorithms targeted at VANETs. It presents a taxonomy of the techniques applied to solve the problems of cluster head election, cluster affiliation, and cluster management, and identifies new directions and recent trends in the design of these algorithms. Additionally, methodologies for validating clustering performance are reviewed, and a key shortcoming—the lack of realistic vehicular channel modeling—is identified. The importance of a rigorous and standardized performance evaluation regime utilizing realistic vehicular channel models is demonstrated.

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A Comparative Survey of VANET Clustering Techniques

Machine-to-machine (M2M) communications enables networked devices to exchange information among each other as well as with business application servers and therefore creates what is known as the Internet-of-Things (IoT). The research community has a consensus for the need of a standardized protocol stack for M2M communications. On the other hand, cognitive radio technology is very promising for M2M communications due to a number of factors. It is expected that cognitive M2M communications will be indispensable in order to realize the vision of IoT. However cognitive M2M communications requires a cognitive radio-enabled protocol stack in addition to the fundamental requirements of energy efficiency, reliability, and Internet connectivity. The main objective of this paper is to provide the state of the art in cognitive M2M communications from a protocol stack perspective. This paper covers the emerging standardization efforts and the latest developments on protocols for cognitive M2M networks. In addition, this paper also presents the authors’ recent work in this area, which includes a centralized cognitive medium access control (MAC) protocol, a distributed cognitive MAC protocol, and a specially designed routing protocol for cognitive M2M networks. These protocols explicitly account for the peculiarities of cognitive radio environments. Performance evaluation demonstrates that the proposed protocols not only ensure protection to the primary users (PUs) but also fulfil the utility requirements of the secondary M2M networks.

Cognitive Machine-to-Machine Communications for Internet-of-Things: A Protocol Stack Perspective

Driver drowsiness and distraction are two main reasons for traffic accidents and the related financial losses. Therefore, researchers have been working for more than a decade on designing driver inattention monitoring systems. As a result, several detection techniques for the detection of both drowsiness and distraction have been proposed in the literature. Some of these techniques were successfully adopted and implemented by the leading car companies. This paper discusses and provides a comprehensive insight into the well-established techniques for driver inattention monitoring and introduces the use of most recent and futuristic solutions exploiting mobile technologies such as smartphones and wearable devices. Then, a proposal is made for the active of such systems into car-to-car communication to support vehicular ad hoc network's (VANET's) primary aim of safe driving. We call this approach the dissemination of driver behavior via C2C communication. Throughout this paper, the most remarkable studies of the last five years were examined thoroughly in order to reveal the recent driver monitoring techniques and demonstrate the basic pros and cons. In addition, the studies were categorized into two groups: driver drowsiness and distraction. Then, research on the driver drowsiness was further divided into two main subgroups based on the exploitation of either visual features or nonvisual features. A comprehensive compilation, including used features, classification methods, accuracy rates, system parameters, and environmental details, was represented as tables to highlight the (dis)advantages and/or limitations of the aforementioned categories. A similar approach was also taken for the methods used for the detection of driver distraction.

Driver Behavior Analysis for Safe Driving: A Survey

In this paper, we illustrate the design of a cross-layered MAC and clustering solution for supporting the fast propagation of broadcast messages in a vehicular ad hoc network (VANET). A distributed dynamic clustering algorithm is proposed to create a dynamic virtual backbone in the vehicular network. The vehicle-members of the backbone are responsible for implementing an efficient messages propagation. The backbone creation and maintenance are proactively performed aiming to balance the stability of backbone connections as well as the cost/efficiency trade-off and the hops-reduction when forwarding broadcast messages. A fast multi-hop MAC forwarding mechanism is defined to exploit the role of backbone vehicles, under a cross-layered approach. Simulation results show the effectiveness of the mutual support of proactive clustering and MAC protocols for efficient dissemination of broadcast messages in VANETs.

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A Cross Layered MAC and Clustering Scheme for Efficient Broadcast in VANETs

Existing research in transport protocols for wireless ad-hoc networks has focused on reliable end-to-end packet delivery under uncertain channel conditions, route failures due to node mobility and link congestion. In a cognitive radio (CR) environment, there are several key challenges that must be addressed apart from the above concerns. The intermittent spectrum sensing undertaken by the CR users, the activity of the licensed users of the spectrum, large-scale bandwidth variation based on spectrum availability, and the channel switching process need to be considered in the transport protocol design. In this paper, a window-based Transport Protocol for CR Ad-Hoc Networks, TP-CRAHN, is proposed that distinguishes each of these events by a combination of explicit feedback from the intermediate nodes and the destination. This is achieved by adapting the classical TCP rate control algorithm running at the source to closely interact with the physical layer channel information, the link layer functions of spectrum sensing and buffer management, and a predictive mobility framework that is developed at the network layer. To the best of our knowledge, this is the first work on the transport layer to specifically address the concerns of the CR ad-hoc networks and our approach is thoroughly validated by simulation experiments.

TP-CRAHN: a Transport Protocol for Cognitive Radio Ad-Hoc Networks

This article discusses the current state-of-the-art research on CRV networks. While it is envisaged that this technology will help to realize high-bandwidth multimedia applications, the research on CRV networks is still at a preliminary stage. The spectrum management functions proposed for general-purpose CR networks will need to be revisited by taking into account the characteristics of the vehicular environment, such as the role of the mobility, and the cooperation possibilities. The lack of realistic test beds and of simulation tools is a serious limitation, and effort needs to be invested in building such evaluation platforms that can provide realistic insights on the performance of CRV networks before the potential for this technology can be fully realized.

Smart Radios for Smart Vehicles: Cognitive Vehicular Networks

Cognitive Radio (CR) networks allow users to opportunistically transmit in the licensed spectrum bands, as long as the performance of the Primary Users (PUs) of the band is not degraded. Consequently, variation in spectrum availability with time and periodic spectrum sensing undertaken by the CR users have a pronounced effect on the higher layer protocol performance, such as at the transport layer. This paper investigates the limitations of classical TCP newReno in a CR ad hoc network environment, and proposes TCP CRAHN, a window-based TCP-friendly protocol. Our approach incorporates spectrum awareness by a combination of explicit feedback from the intermediate nodes and the destination. This is achieved by adapting the classical TCP rate control algorithm running at the source to closely interact with the physical layer channel information, the link layer functions of spectrum sensing and buffer management, and a predictive mobility framework that is developed at the network layer. An analysis of the expected throughput in TCP CRAHN is provided, and simulation results reveal significant improvements by using our approach. To the best of our knowledge, our approach takes the first steps toward the design of a transport layer for CR ad hoc networks.

M. Di Felice

Papers

A Cross Layered MAC and Clustering Scheme for Efficient Broadcast in VANETs

TP-CRAHN: a Transport Protocol for Cognitive Radio Ad-Hoc Networks

Smart Radios for Smart Vehicles: Cognitive Vehicular Networks

TCP CRAHN: A Transport Control Protocol for Cognitive Radio Ad Hoc Networks

Reinforcement Learning-Based Spectrum Management for Cognitive Radio Networks: A Literature Review and Case Study