The Internet of Things vision: Key features, applications and open issues

Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The full potential of ADSs cannot be realized unless the robustness of state-of-the-art is improved further. This paper discusses unsolved problems and surveys the technical aspect of automated driving. Studies regarding present challenges, high-level system architectures, emerging methodologies and core functions including localization, mapping, perception, planning, and human machine interfaces, were thoroughly reviewed. Furthermore, many state-of-the-art algorithms were implemented and compared on our own platform in a real-world driving setting. The paper concludes with an overview of available datasets and tools for ADS development.

A Survey of Autonomous Driving: Common Practices and Emerging Technologies

All one needs to know about fog computing and related edge computing paradigms: A complete survey

A wide variety of applications for road safety and traffic efficiency are intended to answer the urgent call for smarter, greener, and safer mobility. Although IEEE 802.11p is considered the de facto standard for on-the-road communications, stakeholders have recently started to investigate the usability of LTE to support vehicular applications. In this article, related work and running standardization activities are scanned and critically discussed; strengths and weaknesses of LTE as an enabling technology for vehicular communications are analyzed; and open issues and critical design choices are highlighted to serve as guidelines for future research in this hot topic.

LTE for vehicular networking: a survey

The developments of connected vehicles are heavily influenced by information and communications technologies, which have fueled a plethora of innovations in various areas, including networking, caching, and computing. Nevertheless, these important enabling technologies have traditionally been studied separately in the existing works on vehicular networks. In this paper, we propose an integrated framework that can enable dynamic orchestration of networking, caching, and computing resources to improve the performance of next generation vehicular networks. We formulate the resource allocation strategy in this framework as a joint optimization problem, where the gains of not only networking but also caching and computing are taken into consideration in the proposed framework. The complexity of the system is very high when we jointly consider these three technologies. Therefore, we propose a novel deep reinforcement learning approach in this paper. Simulation results with different system parameters are presented to show the effectiveness of the proposed scheme.

Integrated Networking, Caching, and Computing for Connected Vehicles: A Deep Reinforcement Learning Approach

In view of evolving the Internet infrastructure, ICN is promoting a communication model that is fundamentally different from the traditional IP address-centric model. The ICN approach consists of the retrieval of content by (unique) names, regardless of origin server location (i.e., IP address), application, and distribution channel, thus enabling in-network caching/replication and content-based security. The expected benefits in terms of improved data dissemination efficiency and robustness in challenging communication scenarios indicate the high potential of ICN as an innovative networking paradigm in the IoT domain. IoT is a challenging environment, mainly due to the high number of heterogeneous and potentially constrained networked devices, and unique and heavy traffic patterns. The application of ICN principles in such a context opens new opportunities, while requiring careful design choices. This article critically discusses potential ways toward this goal by surveying the current literature after presenting several possible motivations for the introduction of ICN in the context of IoT. Major challenges and opportunities are also highlighted, serving as guidelines for progress beyond the state of the art in this timely and increasingly relevant topic.

Information-centric networking for the internet of things: challenges and opportunities

In the connected vehicle ecosystem, a high volume of information-rich and safety-critical data will be exchanged by roadside units and onboard transceivers to improve the driving and traveling experience. However, poor-quality wireless links and the mobility of vehicles highly challenge data delivery. The IP address-centric model of the current Internet barely works in such extremely dynamic environments and poorly matches the localized nature of the majority of vehicular communications, which typically target specific road areas (e.g., in the proximity of a hazard or a point of interest) regardless of the identity/address of a single vehicle passing by. Therefore, a paradigm shift is advocated from traditional IP-based networking toward the groundbreaking information- centric networking. In this article, we scrutinize the applicability of this paradigm in vehicular environments by reviewing its core functionalities and the related work. The analysis shows that, thanks to features like named content retrieval, innate multicast support, and in-network data caching, information-centric networking is positioned to meet the challenging demands of vehicular networks and their evolution. Interoperability with the standard architectures for vehicular applications along with synergies with emerging computing and networking paradigms are debated as future research perspectives.

Information-centric networking for connected vehicles: a survey and future perspectives

IEEE 80211p/WAVE (Wireless Access for Vehicular Environment) is the emerging standard to enable wireless access in the vehicular environment Most of the research contributions in this area has focused on safety-related applications, while comfort and information/entertainment applications (such as on board Internet access, point-of-interest notification, e-map download) have been considered only recently Notwithstanding, the user interest in this kind of applications is expected to become a big market driver in a near future In this paper, an extension to IEEE 80211p is proposed that is compliant with the multi-channel operation of the WAVE architecture and targets at the support of non-safety applications, while preserving the delivery of safety services The proposed W-HCF (WAVE-based Hybrid Coordination Function) protocol leverages controlled access capabilities on top of the basic contention-based access of the IEEE 80211p; it exploits vehicles' position information and coordination among WAVE providers in order to improve performances of delay-constrained and loss-sensitive non-safety applications

Enhancing IEEE 802.11p/WAVE to provide infotainment applications in VANETs

The Named Data Networking (NDN) project is emerging as one of the most promising information-centric future Internet architectures. Besides NDN recognized potential as a content retrieval solution in wired and wireless domains, its innovative concepts, such as named content, name-based routing and in-network caching, particularly suit the requirements of Internet of Things (IoT) interconnecting billions of heterogeneous objects. IoT highly differs from today's Internet due to resource-constrained devices, massive volumes of small exchanged data, and traffic type diversity. The study in this paper addresses the design of a high-level NDN architecture, whose main components are overhauled to specifically meet the IoT challenges.

Marica Amadeo

Papers

Information-centric networking for the internet of things: challenges and opportunities

Information-centric networking for connected vehicles: a survey and future perspectives

Enhancing IEEE 802.11p/WAVE to provide infotainment applications in VANETs

Named data networking for IoT: An architectural perspective

Forwarding strategies in named data wireless ad hoc networks