Towards video streaming in IoT environments: vehicular communication perspective

Multimedia oriented Internet of Things (IoT) enables pervasive and real-time communication of video, audio and image data among devices in an immediate surroundings. Today's vehicles have the capability of supporting real time multimedia acquisition. Vehicles with high illuminating infrared cameras and customized sensors can communicate with other on-road devices using dedicated short-range communication (DSRC) and 5G enabled communication technologies. Real time incidence of both urban and highway vehicular traffic environment can be captured and transmitted using vehicle-to-vehicle and vehicle-to-infrastructure communication modes. Video streaming in vehicular IoT (VSV-IoT) environments is in growing stage with several challenges that need to be addressed ranging from limited resources in IoT devices, intermittent connection in vehicular networks, heterogeneous devices, dynamism and scalability in video encoding, bandwidth underutilization in video delivery, and attaining application-precise quality of service in video streaming. In this context, this paper presents a comprehensive review on video streaming in IoT environments focusing on vehicular communication perspective. Specifically, significance of video streaming in vehicular IoT environments is highlighted focusing on integration of vehicular communication with 5G enabled IoT technologies, and smart city oriented application areas for VSV-IoT. A taxonomy is presented for the classification of related literature on video streaming in vehicular network environments. Following the taxonomy, critical review of literature is performed focusing on major functional model, strengths and weaknesses. Metrics for video streaming in vehicular IoT environments are derived and comparatively analyzed in terms of their usage and evaluation capabilities. Open research challenges in VSV-IoT are identified as future directions of research in the area. The survey would benefit both IoT and vehicle industry practitioners and researchers, in terms of augmenting understanding of vehicular video streaming and its IoT related trends and issues

Towards new methods for mobility data gathering: content, sources, incentives

Over the past decade, huge amounts of work has been done in mobile and opportunistic networking research. Unfortunately, much of this has had little impact as the results have not been applicable to reality, due to incorrect assumptions and models used in the design and evaluation of the systems. In this paper, we outline some of the problems of the assumptions of early research in the field, and provide a survey of some initial work that has started to take place to alleviate this through more realistic modelling and measurements of real systems. We do note that there is still much work to be done in this area, and then go on to identify some important properties of the network that must be studied further. We identify the types of data that are important to measure, and also give some guidelines on finding existing and potentially new sources for such data and incentivizing the holders of the data to share it

Priority-Based Content Delivery in the Internet of Vehicles through Named Data Networking

Named Data Networking (NDN) has been recently proposed as a prominent solution for content delivery in the Internet of Vehicles (IoV), where cars equipped with a variety of wireless communication technologies exchange information aimed to support safety, traffic efficiency, monitoring and infotainment applications. The main NDN tenets, i.e., name-based communication and in-network caching, perfectly fit the demands of time- and spatially-relevant content requested by vehicles regardless of their provenance. However, existing vehicular NDN solutions have not been targeted to wisely ensure prioritized traffic treatment based on the specific needs of heterogeneous IoV content types. In this work, we propose a holistic NDN solution that, according to the demands of data traffic codified in NDN content names, dynamically shapes the NDN forwarding decisions to ensure the appropriate prioritization. Specifically, our proposal first selects the outgoing interface(s) (i.e., 802.11, LTE) for NDN packets and then properly tunes the timing of the actual transmissions. Simulation results show that the proposed enhancements succeed in achieving differentiated traffic treatment, while keeping traffic load under control

Routing and Applications of Vehicular Named Data Networking

Vehicular Ad hoc NETwork (VANET) allows vehicles to exchange important informationamong themselves and has become a critical component for enabling smart transportation.In VANET, vehicles are more interested in content itself than from which vehicle the contentis originated. Named Data Networking (NDN) is an Internet architecture that concentrateson what the content is rather than where the content is located. We adopt NDN as theunderlying communication paradigm for VANET because it can better address a plethora ofproblems in VANET, such as frequent disconnections and fast mobility of vehicles. However,vehicular named data networking faces the problem of how to efficiently route interestpackets and data packets. To address the problem, we propose a new geographic routing strategy of applying NDNin vehicular networks with Delay Tolerant Networking (DTN) support, called GeoDTN-NDN. We designed a hybrid routing mechanism for solving the flooding issue of forwardinginterest packets and the disruption problem of delivering data packets. To avoid disruptionscaused by routing packets over less-traveled roads, we develop a new progressive segmentrouting approach that takes into consideration how vehicles are distributed among differentroads, with the goal of favoring well-traveled roads. A novel criterion for determiningprogress of routing is designed to guarantee that the destination will be reached no matterwhether a temporary loop may be formed in the path. We also investigate applications of vehicular named data networking. We categorizethese applications into four types and design an NDN naming scheme for them. We proposea fog-computing based architecture to support the smart parking application, which enablesa driver to find a parking lot with available parking space and make reservation for futureparking need. Finally we describe several future research directions for vehicular nameddata networking

ReFIoV: a novel reputation framework for information-centric vehicular applications

In this article, a novel reputation framework for information-centric vehicular applications leveraging on machine learning and the artificial immune system (AIS), also known as ReFIoV, is proposed. Specifically, Bayesian learning and classification allow each node to learn as newly observed data of the behavior of other nodes become available and hence classify these nodes, meanwhile, the K-Means clustering algorithm allows to integrate recommendations from other nodes even if they behave in an unpredictable manner. AIS is used to enhance misbehavior detection. The proposed ReFIoV can be implemented in a distributed manner as each node decides with whom to interact. It provides incentives for nodes to cache and forward others’ mobile data as well as achieves robustness against false accusations and praise. The performance evaluation shows that ReFIoV outperforms state-of-the-art reputation systems for the metrics considered. That is, it presents a very low number of misbehaving nodes incorrectly classified in comparison to another reputation scheme. The proposed AIS mechanism presents a low overhead. The incorporation of recommendations enabled the framework to reduce even further detection time

Service Provisioning in Edge-Cloud Continuum Emerging Applications for Mobile Devices

Disruptive applications for mobile devices can be enhanced by Edge computing facilities. In this context, Edge Computing (EC) is a proposed architecture to meet the mobility requirements imposed by these applications in a wide range of domains, such as the Internet of Things, Immersive Media, and Connected and Autonomous Vehicles. EC architecture aims to introduce computing capabilities in the path between the user and the Cloud to execute tasks closer to where they are consumed, thus mitigating issues related to latency, context awareness, and mobility support. In this survey, we describe which are the leading technologies to support the deployment of EC infrastructure. Thereafter, we discuss the applications that can take advantage of EC and how they were proposed in the literature. Finally, after examining enabling technologies and related applications, we identify some open challenges to fully achieve the potential of EC, and also research opportunities on upcoming paradigms for service provisioning. This survey is a guide to comprehend the recent advances on the provisioning of mobile applications, as well as foresee the expected next stages of evolution for these applications

Cloud Computing in VANETs: Architecture, Taxonomy, and Challenges

Cloud Computing in VANETs (CC-V) has been investigated into two major themes of research including Vehicular Cloud Computing (VCC) and Vehicle using Cloud (VuC). VCC is the realization of autonomous cloud among vehicles to share their abundant resources. VuC is the efficient usage of conventional cloud by on-road vehicles via a reliable Internet connection. Recently, number of advancements have been made to address the issues and challenges in VCC and VuC. This paper qualitatively reviews CC-V with the emphasis on layered architecture, network component, taxonomy, and future challenges. Specifically, a four-layered architecture for CC-V is proposed including perception, co-ordination, artificial intelligence and smart application layers. Three network component of CC-V namely, vehicle, connection and computation are explored with their cooperative roles. A taxonomy for CC-V is presented considering major themes of research in the area including design of architecture, data dissemination, security, and applications. Related literature on each theme are critically investigated with comparative assessment of recent advances. Finally, some open research challenges are identified as future issues. The challenges are the outcome of the critical and qualitative assessment of literature on CC-V