Secure and robust multi-constrained QoS aware routing algorithm for VANETs

Secure QoS routing algorithms are a fundamental part of wireless networks that aim to provide services with QoS and security guarantees. In Vehicular Ad hoc Networks (VANETs), vehicles perform routing functions, and at the same time act as end-systems thus routing control messages are transmitted unprotected over wireless channels. The QoS of the entire network could be degraded by an attack on the routing process, and manipulation of the routing control messages. In this paper, we propose a novel secure and reliable multi-constrained QoS aware routing algorithm for VANETs. We employ the Ant Colony Optimisation (ACO) technique to compute feasible routes in VANETs subject to multiple QoS constraints determined by the data traffic type. Moreover, we extend the VANET-oriented Evolving Graph (VoEG) model to perform plausibility checks on the exchanged routing control messages among vehicles. Simulation results show that the QoS can be guaranteed while applying security mechanisms to ensure a reliable and robust routing service

Benets of tight coupled architectures for the integration of GNSS receiver and Vanet transceiver

Vehicular adhoc networks (VANETs) are one emerging type of networks that will enable a broad range of applications such as public safety, traffic management, traveler information support and entertain ment. Whether wireless access may be asynchronous or synchronous (respectively as in the upcoming IEEE 8021.11p standard or in some alternative emerging solutions), a synchronization among nodes is required. Moreover, the information on position is needed to let vehicular services work and to correctly forward the messages. As a result, timing and positioning are a strong prerequisite of VANETs. Also the diffusion of enhanced GNSS Navigators paves the way to the integration between GNSS receivers and VANET transceiv ers. This position paper presents an analysis on potential benefits coming from a tightcoupling between the two: the dissertation is meant to show to what extent Intelligent Transportation System (ITS) services could benefit from the proposed architectur

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

Reconfigurable Security: Edge Computing-based Framework for IoT

In various scenarios, achieving security between IoT devices is challenging since the devices may have different dedicated communication standards, resource constraints as well as various applications. In this article, we first provide requirements and existing solutions for IoT security. We then introduce a new reconfigurable security framework based on edge computing, which utilizes a near-user edge device, i.e., security agent, to simplify key management and offload the computational costs of security algorithms at IoT devices. This framework is designed to overcome the challenges including high computation costs, low flexibility in key management, and low compatibility in deploying new security algorithms in IoT, especially when adopting advanced cryptographic primitives. We also provide the design principles of the reconfigurable security framework, the exemplary security protocols for anonymous authentication and secure data access control, and the performance analysis in terms of feasibility and usability. The reconfigurable security framework paves a new way to strength IoT security by edge computing.Comment: under submission to possible journal publication

Vehicular Fog Computing Enabled Real-time Collision Warning via Trajectory Calibration

Vehicular fog computing (VFC) has been envisioned as a promising paradigm for enabling a variety of emerging intelligent transportation systems (ITS). However, due to inevitable as well as non-negligible issues in wireless communication, including transmission latency and packet loss, it is still challenging in implementing safety-critical applications, such as real-time collision warning in vehicular networks. In this paper, we present a vehicular fog computing architecture, aiming at supporting effective and real-time collision warning by offloading computation and communication overheads to distributed fog nodes. With the system architecture, we further propose a trajectory calibration based collision warning (TCCW) algorithm along with tailored communication protocols. Specifically, an application-layer vehicular-to-infrastructure (V2I) communication delay is fitted by the Stable distribution with real-world field testing data. Then, a packet loss detection mechanism is designed. Finally, TCCW calibrates real-time vehicle trajectories based on received vehicle status including GPS coordinates, velocity, acceleration, heading direction, as well as the estimation of communication delay and the detection of packet loss. For performance evaluation, we build the simulation model and implement conventional solutions including cloud-based warning and fog-based warning without calibration for comparison. Real-vehicle trajectories are extracted as the input, and the simulation results demonstrate that the effectiveness of TCCW in terms of the highest precision and recall in a wide range of scenarios

Internet of Vehicles: Motivation, Layered Architecture, Network Model, Challenges, and Future Aspects

© 2013 IEEE. Internet of Things is smartly changing various existing research areas into new themes, including smart health, smart home, smart industry, and smart transport. Relying on the basis of 'smart transport,' Internet of Vehicles (IoV) is evolving as a new theme of research and development from vehicular ad hoc networks (VANETs). This paper presents a comprehensive framework of IoV with emphasis on layered architecture, protocol stack, network model, challenges, and future aspects. Specifically, following the background on the evolution of VANETs and motivation on IoV an overview of IoV is presented as the heterogeneous vehicular networks. The IoV includes five types of vehicular communications, namely, vehicle-to-vehicle, vehicle-to-roadside, vehicle-to-infrastructure of cellular networks, vehicle-to-personal devices, and vehicle-to-sensors. A five layered architecture of IoV is proposed considering functionalities and representations of each layer. A protocol stack for the layered architecture is structured considering management, operational, and security planes. A network model of IoV is proposed based on the three network elements, including cloud, connection, and client. The benefits of the design and development of IoV are highlighted by performing a qualitative comparison between IoV and VANETs. Finally, the challenges ahead for realizing IoV are discussed and future aspects of IoV are envisioned