Search

As an application of “smart transport” for Internet of Things, Internet of Vehicle (IoV) has emerged as a new research field based on vehicular ad hoc networks (VANETs). With the development of smart vehicles and the integration of sensors, applications of traffic management and road safety in large-scale IoV systems have drawn great attentions. By sensing events occurred on roads, vehicles can broadcast messages to inform others about traffic jams or accidents. However, the store-carry-and-forward transmission pattern may cause a large transmission delay, making the implementation of large-scale traffic management difficult. In this paper, we put forward a feasible solution to minimize the response time for traffic management service, by enabling real-time content dissemination based on heterogeneous network access in IoV systems. We first design a crowdsensing-based system model for large-scale IoV systems. Then, a cluster-based optimization framework is investigated to provide timely responses for traffic management. Specifically, we estimate the message transmission delay by stochastic theory, which can provide a guideline for the next-hop relay selection in our delay-sensitive routing scheme. Furthermore, network performances are evaluated based on two city-road maps, and performance metrics, containing average delivery delay, average delivery ratio, average communication cost, and access ratio, demonstrate the superiority of our system. Finally, we conclude our work and discuss the further work. [ABSTRACT FROM AUTHOR]

The proliferation of IoTs beside the emergence of various cloud services push the horizon of edge computing. By offering cloud capabilities at the network edge closer to mobile devices, edge computing is a promising paradigm to resolve several vital challenges in IoTs, such as bandwidth saturation, energy constraints, low latency transmission, and data security and privacy. To provide a comprehensive understanding of edge computing supported by the integration of IoTs and cloud computing, that is, CoTs, this article first discusses some distinct research directions in CoTs with respect to edge computing. Given the significance of energy efficiency and sustainability of edge deployment in CoTs, we put forward a green and sustainable virtual network embedding framework for cooperative edge computing in wireless-optical broadband access networks. Specifically, we leverage a reliability function to confirm the number of backup edge devices, and embed virtual networks onto the suitable edge devices in CoTs. Finally, several research challenges and open issues are discussed. [ABSTRACT FROM AUTHOR]

As an emerging platform based on ITS, SIoV is promising for applications of traffic management and road safety in smart cities. However, the endto- end delay is large in store-carry-and-forwardbased vehicular networks, which has become the main obstacle for the implementation of large-scale SIoV. With the extensive applications of mobile devices, crowdsensing is promising to enable realtime content dissemination in a city-wide traffic management system. This article first provides an overview of several promising research areas for traffic management in SIoV. Given the significance of traffic management in urban areas, we investigate a crowdsensing-based framework to provide timely response for traffic management in heterogeneous SIoV. The participant vehicles based on D2D communications integrate trajectory and topology information to dynamically regulate their social behaviors according to network conditions. A real-world taxi trajectory analysis-based performance evaluation is provided to demonstrate the effectiveness of the designed framework. Furthermore, we discuss several future [ABSTRACT FROM AUTHOR]