Affiliation:
1. State Key Laboratory of Integrated Services Networks, Xidian University, China
2. School of Information and Safety Engineering, Zhongnan University of Economics and Law, China
Abstract
As a key use case of Industry 4.0 and the Smart City, the Internet of Vehicles (IoV) provides an efficient way for city managers to regulate the traffic flow, improve the commuting performance, reduce the transportation facility cost, alleviate the traffic jam, and so on. In fact, the significant development of Internet of Vehicles has boosted the emergence of a variety of Industry 4.0 applications, e.g., smart logistics, intelligent transforation, and autonomous driving. The prerequisite of deploying these applications is the design of efficient data dissemination schemes by which the interactive information could be effectively exchanged. However, in Internet of Vehicles, an efficient data scheme should adapt to the high node movement and frequent network changing. To achieve the objective, the ability to predict short-term traffic is crucial for making optimal policy in advance. In this article, we propose a novel data dissemination scheme by exploring short-term traffic prediction for Industry 4.0 applications enabled in Internet of Vehicles. First, we present a three-tier network architecture with the aim to simply network management and reduce communication overheads. To capture dynamic network changing, a deep learning network is employed by the controller in this architecture to predict short-term traffic with the availability of enormous traffic data. Based on the traffic prediction, each road segment can be assigned a weight through the built two-dimensional delay model, enabling the controller to make routing decisions in advance. With the global weight information, the controller leverages the ant colony optimization algorithm to find the optimal routing path with minimum delay. Extensive simulations are carried out to demonstrate the accuracy of the traffic prediction model and the superiority of the proposed data dissemination scheme for Industry 4.0 applications.
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Key research and development plan of Shaanxi province
Key laboratory of industrial internet of things & networked control
Ministry of Education
Key laboratory of embedded system and service computing
Ministry of Education, Xi’an Science and Technology Plan
Xi’an Key Laboratory of Mobile Edge Computing and Security
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications
Cited by
58 articles.
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