Data Dissemination for Industry 4.0 Applications in Internet of Vehicles Based on Short-term Traffic Prediction

2022 ◽  
Vol 22 (1) ◽  
pp. 1-18
Chen Chen ◽  
Lei Liu ◽  
Shaohua Wan ◽  
Xiaozhe Hui ◽  
Qingqi Pei

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.

2018 ◽  
Vol 26 (3) ◽  
pp. 25-36
Deo Prakash ◽  
Neeraj Kumar ◽  
M.L. Garg

Mobile Adhoc Network (MANET) is a dynamic network without any centralized control. Due to frequent topological change, routing has been always a challenging task in these networks. This article presents optimized routing for efficient data dissemination in MANETs to meet the fast-changing technology of today's world. A novel metric for such optimized routing in MANET is proposed. The main parameters considered to evaluate this metric are the energy consumed during the communication, link stability, Packet Delivery Ratio (PDR) and traffic. The concept is based on a scenario in which a mobile node (source) sends data packets to another mobile node (destination) through its dynamically connected neighboring nodes. The path which consumes the lowest energy and also shows highest link stability is selected for consideration. In case the paths consume the same amount of energy, the highest stable path is chosen. In this manner, the most optimized path is selected. The authors' routing approach shows more efficiency than earlier in dissemination of data and information over the Mobile Ad-Hoc Networks.

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Xiying Fan ◽  
Chuanhe Huang ◽  
Junyu Zhu ◽  
Bin Fu

Due to the dynamically changing topology of Internet of Vehicles (IoV), it is a challenging issue to achieve efficient data dissemination in IoV. This paper considers strongly connected IoV with a number of heterogenous vehicular nodes to disseminate information and studies distributed replication-based data dissemination algorithms to improve the performance of data dissemination. Accordingly, two data replication algorithms, a deterministic algorithm and a distributed randomised algorithm, are proposed. In the proposed algorithms, the number of message copies spread in the network is limited and the network will be balanced after a series of average operations among the nodes. The number of communication stages needed for network balance shows the complexity of network convergence as well as network convergence speed. It is proved that the network can achieve a balanced status after a finite number of communication stages. Meanwhile, the upper and lower bounds of the time complexity are derived when the distributed randomised algorithm is applied. Detailed mathematical results show that the network can be balanced quickly in complete graph; thus highly efficient data dissemination can be guaranteed in dense IoV. Simulation results present that the proposed randomised algorithm outperforms the present schemes in terms of transmissions and dissemination delay.

2021 ◽  
Vol 124 ◽  
pp. 102977
Junyi Li ◽  
Fangce Guo ◽  
Aruna Sivakumar ◽  
Yanjie Dong ◽  
Rajesh Krishnan

IEEE Access ◽  
2021 ◽  
pp. 1-1
Kyungeun Lee ◽  
Moonjung Eo ◽  
Euna Jung ◽  
Yoonjin Yoon ◽  
Wonjong Rhee

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