A Multi-Layer Collaboration Framework for Industrial Parks with 5G Vehicle-to-Everything Networks

Yanjun Shi , Qiaomei Han , Weiming Shen * , Xianbin Wang

Engineering ›› 2021, Vol. 7 ›› Issue (6) : 818 -831.

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Engineering ›› 2021, Vol. 7 ›› Issue (6) : 818 -831. DOI: 10.1016/j.eng.2020.12.021
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A Multi-Layer Collaboration Framework for Industrial Parks with 5G Vehicle-to-Everything Networks

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Abstract

The fifth-generation (5G) wireless communication networks are expected to play an essential role in the transformation of vertical industries. Among many exciting applications to be enabled by 5G, logistics tasks in industry parks can be performed more efficiently via vehicle-to-everything (V2X) communications. In this paper, a multi-layer collaboration framework enabled by V2X is proposed for logistics management in industrial parks. The proposed framework includes three layers: a perception and execution layer, a logistics layer, and a configuration layer. In addition to the collaboration among these three layers, this study addresses the collaboration among devices, edge servers, and cloud services. For effective logistics in industrial parks, task collaboration is achieved through four functions: environmental perception and map construction, task allocation, path planning, and vehicle movement. To dynamically coordinate these functions, device–edge–cloud collaboration, which is supported by 5G slices and V2X communication technology, is applied. Then, the analytical target cascading method is adopted to configure and evaluate the collaboration schemes of industrial parks. Finally, a logistics analytical case study in industrial parks is employed to demonstrate the feasibility of the proposed collaboration framework.

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5G / Vehicle-to-everything / Industrial park / Logistics / Device–edge–cloud collaboration / Analytical target cascading

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Yanjun Shi, Qiaomei Han, Weiming Shen *, Xianbin Wang. A Multi-Layer Collaboration Framework for Industrial Parks with 5G Vehicle-to-Everything Networks. Engineering, 2021, 7(6): 818-831 DOI:10.1016/j.eng.2020.12.021

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