Automatic Network Slicing for IoT in Smart City
Fanqin Zhou, Peng Yu, Lei Feng, Xuesong Qiu, Zhili Wang, Luoming Meng, Michel Kadoch, Liang Gong, Xianjiong Yao
Abstract
Internet of things (IoT) in smart city consists of a diversity of public utility and vertical industry services with extremely different performance requirements. As a key technology of 5G networks, network slicing (NS) is featured to provide distinct virtual networks and differentiated QoS guarantees in a shared infrastructure. Therefore, it becomes necessary to employ intelligent NS management for IoT in smart city. This work proposes a machine learning (ML) driven automatic NS framework which can intelligently scale slice according to network state. The resource preservation and slicing implementation scheme is given to trade off robustness and resource efficiency. Finally, the present study provides preliminary results via simulation and experimentation to justify the effectiveness and efficiency of the presented design.