Abstract
Massive machine-type communications (mMTCs) for Internet of things are being developed thanks to the fifth-generation (5G) wireless systems. Narrowband Internet of things (NB-IoT) is an important communication technology for machine-type communications. It supports many different protocols for communication. The reliability and performance of application layer communication protocols are greatly affected by the retransmission time-out (RTO) algorithm. In order to improve the reliability and performance of machine-type communications, this study proposes a novel RTO algorithm UDP-XGB based on the user datagram protocol (UDP) and NB-IoT. It combines traditional algorithms with machine learning. The simulation results show that real round-trip time (RTT) is close to the RTO, which is obtained by this algorithm, and the reliability and performance of machine-type communications have improved.
Highlights
5G, the fifth generation of mobile communication technology, on the one hand, greatly improves the high-bandwidth mobile Internet service experience of individual users and creates new life and entertainment application scenarios
To prevent the high-frequency communication of some devices in Massive machine-type communications (mMTCs) from consuming too much network resources, we need to analyze it from different technical levels based on the existing Internet of things (IoT) communication technology
Based on the above observations, this study studies how to determine the retransmission time-out (RTO) when Narrowband Internet of things (NB-IoT) uses user datagram protocol (UDP) for reliable transmission in mobile scenarios. e objective is how to send the same data with less network resources and lower network delay compared with traditional algorithms
Summary
5G, the fifth generation of mobile communication technology, on the one hand, greatly improves the high-bandwidth mobile Internet service experience of individual users and creates new life and entertainment application scenarios. To prevent the high-frequency communication of some devices in mMTC from consuming too much network resources, we need to analyze it from different technical levels based on the existing IoT communication technology. E network layer is responsible for the data communication between different devices and the cloud. NB-IoT communication needs the protocol support of transport layer, such as transmission control protocol (TCP) and user datagram protocol (UDP). When a device using NB-IoT is moving, the network will produce large fluctuations, such as from outdoor to indoor At this time, the determination of RTO is often not ideal, resulting in high network delay of data transmission or large network resource consumption. Based on the above observations, this study studies how to determine the RTO when NB-IoT uses UDP for reliable transmission in mobile scenarios. We use machine-learning methods to analyze the collected data and propose a UDPXGB algorithm [28]. is study further improves the performance of the UDP-XGB algorithm, and enriches and improves the experimental simulation
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