Research Article
A Traffic Prediction Algorithm Based on Converged Networks of LTE and Low Power Wide Area Networks
@INPROCEEDINGS{10.1007/978-3-030-72792-5_6, author={Huan Li and Feng Sun and Yang Liu and Shuai Ren and Yang Nan and Chao Chen}, title={A Traffic Prediction Algorithm Based on Converged Networks of LTE and Low Power Wide Area Networks}, proceedings={Simulation Tools and Techniques. 12th EAI International Conference, SIMUtools 2020, Guiyang, China, August 28-29, 2020, Proceedings, Part I}, proceedings_a={SIMUTOOLS}, year={2021}, month={4}, keywords={Network traffic Traffic estimation Traffic modeling Normal regression model Dynamic changes}, doi={10.1007/978-3-030-72792-5_6} }- Huan Li
Feng Sun
Yang Liu
Shuai Ren
Yang Nan
Chao Chen
Year: 2021
A Traffic Prediction Algorithm Based on Converged Networks of LTE and Low Power Wide Area Networks
SIMUTOOLS
Springer
DOI: 10.1007/978-3-030-72792-5_6
Abstract
Network traffic plays an important role in network management and network activities. It has an important impact on traffic engineering and network performance. However, we have larger difficulties in capturing and estimating them. This paper proposes a new estimating algorithm to forecast and model network traffic in time-frequency synchronization applications. Our approach is based on the normal regression theory. Firstly, normal regression theory is used to characterize and model network traffic. Secondly, the corresponding normal regression model is created to describe network traffic by finding the model parameters using the samples about network traffic. Finally, the estimation algorithm is proposed to predict network traffic in time-frequency synchronization applications. Simulation results indicate that our approach is effective.
