Interpretable Nonroutine Network Traffic Prediction with a Case Study
Abstract
This paper pioneers a nonroutine network traffic prediction (NNTP) method to prospectively provide a theoretical basis for avoiding large-scale network disruption by accurately predicting bursty traffic. Certain events that impact user behavior subsequently trigger nonroutine traffic, which significantly constrains the performance of network traffic prediction (NTP) models. By analyzing nonroutine traffic and the corresponding events, the NNTP method is pioneered to construct interpretable NTP model. Based on the real-world traffic data, the network traffic generated during soccer games serves as a case study to validate the performance of the NNTP method. The numerical results indicate that our prediction closely fits the traffic pattern. In comparison to existing researches, the NNTP method is at the forefront of finding a balance among interpretability, accuracy, and computational complexity.
Cite
@article{arxiv.2409.14550,
title = {Interpretable Nonroutine Network Traffic Prediction with a Case Study},
author = {Liangzhi Wang and Haoyuan Zhu and Jiliang Zhang and Zitian Zhang and Jie Zhang},
journal= {arXiv preprint arXiv:2409.14550},
year = {2024}
}
Comments
This work has been submitted to the IEEE for possible publication