The cellular network plays a pivotal role in providing Internet access, since
it is the only global-scale infrastructure with ubiquitous mobility support. To
manage and maintain large-scale networks, mobile network operators require
timely information, or even accurate performance forecasts. In this paper, we
propose LightningNet, a lightweight and distributed graph-based framework for
forecasting cellular network performance, which can capture spatio-temporal
dependencies that arise in the network traffic. LightningNet achieves a steady
performance increase over state-of-the-art forecasting techniques, while
maintaining a similar resource usage profile. Our architecture ideology also
excels in the respect that it is specifically designed to support IoT and edge
devices, giving us an even greater step ahead of the current state-of-the-art,
as indicated by our performance experiments with NVIDIA Jetson.

我们提出了 LightningNet，​​一种轻量级的分布式基于图的框架，用于预测移动网络性能，能够捕捉网络流量中出现的时空依赖关系。LightningNet 在保持类似资源使用配置的同时，相对于现有技术具有稳定的性能提升。我们的架构理念还在支持物联网和边缘设备方面表现优秀，根据与 NVIDIA Jetson 的性能实验表明，我们具有更先进的技术水平。