论文标题
缩小卫星集成社区网络的管理差距：一种自我维护的等级制方法
Closing the Management Gap for Satellite-Integrated Community Networks: A Hierarchical Approach to Self-Maintenance
论文作者
论文摘要
社区网络（CNS）已成为在世界各地未服务和服务不足的地区提供基本互联网连接的重要范式。但是，中枢神经系统的不可或缺的部分是网络管理，在这种网络管理中，响应迅速和自主维护非常需要。随着电信网络中的技术进步，设想将经典的卫星依赖性CN转变为卫星集成的CN（SICN），该卫星将具有重要的自主权，智能和网络管理中的可扩展性。本文讨论了基于机器学习（ML）的层次结构方法，以实现对SICN的自主自我维护。该方法分为异常识别和缓解异常阶段，其中相关的ML方法，数据收集均值，部署选项和缓解方案。通过案例研究，我们讨论了使用卫星和固定连接作为回程选项的典型情况
Community networks (CNs) have become an important paradigm for providing essential Internet connectivity in unserved and underserved areas across the world. However, an indispensable part for CNs is network management, where responsive and autonomous maintenance is much needed. With the technological advancement in telecommunications networks, a classical satellite-dependent CN is envisioned to be transformed into a satellite-integrated CN (SICN), which will embrace significant autonomy, intelligence, and scalability in network management. This article discusses the machine-learning (ML) based hierarchical approach to enabling autonomous self-maintenance for SICNs. The approach is split into the anomaly identification and anomaly mitigation phases, where the related ML methods, data collection means, deployment options, and mitigation schemes are presented. With the case study, we discuss a typical scenario using satellite and fixed connections as backhaul options and show the effectiveness and performance improvements of the proposed approach with recurrent neural network and ensemble methods
