# Closing the Management Gap for Satellite-Integrated Community Networks: A Hierarchical Approach to Self-Maintenance

arXiv: https://arxiv.org/abs/2202.07532 · HTML: https://mlsanity.com/paper/2202.07532/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 15 references that are in the map.
- First posted on arXiv 15 Feb 2022.

## Builds on (most cited first, 2 of 2)

- [RemIX: A Distributed Internet Exchange for Remote and Rural Networks](https://mlsanity.com/paper/1603.08978/) (2016)
- [Community Networks and Sustainability: a Survey of Perceptions, Practices, and Proposed Solutions](https://mlsanity.com/paper/1707.06898/) (2017)

## Abstract (arXiv)

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