Geometric Fairness-Aware Routing for Federated Edge Networks
Emerging 6G and edge-intelligent networks require effective and balanced routing algorithms among varied and spatially distributed devices. Existing federated routing systems often prioritize aggregate latency or throughput above fairness and the underlying geometric structure of network topologies. This paper describes Geo-FairFed, a geometric fairness-aware routing system that blends hyperbolic graph neural networks (HGNNs) and federated optimization to provide equal performance across edge nodes. Each node learns topology-aware representations on a negatively curved manifold, which include hierarchical relationships and connection asymmetries. A global aggregator next enforces fairness...
| Authors | Ratun Rahman |
|---|---|
| Primary category | cs.NI |
| Published | 31 May 2026 |
| Last updated at source | 31 May 2026 |
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