# Network-Optimised Spiking Neural Network for Event-Driven Networking

arXiv: https://arxiv.org/abs/2509.23516 · HTML: https://mlsanity.com/paper/2509.23516/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Sep 2025.

## Built on by (most cited first, 3 of 3)

- [Network-Optimised Spiking Neural Network (NOS) Scheduling for 6G O-RAN: Spectral Margin and Delay-Tail Control](https://mlsanity.com/paper/2510.11291/) (2025)
- [Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safety](https://mlsanity.com/paper/2605.12729/) (2026)
- [NOS-Gate: Queue-Aware Streaming IDS for Consumer Gateways under Timing-Controlled Evasion](https://mlsanity.com/paper/2601.00389/) (2026)

## Abstract (arXiv)

Delay-coupled systems often require low-latency decisions from sparse telemetry, where dense fixed-step neural inference is wasteful and can degrade near stability margins. We introduce Network-Optimised Spiking (NOS), a trainable two-state event-driven dynamical unit for delayed, graph-coupled streams, whose states map to a fast load variable and a slower recovery resource. NOS uses bounded excitability for finite buffers, explicit leak terms for service and damping, and graph-local coupling with per-link gates and communication delays, with differentiable resets compatible with surrogate-gradient training and neuromorphic execution. We prove existence and uniqueness of subthreshold equilibria, derive Jacobian-based stability conditions, and obtain a scalar network stability threshold that separates topology from node dynamics via a Perron-mode spectral condition. A stochastic arrival model aligned with telemetry smoothing explains increased variability as systems approach stability boundaries. On delayed graph forecasting and early-warning tasks from queue telemetry, NOS improves detection F1 and detection latency over MLP, RNN/GRU, and temporal GNN baselines under a common residual-based protocol, while providing calibration rules for resource-constrained deployments. Code and Demos: https://mbilal84.github.io/nos-snn-networking/