MANE: A Multi-Path Adaptive Network for Edge Onloading of Deep Neural Networks
Split computing constitutes a widely used distributed inference approach, where a lightweight head model is onloaded onto the device and a heavier tail model resides on an edge server, leveraging the growing computational capabilities of modern System-on-Chips while alleviating server load. As intelligent indoor environments such as smart offices grow increasingly populated with diverse IoT devices, a single edge server must simultaneously assist multiple devices, each competing for the same shared inference resources. Without a principled mechanism to manage this shared load, the server is quickly overwhelmed, causing latency SLO violations and rendering server-assisted inference ineffec...
| Authors | Sokratis Nikolaidis, Stylianos I. Venieris, Leonidas Malachias et al. |
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| Primary category | cs.DC |
| Published | 13 September 2026 |
| Last updated at source | 13 September 2026 |
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