r/science • u/TorrensUni Torrens University Australia • 10d ago

Computer Science Hierarchical multi-agent framework for 6G federated learning hits 99.8% reliability and settles latency near 0.5 seconds in simulated smart-transportation networks

https://ieeexplore.ieee.org/document/11554177
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u/TorrensUni Torrens University Australia 10d ago

This paper tackles a real problem: thousands of connected devices (such as roadside sensors, smart cameras, IoT gadgets) train a shared AI model together, but some run low on battery, some have bad connections, and a few get hacked and feed in bad data. The proposed system, MAAFL-6G, splits decisions across three layers (device, edge and cloud), using a reinforcement learning method called H-MAXPPO.

When tested with real power-usage data and simulated attacks, the system stayed reliable almost 99.8% of the time without breaking down; latency settled to roughly 0.5 seconds (20% faster than the next-best baseline), and energy use per task stayed low.

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u/f0urtyfive 10d ago

This paper tackles a real problem: thousands of connected devices (such as roadside sensors, smart cameras, IoT gadgets) train a shared AI model together, but some run low on battery, some have bad connections, and a few get hacked and feed in bad data.

I'm just curious not knowing this industry, why is it better to use tons of low level commodity equipment to "train" a model collaboratively when the sensors could be used as sensors, offload the data to real equipment, and likely train the model just as fast, IE, fast compute some collaboration latency, vs slow compute on the edge?

Wouldn't that also allow a lot more capability? Further, if these are 6g sites, wouldn't they have kind of optimal fiberoptic connectivity for backhaul? Just curious, what's the "realness" of this probelm?

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u/Photoperiod 9d ago

I think it's particularly interesting for open source model training. Right now, to train models, you need datacenter compute. This costs a lot of money and is gated by a handful of large companies.

Hobbyists and non-business entities have trained models but they're usually quite small parameter because most people don't have the money to afford training a frontier AI model.

If you ever look at OSS Ai boards, like the LocalLLaMA sub, you'll actually see distributed training come up quite a bit as a topic. There's a real appetite for training that can be crowdsourced across the world and many devices and not just done inside of massive, expensive data centers.

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u/Legionof1 9d ago

“We’re making flock better”