Abstract
Inspired by the collective intelligence observed in natural swarms, where individual proactive actions contribute to superior global performance, we advocate for a shift towards Swarm DL. By harnessing the potential of physically adjacent mobile devices in IoT scenarios, we present DeepSwarm, a closed-loop system framework architecture. DeepSwarm facilitates bidirectional optimization between data acquisition and processing, aiming to push the performance boundaries of on-device DL Specifically, DeepSwarm addresses the requirements of proactive Swarm DL by decomposing them into layers: self-organized swarm data acquisition and self-adaptive, self-evolutionary swarm data processing. © Higher Education Press 2025.
| Original language | English |
|---|---|
| Article number | 193501 |
| Journal | Frontiers of Computer Science |
| Volume | 19 |
| Issue number | 3 |
| Online published | 20 Nov 2024 |
| DOIs | |
| Publication status | Published - Mar 2025 |
Funding
The work was supported by the National Science Fund for Distinguished Young Scholars (62025205), the National Natural Science Foundation of China (Grant Nos. 62032020, 62102317), CityU APRC Grant (9610633).
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