DeepSwarm: towards swarm deep learning with bi-directional optimization of data acquisition and processing

Sicong Liu, Bin Guo, Ziqi Wang, Lehao Wang, Zimu Zhou, Xiaochen Li, Zhiwen Yu

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.