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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
  • Northwestern Polytechnical University Xian
  • City University of Hong Kong
  • Harbin Engineering University

Research output: Contribution to journalLetterpeer-review

8 Scopus citations

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.

Original languageEnglish
Article number193501
JournalFrontiers of Computer Science
Volume19
Issue number3
DOIs
StatePublished - Mar 2025

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