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In this chapter, we present a communication-efficient hierarchical federated learning framework over client-edge-cloud continuum, which efficiently integrates both synchronous client-edge model aggregation and asynchronous edge-cloud model aggregation, and conducts adaptive staleness control for accurate and cost-efficient FL model learning.

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Communication-Efficient Client-Edge-Cloud Hierarchical Federated Learning

  • 章节

  • 发表日期：

    2025年

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  • Sen Lin,
  • Zhi Zhou,
  • Zhaofeng Zhang,
  • Xu Chen,
  • Junshan Zhang

摘要

In this chapter, we present a communication-efficient hierarchical federated learning framework over client-edge-cloud continuum, which efficiently integrates both synchronous client-edge model aggregation and asynchronous edge-cloud model aggregation, and conducts adaptive staleness control for accurate and cost-efficient FL model learning.