为并行分层联合学习公平分配边缘服务器带宽

Md Anwar Hossen, Fatema Siddika, Wensheng Zhang
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引用次数: 0

摘要

本文探讨了三层系统中的并发 FL 进程,边缘设备和 FL 服务器之间有边缘服务器。这种设置面临的一个挑战是,从边缘设备到边缘服务器的带宽有限。因此,高效、公平地分配带宽以支持同步 FL 进程变得至关重要。我们提出了一种博弈论方法来模拟带宽分配问题,并开发了分布式和集中式启发式方案来找到博弈的近似纳什均衡。我们使用集中式和完全分布式假设提出了上述方法。通过严格的分析和实验,我们证明了我们的方案能高效、公平地为集中式和分布式方案的 FL 进程分配带宽,并且优于每个边缘服务器根据其收到的 FL 服务器请求按比例分配带宽的基准方案。建议的分布式和集中式方案性能相当。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fair Allocation of Bandwidth At Edge Servers For Concurrent Hierarchical Federated Learning
This paper explores concurrent FL processes within a three-tier system, with edge servers between edge devices and FL servers. A challenge in this setup is the limited bandwidth from edge devices to edge servers. Thus, allocating the bandwidth efficiently and fairly to support simultaneous FL processes becomes crucial. We propose a game-theoretic approach to model the bandwidth allocation problem and develop distributed and centralized heuristic schemes to find an approximate Nash Equilibrium of the game. We proposed the approach mentioned above using centralized and entirely distributed assumptions. Through rigorous analysis and experimentation, we demonstrate that our schemes efficiently and fairly assign the bandwidth to the FL processes for centralized and distributed solutions and outperform a baseline scheme where each edge server assigns bandwidth proportionally to the FL servers' requests that it receives. The proposed distributed and centralized schemes have comptetive performance.
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