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Twin Sorting Dynamic Programming Assisted User Association and Wireless Bandwidth Allocation for Hierarchical Federated Learning

arXiv 2408.09076 ↗First posted 17 Aug 2024cs.LG cs.NIcited by 0

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Abstract (arXiv)

In this paper, we study user association and wireless bandwidth allocation for a hierarchical federated learning system that consists of mobile users, edge servers, and a cloud server. To minimize the length of a global round in hierarchical federated learning with equal bandwidth allocation, we formulate a combinatorial optimization problem. We design the twin sorting dynamic programming (TSDP) algorithm that obtains a globally optimal solution in polynomial time when there are two edge servers. In addition, we put forward the TSDP-assisted algorithm for user association when there are three or more edge servers. Furthermore, given a user association matrix, we formulate and solve a convex optimization problem for optimal wireless bandwidth allocation. Simulation results show that the proposed approach outperforms a number of alternative schemes.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 19 of its 45 references that are in the map. First posted on arXiv 17 Aug 2024.

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19 of 45 references.

References · 19

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
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  10. 2021Hierarchical Federated Learning with Quantization: Convergence Analysis and System Designcited by 47
  11. 2020Multi-Stage Hybrid Federated Learning over Large-Scale D2D-Enabled Fog Networkscited by 42
  12. 2021Mobility-Aware Cluster Federated Learning in Hierarchical Wireless Networkscited by 35
7 more
  1. 2023HiFlash: Communication-Efficient Hierarchical Federated Learning with Adaptive Staleness Control and Heterogeneity-aware Client-Edge Associationcited by 17
  2. 2022Multi-Edge Server-Assisted Dynamic Federated Learning with an Optimized Floating Aggregation Pointcited by 10
  3. 2022Energy-Aware Edge Association for Cluster-based Personalized Federated Learningcited by 6
  4. 2022Time Minimization in Hierarchical Federated Learningcited by 4
  5. 2020Online User-AP Association with Predictive Scheduling in Wireless Caching Networkscited by 2
  6. 2014Optimizing User Association and Spectrum Allocation in HetNets: A Utility Perspectivecited by 1
  7. 2023Privacy-Preserving Joint Edge Association and Power Optimization for the Internet of Vehicles via Federated Multi-Agent Reinforcement Learningcited by 1

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