Twin Sorting Dynamic Programming Assisted User Association and Wireless Bandwidth Allocation for Hierarchical Federated Learning
<|reference_start|>Twin Sorting Dynamic Programming Assisted User Association and Wireless Bandwidth Allocation for Hierarchical Federated Learning: 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.<|reference_end|>
@article{gau2024twin,
    title={Twin Sorting Dynamic Programming Assisted User Association and Wireless
  Bandwidth Allocation for Hierarchical Federated Learning},
    author={Rung-Hung Gau, Ting-Yu Wang and Chun-Hung Liu},
    journal={arXiv preprint arXiv:2408.09076},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.09076},
    primaryClass={cs.LG cs.NI}
}