@techreport{oai:ipsj.ixsq.nii.ac.jp:00222162,
 author = {長屋, 健太郎 and 落合, 秀也 and 江崎, 浩 and Kentaro, Nagaya and Hideya, Ochiai and Hiroshi, Esaki},
 issue = {23},
 month = {Nov},
 note = {Wireless Ad-Hoc Federated Learning (WAFL) の研究はシミュレーションを用いたものが殆どで，その実現可能性に着目しマイクロコンピュータ等を用いてアルゴリズムの実装を試みた例は存在しない．本研究では WAFL におけるモデルの送受信アルゴリズムを提案，実装する．次にフィールド実験を実施し，モデルの復元に必要なパケット受信成功率をパラメータとして変動させながら，WAFL における前方誤り訂正を用いたパケット冗長化の有用性を検討する．, Most studies of Wireless Ad-Hoc Federated Learning (WAFL) are done in simulations, and few have focused on its feasibility and tried to implement its algorithm. In this study, we first propose and implement model transfer algorithm of WAFL. After that, we install the program to micro computers and perform a field experiment. The result of the experiment is then processed to multiple contact patterns of nodes by varying a model restoring threshold. From the result of WAFL simulations done by using the actual contact patterns acquired from the experiment, we aim to analyze the effectiveness of Forward Error Correction on WAFL.},
 title = {Wireless Ad-Hoc Federated Learning における前方誤り訂正による機械学習モデルの交換手法},
 year = {2022}
}