Node selection based on label quantity information in federated learning
Aiming at the problem that the difference of node data distribution has adverse effect on the performance of federated learning algorithm, a node selection algorithm based on label quantity information was proposed.An optimization objective based on the label quantity information of nodes was design...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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China InfoCom Media Group
2021-12-01
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| Series: | 物联网学报 |
| Subjects: | |
| Online Access: | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2021.00249/ |
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| _version_ | 1850091095443111936 |
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| author | Jiahua MA Xinghua SUN Wenchao XIA Xijun WANG Hongzhou TAN Hongbo ZHU |
| author_facet | Jiahua MA Xinghua SUN Wenchao XIA Xijun WANG Hongzhou TAN Hongbo ZHU |
| author_sort | Jiahua MA |
| collection | DOAJ |
| description | Aiming at the problem that the difference of node data distribution has adverse effect on the performance of federated learning algorithm, a node selection algorithm based on label quantity information was proposed.An optimization objective based on the label quantity information of nodes was designed, considering the optimization problem of selecting the nodes with balanced label distribution under a certain time consumption limit.According to the correlation between the aggregated label distribution of selected nodes and the convergence of the global model, the upper bound of the weight divergence of the global model was reduced to improve the convergence stability of the algorithm.Simulation results shows that the new algorithm had higher convergence efficiency than the existing node selection algorithm. |
| format | Article |
| id | doaj-art-748e3400ad4f43ab92d918b211dcc498 |
| institution | DOAJ |
| issn | 2096-3750 |
| language | zho |
| publishDate | 2021-12-01 |
| publisher | China InfoCom Media Group |
| record_format | Article |
| series | 物联网学报 |
| spelling | doaj-art-748e3400ad4f43ab92d918b211dcc4982025-08-20T02:42:26ZzhoChina InfoCom Media Group物联网学报2096-37502021-12-015465359647552Node selection based on label quantity information in federated learningJiahua MAXinghua SUNWenchao XIAXijun WANGHongzhou TANHongbo ZHUAiming at the problem that the difference of node data distribution has adverse effect on the performance of federated learning algorithm, a node selection algorithm based on label quantity information was proposed.An optimization objective based on the label quantity information of nodes was designed, considering the optimization problem of selecting the nodes with balanced label distribution under a certain time consumption limit.According to the correlation between the aggregated label distribution of selected nodes and the convergence of the global model, the upper bound of the weight divergence of the global model was reduced to improve the convergence stability of the algorithm.Simulation results shows that the new algorithm had higher convergence efficiency than the existing node selection algorithm.http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2021.00249/federated learningnode selectioncommunication delay |
| spellingShingle | Jiahua MA Xinghua SUN Wenchao XIA Xijun WANG Hongzhou TAN Hongbo ZHU Node selection based on label quantity information in federated learning 物联网学报 federated learning node selection communication delay |
| title | Node selection based on label quantity information in federated learning |
| title_full | Node selection based on label quantity information in federated learning |
| title_fullStr | Node selection based on label quantity information in federated learning |
| title_full_unstemmed | Node selection based on label quantity information in federated learning |
| title_short | Node selection based on label quantity information in federated learning |
| title_sort | node selection based on label quantity information in federated learning |
| topic | federated learning node selection communication delay |
| url | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2021.00249/ |
| work_keys_str_mv | AT jiahuama nodeselectionbasedonlabelquantityinformationinfederatedlearning AT xinghuasun nodeselectionbasedonlabelquantityinformationinfederatedlearning AT wenchaoxia nodeselectionbasedonlabelquantityinformationinfederatedlearning AT xijunwang nodeselectionbasedonlabelquantityinformationinfederatedlearning AT hongzhoutan nodeselectionbasedonlabelquantityinformationinfederatedlearning AT hongbozhu nodeselectionbasedonlabelquantityinformationinfederatedlearning |