{"title":"Traffic Prediction and Resource Allocation Based on Deep Bidirectional LSTM in Data Center Networks","authors":"Yonghuai Wang","doi":"10.1109/ICCCI51764.2021.9486790","DOIUrl":null,"url":null,"abstract":"This article first proposes an adaptive traffic scheduling strategy for optoelectronic hybrid data centers. The strategy is composed of a deep bidirectional LSTM-based traffic prediction model and a prediction-assisted traffic scheduling method. The simulation results confirm that the presented method can achieve non-congested intra-data center traffic scheduling and higher network performance even under heavy traffic conditions.","PeriodicalId":180004,"journal":{"name":"2021 3rd International Conference on Computer Communication and the Internet (ICCCI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd International Conference on Computer Communication and the Internet (ICCCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCI51764.2021.9486790","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This article first proposes an adaptive traffic scheduling strategy for optoelectronic hybrid data centers. The strategy is composed of a deep bidirectional LSTM-based traffic prediction model and a prediction-assisted traffic scheduling method. The simulation results confirm that the presented method can achieve non-congested intra-data center traffic scheduling and higher network performance even under heavy traffic conditions.