LBRS: A Reinforcement Learning Approach to Mixed Flow Scheduling in Data Center Networks.

Saved in:
Bibliographic Details
Title: LBRS: A Reinforcement Learning Approach to Mixed Flow Scheduling in Data Center Networks.
Authors: XING-YAN ZHANG1,2, Zhangxy@hue.edu.cn
Source: Journal of Information Science & Engineering; Jul2025, Vol. 41 Issue 4, p915-926, 12p
Database: Applied Science & Technology Source
FullText Links:
  – Type: pdflink
Text:
  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 186742397
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: LBRS: A Reinforcement Learning Approach to Mixed Flow Scheduling in Data Center Networks.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22XING-YAN+ZHANG%22">XING-YAN ZHANG</searchLink><relatesTo>1,2</relatesTo>, <i>Zhangxy@hue.edu.cn</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Journal+of+Information+Science+%26+Engineering%22">Journal of Information Science & Engineering</searchLink>; Jul2025, Vol. 41 Issue 4, p915-926, 12p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=186742397
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.6688/JISE.202507_41(4).0009
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
        StartPage: 915
    Titles:
      – TitleFull: LBRS: A Reinforcement Learning Approach to Mixed Flow Scheduling in Data Center Networks.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: XING-YAN ZHANG
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 07
              Text: Jul2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 10162364
          Numbering:
            – Type: volume
              Value: 41
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Journal of Information Science & Engineering
              Type: main
ResultId 1