Sequenced Switch Migration for Balancing Controller Loads in Large-Scale Software-Defined Networking.

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Title: Sequenced Switch Migration for Balancing Controller Loads in Large-Scale Software-Defined Networking.
Authors: Lan Yao1, Tao Hu1 hutaondsc@163.com, Julong Lan1
Source: International Journal of Performability Engineering. Aug2018, Vol. 14 Issue 8, p1848-1856. 9p.
Subjects: Software-defined networking, Computer network software, Controller area network (Computer network), Electronic controllers, Heuristic algorithms, Signal processing
Abstract: The proposal of the multi-controller has improved the scalability and reliability of software-defined networking (SDN), and the entire network is divided into several subdomains with the self-governed controller. Due to the dynamic changes of network traffic in different subdomains, a new challenge has emerged for balancing loads on the distributed controllers. Switch migration, a promising method, is designed to solve the unbalanced distribution of controller loads. However, existing schemes implement switch migration without considering migration sequences and are characterized by long migration time and poor controller processing efficiency. To solve the above problems, this paper proposes the Sequenced Switch Migration (SSM) approach, which considers migration parameters (e.g., delay, traffic, residual capacity, and failure probability) for multi-objective optimization and achieves efficient switch migration using a sequenced manner. By executing the parallel and heuristic algorithms, SSM can reduce the execution time of migration while ensuring the performance requirements of controllers. The simulation results show that compared with the existing schemes, SSM reduces the total migration time by about 32.7% and decreases controller load variance by 28.5% when controllers are under high load condition. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Performability Engineering is the property of Totem Publisher, Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Sequenced Switch Migration for Balancing Controller Loads in Large-Scale Software-Defined Networking.
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  Data: <searchLink fieldCode="AR" term="%22Lan+Yao%22">Lan Yao</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Tao+Hu%22">Tao Hu</searchLink><relatesTo>1</relatesTo><i> hutaondsc@163.com</i><br /><searchLink fieldCode="AR" term="%22Julong+Lan%22">Julong Lan</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Performability+Engineering%22">International Journal of Performability Engineering</searchLink>. Aug2018, Vol. 14 Issue 8, p1848-1856. 9p.
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  Data: <searchLink fieldCode="DE" term="%22Software-defined+networking%22">Software-defined networking</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+network+software%22">Computer network software</searchLink><br /><searchLink fieldCode="DE" term="%22Controller+area+network+%28Computer+network%29%22">Controller area network (Computer network)</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+controllers%22">Electronic controllers</searchLink><br /><searchLink fieldCode="DE" term="%22Heuristic+algorithms%22">Heuristic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing%22">Signal processing</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The proposal of the multi-controller has improved the scalability and reliability of software-defined networking (SDN), and the entire network is divided into several subdomains with the self-governed controller. Due to the dynamic changes of network traffic in different subdomains, a new challenge has emerged for balancing loads on the distributed controllers. Switch migration, a promising method, is designed to solve the unbalanced distribution of controller loads. However, existing schemes implement switch migration without considering migration sequences and are characterized by long migration time and poor controller processing efficiency. To solve the above problems, this paper proposes the Sequenced Switch Migration (SSM) approach, which considers migration parameters (e.g., delay, traffic, residual capacity, and failure probability) for multi-objective optimization and achieves efficient switch migration using a sequenced manner. By executing the parallel and heuristic algorithms, SSM can reduce the execution time of migration while ensuring the performance requirements of controllers. The simulation results show that compared with the existing schemes, SSM reduces the total migration time by about 32.7% and decreases controller load variance by 28.5% when controllers are under high load condition. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Performability Engineering is the property of Totem Publisher, Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.23940/ijpe.18.08.p22.18481856
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 9
        StartPage: 1848
    Subjects:
      – SubjectFull: Software-defined networking
        Type: general
      – SubjectFull: Computer network software
        Type: general
      – SubjectFull: Controller area network (Computer network)
        Type: general
      – SubjectFull: Electronic controllers
        Type: general
      – SubjectFull: Heuristic algorithms
        Type: general
      – SubjectFull: Signal processing
        Type: general
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      – TitleFull: Sequenced Switch Migration for Balancing Controller Loads in Large-Scale Software-Defined Networking.
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            NameFull: Lan Yao
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            NameFull: Tao Hu
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            NameFull: Julong Lan
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            – D: 01
              M: 08
              Text: Aug2018
              Type: published
              Y: 2018
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            – TitleFull: International Journal of Performability Engineering
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