Journal of Information Processing Systems

  • 제14권1호
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  • Pages.228-238
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  • 2018
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  • 1976-913X(pISSN)
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  • 2092-805X(eISSN)
한국정보처리학회 (Korea Information Processing Society)
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Efficient Flow Table Management Scheme in SDN-Based Cloud Computing Networks

  • Ha, Nambong (Dept. of Computer Science, Kyonggi University) ;
  • Kim, Namgi (Dept. of Computer Science, Kyonggi University)
  • 투고 : 2017.03.14
  • 심사 : 2017.05.06
  • 발행 : 2018.02.28
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초록

With the rapid advancement of Internet services, there has been a dramatic increase in services that dynamically provide Internet resources on demand, such as cloud computing. In a cloud computing service, because the number of users in the cloud is changing dynamically, it is more efficient to utilize a flexible network technology such as software-defined networking (SDN). However, to efficiently support the SDN-based cloud computing service with limited resources, it is important to effectively manage the flow table at the SDN switch. Therefore, in this paper, a new flow management scheme is proposed that is able to, through efficient management, speed up the flow-entry search speed and simultaneously maximize the number of flow entries. The proposed scheme maximizes the capacity of the flow table by efficiently storing flow entry information while quickly executing the operation of flow-entry search by employing a hash index. In this paper, the proposed scheme is implemented by modifying the actual software SDN switch and then, its performance is analyzed. The results of the analysis show that the proposed scheme, by managing the flow tables efficiently, can support more flow entries.

키워드

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Fig. 1. Flow table and flow entry fields.

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Fig. 2. Example of a hash-based flow table.

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Fig. 3. Example of a wildcard-based flow table.

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Fig. 4. The hash-indexed wildcard scheme.

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Fig. 5. Implemented architecture of the hash-assisted wildcard scheme.

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Fig. 6. Implemented architecture of the hash-indexed wildcard scheme.

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Fig. 7. Packet forwarding time for small system environment.

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Fig. 8. Packet forwarding time for large system environment.

Table 1. System environment for the experiments

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Table 2. Experimental setup

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참고문헌

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피인용 문헌

  1. Design and implementation of a Bloom filter-based data deduplication algorithm for efficient data management pp.1868-5145, 2018, https://doi.org/10.1007/s12652-018-0893-1