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SDN 환경에서의 서버 부하 임계치 경고를 통한 효율적인 부하분산 기법

Efficient Load Balancing Technique through Server Load Threshold Alert in SDN

  • 투고 : 2021.07.22
  • 심사 : 2021.10.17
  • 발행 : 2021.10.31

초록

기존 네트워크 체계의 한계점을 극복하기 위해 등장한 SDN(Software Defined Networking) 기술은 네트워크 장비에서의 HW와 SW의 분리를 통해 기존 체계의 경직성을 해소한다. 이러한 SDN의 특성은 하드웨어 중심의 네트워크 장비를 벗어나 폭넓은 확장성을 제공하며, 다양한 규모의 데이터센터에서의 유연한 부하분산정책을 제공해준다. 그동안 이러한 SDN의 장점을 데이터센터에 적용한 연구들이 다수 진행되어왔으며 효과를 보여줬다. 기존 연구들에서 주되게 사용된 방식은 서버의 부하를 주기적으로 확인하여 이를 기반으로 부하분산을 수행하는 방식이었다. 이 방식에서는 서버의 수가 많고 서버 로드 확인 주기가 짧을수록 트래픽이 증가한다. 본 논문에서는 이러한 제한사항을 해소하기 위해 서버에서 특정 수준의 부하 발생 시 이를 컨트롤러로 보고하는 방식을 통해 불필요한 트래픽을 없애고 서버들의 자원을 보다 효율적으로 관리할 수 있는 새로운 부하분산 기법을 제안한다.

The SDN(Software Defined Networking) technology, which appeared to overcome the limitations of the existing network system, resolves the rigidity of the existing system through the separation of HW and SW in network equipment. These characteristics of SDN provide wide scalability beyond hardware-oriented network equipment, and provide flexible load balancing policies in data centers of various sizes. In the meantime, many studies have been conducted to apply the advantages of SDN to data centers and have shown their effectiveness. The method mainly used in previous studies was to periodically check the server load and perform load balancing based on this. In this method, the more the number of servers and the shorter the server load check cycle, the more traffic increases. In this paper, we propose a new load balancing technique that can eliminate unnecessary traffic and manage server resources more efficiently by reporting to the controller when a specific level of load occurs in the server to solve this limitation.

키워드

참고문헌

  1. Martin McKeay, "Adapting to the Unpredictable," Akamai, State of the Internet, vol. 7, Issue 1, 2021.
  2. B. Yoon, "Future Networking Technology of SDN," Electronics and Telecommunications Trends, vol. 27, no. 2, 2012.
  3. D. Min, "Market Trends of SDN/NFV Supply and Demand," Electronics and Telecommunications Trends, ETRI, 2016.
  4. IDC, "Worldwide Data center Software-Defined Networking Forecast, 2019-2023," Nov, 2019
  5. J. Jang "SDN/NFV Military application plan (Based on the Defense Integrated Data Center(DIDC))," The Korea Institute of Electronic Communication Sciences, vol.15, no.4, 2020, pp. 687-694.
  6. M. LEE "Implementation of a Platform for the Big Scientific Data Transfers," The Korea Institute of Electronic Communication Sciences, vol.13, no.4, 2018, pp. 881-886.
  7. J. Holusha, "Commercial Property/Engine Room for the Internet; Combining a Data Center Witha 'Telco Hotel," New York Times, 2019.
  8. J. Kim "Efficient Load Balancing Technique Considering Data Generation Form and Server Response Time in SDN," The Korea Institute of Electronic Communication Sciences, vol.15, no.4, 2020, pp. 679-686.
  9. P. Deepalakshmi, "D-Serv LB: Dynamic server load balancing algorithm," International Journal of Communication Systems, vol. 32, Issue. 1, 2019, pp. 293-310.
  10. M. Yang, "Research on Load Balancing Algorithm Based on the Unused Rate of the CPU and Memory," International Conference on Instrumentation and Measurement, Computer, Communication and Control(IMCCC), 2015, pp. 542-545.
  11. S. Kiarash, "SD-WLB: An SDN aided mechanism for web load balancing based on server statistics," ETRI, vol.41, Issue. 2, 2018, pp. 197-206.
  12. B. Lee "A Study on Efficient Load Balancing Mechanism in Distributed Web Cluster System," Korea Society of Computer Information, vol.16, no.8, 2011, pp. 11-18. https://doi.org/10.9708/jksci.2011.16.8.011