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Performance Analysis and Optimization of OpenDaylight Controller in Distributed Cluster Environment

분산 클러스터 환경에서 오픈데이라이트 컨트롤러 성능 분석 및 최적화

  • 이솔이 (충북대학교 정보통신공학부) ;
  • 김태홍 (충북대학교 정보통신공학부) ;
  • 김태준 (충북대학교 정보통신공학부)
  • Received : 2017.04.05
  • Accepted : 2017.07.06
  • Published : 2017.11.30

Abstract

OpenDaylight is an SDN (Software Defined Networking) open source framework, which is popular in network fields recently. This paper analyzes the performance of a controller cluster architecture by focusing on distributed datastore and Raft leader election algorithm. In addition, we propose an enhanced version of Raft algorithm in order to improve the performance of distributed datastore by distributing shard leaders over controller cluster. This paper compares the conventional Raft algorithm with the proposed version of the Raft algorithm. Moreover, we compare the performance of distributed datastore according to shard roles such as leader and follower. Experimental results show that Shard leaders provide better performance than followers and Shard updating requests need to be distributed over multiple controllers. So, by using proposed version of Raft algorithm, controller performance can be improved. The details of the experiment results are cleary described.

본 논문에서는 SDN (Software Defined Networking) 오픈소스 프레임워크인 오픈데이라이트(ODL, OpenDaylight) 컨트롤러 클러스터 환경에서 클러스터의 구조를 분석하며 고가용성(High availability)을 지원하는 컨트롤러 클러스터의 동작 방식을 다룬다. 또한 Raft 알고리즘의 리더 선정(Leader Election) 과정을 분석하고 효율적인 시스템 운용을 위한 Leader Election 과정의 개선 방안을 제안한다. 이와 함께 샤드(Shard) 리더와 샤드 팔로어의 성능차이를 제시하고, 기존과 제안 방식의 컨트롤러 클러스터의 성능을 비교 분석한다. 실험의 결과에 따르면 리더의 성능은 팔로어의 성능보다 좋으며 하나의 컨트롤러로 요청이 집중되어 전달될 때보다 분산된 컨트롤러로 요청이 전달될 때의 성능이 더 좋다. 따라서 제안 기법을 통하여 컨트롤러로의 요청을 분산함으로써 성능을 높일 수 있다.

Keywords

References

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