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A Monitoring Scheme Based on Artificial Intelligence in Mobile Edge Cloud Computing Environments

모바일 엣지 클라우드 환경에서 인공지능 기반 모니터링 기법

  • 임종범 (한국산업기술대학교 게임공학부) ;
  • 최희석 (고려대학교 컴퓨터학과) ;
  • 유헌창 (고려대학교 컴퓨터학과)
  • Received : 2017.12.11
  • Accepted : 2018.01.28
  • Published : 2018.02.28

Abstract

One of the crucial issues in mobile edge cloud computing environments is to monitor mobile devices. Due to the inherit properties of mobile devices, they are prone to unstable behavior that leads to failures. In order to satisfy the service level agreement (SLA), the mobile edge cloud administrators should take appropriate measures through a monitoring scheme. In this paper, we propose a monitoring scheme of mobile devices based on artificial intelligence in mobile edge cloud computing environments. The proposed monitoring scheme is able to measure faults of mobile devices based on previous and current monitoring information. To this end, we adapt the hidden markov chain model, one of the artificial intelligence technologies, to monitor mobile devices. We validate our monitoring scheme based on the hidden markov chain model. The proposed monitoring scheme can also be used in general cloud computing environments to monitor virtual machines.

모바일 엣지 클라우드 환경에서 중요하게 다루어야 할 사항 중 하나는 모바일 장치에 대한 모니터링이다. 모바일 장치는 장치의 특성상 불안정한 상태가 발생하여 결함이 발생할 수 있기 때문에 모바일 엣지 클라우드의 SLA (Service Level Agreement)를 만족시키기 위해서는 모바일 장치의 모니터링 기법을 통해 결함을 측정하여 이에 대한 조치를 수행하여야 한다. 이 논문에서는 모바일 엣지 클라우드 환경에서 인공지능 기반 모바일 장치 모니터링 기법을 제안한다. 제안하는 모니터링 기법은 모바일 장치에 대한 이전 모니터링 정보와 현재 모니터링 정보를 기반으로 모바일 장치의 결함 발생을 측정할 수 있도록 설계 되었다. 이를 위해 인공지능 기법 중 하나인 은닉 마르코프 체인 모델을 모바일 장치에 대한 모니터링 기법에 적용하였다. 실험 평가를 통해 제안하는 모니터링 기법에 대한 검증을 수행하였다. 제안하는 기법은 모바일 장치뿐만 아니라 일반적인 클라우드 환경에서의 가상 머신을 모니터링 하는 방법으로도 활용할 수 있도록 설계되었다.

Keywords

References

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