정보과학회 논문지 (Journal of KIISE)

  • 제42권11호
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  • Pages.1423-1429
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  • 2015
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  • 2383-630X(pISSN)
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  • 2383-6296(eISSN)
한국정보과학회 (Korean Institute of Information Scientists and Engineers)
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미래 사물인터넷을 위한 마르코프 게임 기반의 QoS 제어 기법

A Markov Game based QoS Control Scheme for the Next Generation Internet of Things

  • 김승욱 (서강대학교 컴퓨터공학과)
  • 투고 : 2015.05.06
  • 심사 : 2015.09.03
  • 발행 : 2015.11.15
⟨ 이전 논문 다음 논문 ⟩

초록

최근, 인터넷이 확장됨에 따라 새로운 가치를 생산하는 활용성이 증가되고 있다. 사물인터넷(Internet of Things)은 미래인터넷의 새로운 개념으로, 네트워크 물리적 객체들의 상호연결을 강조하여 최근 크게 주목받고 있으나, 사물인터넷상에서 서로 다른 서비스품질 요구를 만족시키기란 상당히 어렵다. 본 논문에서는, 사물인터넷 시스템의 다양한 서비스품질요구를 만족시킬 수 있는 효율적인 자원할당 방법을 제시한다. 제안된 방법은 마르코프 게임 모델에 기초하여 시스템 성능을 최대화할 수 있도록 효율적으로 사물인터넷 자원들을 할당한다. 시뮬레이션 결과, 제안된 방법은 현재의 사물인터넷 상황에서 기존의 방식에 비해 뛰어난 성능을 보여준다.

The Internet of Things (IoT) is a new concept associated with the future Internet, and it has recently become a popular concept to build a dynamic, global network infrastructure. However, the deployment of IoT creates difficulties in satisfying different Quality of Service (QoS) requirements and achieving rapid service composition and deployment. In this paper, we propose a new QoS control scheme for IoT systems. The Markov game model is applied in our proposed scheme to effectively allocate IoT resources while maximizing system performance. The results of our study are validated by running a simulation to prove that the proposed scheme can promptly evaluate current IoT situations and select the best action. Thus, our scheme approximates the optimum system performance.

키워드

참고문헌

  1. Qi Zhang and Dewei Peng, "Intelligent Decision-Making Service Framework Based on QoS Model in the Internet of Things," IEEE DCABES'2012, pp. 103-107, 2012.
  2. Ling Li, Shancang Li and Shanshan Zhao, "QoS-Aware Scheduling of Services-Oriented Internet of Things," IEEE Transactions on Industrial Informatics, Vol. 10, No. 2, pp. 1497-1505, 2014. https://doi.org/10.1109/TII.2014.2306782
  3. Sungwook Kim, "Adaptive Ad-hoc Network Routing Scheme by Using Incentive-based Model," Ad hoc & Sensor Wireless Networks, Vol. 15, No. 2, pp. 107-125, 2012.
  4. J. van der Wal, "Discounted Markov games : successive approximation and stopping times," International Journal of Game Theory, Vol. 6, No. 1, pp. 11-22, 1977. https://doi.org/10.1007/BF01770870
  5. Peter Vrancx, Katja Verbeeck, and Ann Nowe, "Decentralized Learning in Markov Games," IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol. 38, No. 4, pp. 976-981, 2008. https://doi.org/10.1109/TSMCB.2008.920998
  6. Ren Duan, Xiaojiang Chen and Tianzhang Xing, "A QoS Architecture for IOT," iThings/CPSCom'2011, pp. 717-720, 2011.
  7. Imran, A., Bennis, M. and Giupponi, L., "Use of learning, game theory and optimization as biomimetic approaches for Self-Organization in macro-femtocell coexistence," IEEE WCNCW'2012, pp. 103-108, 2012.