The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
권호 표지
DOI QR코드

DOI QR Code

Reliability-Based Adaptive Consensus Algorithm for Synchronization in a Distributed Network

분산 네트워크에서 단말 간 동기화를 위한 신뢰도 기반의 적응적 컨센서스 알고리즘

  • Seo, Sangah (Korea Advanced Institute of Science and Technology School of Electrical Engineering) ;
  • Yun, Sangseok (Korea Advanced Institute of Science and Technology School of Electrical Engineering) ;
  • Ha, Jeongseok (Korea Advanced Institute of Science and Technology School of Electrical Engineering)
  • Received : 2016.11.26
  • Accepted : 2017.03.06
  • Published : 2017.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

This paper investigates a synchronization algorithm for a distributed network which does not have a centralized infrastructure. In order to operate a distributed network, synchronization across distributed terminals should be acquired in advance, and hence, a plenty of distributed synchronization algorithms have been studied extensively in the past. However, most of the previous studies focus on the synchronization only in fault-free networks. Thus, if there are some malfunctioning terminals in the network, the synchronization can not be guaranteed with conventional distributed synchronization methods. In this paper, we propose a reliability-based adaptive consensus algorithm which can effectively acquire the synchronization across distributed terminals and confirm performance of the proposed algorithm by conducting numerical simulations.

본 논문에서는 중앙제어 형 기반 시설 없이 단말 간 자율적인 협력을 통해 무선 통신을 수행하는 분산 네트워크에서 단말 간 동기 획득을 위한 분산 동기 알고리즘에 관해 연구하였다. 무선 통신을 수행하기 위해 단말 간 동기는 필수적으로 획득되어야 하고, 따라서 이를 위한 다양한 분산 동기 알고리즘들이 활발히 연구되어 왔다. 하지만 대부분의 분산 동기 알고리즘에 관한 연구는 네트워크에 속한 모든 단말이 예외 없이 규칙을 따르는 경우에 한정되어 있다. 이 때문에 하나 이상의 단말이 기능 고장을 일으켜 오작동을 유발하거나, 혹은 단말 간 동기 획득을 방해할 목적으로 의도적인 오작동을 일으키는 단말이 네트워크에 존재하는 경우 기존 분산 동기 알고리즘으로는 단말 간 동기 획득을 보장할 수 없다. 이에 본 논문에서는 오작동이 존재하는 분산 네트워크에서도 효과적으로 단말 간 동기를 획득할 수 있는 신뢰도 기반의 적응적 컨센서스 알고리즘을 제안하고 실험적으로 검증하였다.

Keywords

References

  1. Y-J. Kim, J-Y. Jung, H-H. Choi, M-H. Han, C-Y. Park, and J-R. Lee, "Bio-inspired resource allocation scheme for multi-hop networks," J. KICS, vol. 40, no. 10, pp. 2035-2046, Oct. 2015. https://doi.org/10.7840/kics.2015.40.10.2035
  2. H.-H. Choi, B. Roh, H. Choi, and J.-R. Lee. "Bio-inspired routing protocol for mobile ad hoc networks," J. KICS, vol. 40, no. 11, pp. 2205-2217, Nov. 2015. https://doi.org/10.7840/kics.2015.40.11.2205
  3. O. Simeone, U. Spagnolini, Y. Bar-Ness, and S. H. Strogatz, "Distributed synchronization in wireless networks," IEEE Sign. Process. Mag., vol. 25, no. 5, pp. 81-97, Sept. 2008. https://doi.org/10.1109/MSP.2008.926661
  4. M.-J. Kim, Y.-J. Lee, and Y.-S. Cho, "A distributed time synchronization technique for OFDMA-based wireless mesh communication systems using bio-inspired algorithm," J. KICS, vol. 38, no. 12, pp. 1069-1078, Dec. 2013.
  5. W. Ren, R. W. Beard, and E. M. Atkins, "A survey of consensus problems in multi-agent coordination," in Proc. Am. Control Conf. 2005, pp. 1859-1864, Portland, Jun. 2005.
  6. J. N. Tsitsiklis, D. P. Bertsekas, and M. Athans, "Distributed asynchronous deterministic and stochastic gradient optimization algorithms," IEEE Trans. Automatic Control, vol. 31, no. 9, pp. 803-812, Sept. 1986. https://doi.org/10.1109/TAC.1986.1104412
  7. W. Ren and R. W. Beard, "Consensus seeking in multiagent systems under dynamically changing interaction topologies," IEEE Trans. Automatic Control, vol. 50, no. 5, pp. 655-661, May 2005. https://doi.org/10.1109/TAC.2005.846556
  8. R. O. Saber and R. M. Murray, "Agreement problems in networks with directed graphs and switching topology," in Proc. 42nd IEEE Conf. Decision and Control, pp. 4126-4132, Maui, Dec. 2003.
  9. R. O. Saber, "Distributed Kalman filtering for sensor networks," in Proc. 46th IEEE Conf. Decision and Control, pp. 5492-5498, New Orleans, Dec. 2007.
  10. R. O. Saber, "Kalman-consensus filter : optimality, stability, and performance," in Proc. 48th IEEE Conf. Decision and Control, pp. 7036-7042, Shanghai, Dec. 2009.
  11. Y-P. Tian, "Convergence rate of consensus algorithms with multiplicative and additive noisy measurements," in Proc. IEEE Conf. Control Appl., pp. 755-760, Argentian, Sept. 2016.
  12. A. Olshevsky and J. N. Tsitsiklis, "Convergence speed in distributed consensus and averaging," SIAM J. Control and Optimization, vol. 48, no. 1, pp. 33-55, Feb. 2009. https://doi.org/10.1137/060678324
  13. H. LeBlanc and X. Koutsoukos, "Consensus in networked multi-agent systems with adversaries," in Proc. 14th Int. Conf. Hybrid Systems: Computation and Control, pp. 281-290, Apr. 2011.
  14. S. Sundaram and C. N. Hadjicostis, "Distributed function calculation via linear iterative strategies in the presence of malicious agents," IEEE Trans. Automatic Control, vol. 56, no. 7, pp. 1495-1508, Jul. 2011. https://doi.org/10.1109/TAC.2010.2088690
  15. F. Pasqualetti, A. Bicchi, and F. Bullo, "On the security of linear consensus networks," in Proc. 48th IEEE Conf. Decision and Control, pp. 4894-4901, Shanghai, Dec. 2009.