Journal of KIISE:Software and Applications (한국정보과학회논문지:소프트웨어및응용)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
권호 표지

An Algorithm based on Evolutionary Computation for a Highly Reliable Network Design

높은 신뢰도의 네트워크 설계를 위한 진화 연산에 기초한 알고리즘

  • 김종율 (한국과학기술원 테크노경영연구소 정보통신경영연구실) ;
  • 이재욱 (동서대학교 인터넷공학부) ;
  • 현광남 (Waseda University Grad. School of Inform. Prod)
  • Published : 2005.04.01
Download PDF
⟨ Previous Next ⟩

Abstract

Generally, the network topology design problem is characterized as a kind of NP-hard combinatorial optimization problem, which is difficult to solve with the classical method because it has exponentially increasing complexity with the augmented network size. In this paper, we propose the efficient approach with two phase that is comprised of evolutionary computation approach based on Prufer number(PN), which can efficiently represent the spanning tree, and a heuristic method considering 2-connectivity, to solve the highly reliable network topology design problem minimizing the construction cost subject to network reliability: firstly, to find the spanning tree, genetic algorithm that is the most widely known type of evolutionary computation approach, is used; secondly, a heuristic method is employed, in order to search the optimal network topology based on the spanning tree obtained in the first Phase, considering 2-connectivity. Lastly, the performance of our approach is provided from the results of numerical examples.

일반적으로 네트워크 설계 문제는 네트워크의 크기가 늘어남에 따라 지수적으로 복잡도가 증가하여 전통적인 방법으로는 풀이하기 힘든 NP-hard 조합 최적화 문제 중의 하나로 분류될 수 있다. 본 논문에서는 네트워크 신뢰도 제약을 고려하면서 네트워크 구축비용을 효과적으로 최소화하는, 높은 신뢰도의 네트워크 토폴로지 설계 문제를 풀기 위해 스패닝 트리를 효율적으로 표현할 수 있는 Prufer수(PN) 기반의 진화 연산법과 2-연결성을 고려하는 휴리스틱 방법으로 구성된 두 단계의 효율적인 해법을 제안한다. 즉, 먼저 스패닝 트리를 찾아내기 위해 진화 연산법 중에 보편적으로 널리 알려져 있는 유전자 알고리즘(GA)을 이용하고 그 다음으로 첫 번째 단계에서 발견한 스패닝 트리에 대해 최적의 네트워크 토폴로지를 찾기 위해서 2-연결성을 고려한 휴리스틱 방법을 적용한다. 마지막으로 수치예의 결과를 통해 제안한 해법의 성능에 대해서 살펴보도록 한다.

Keywords

References

  1. R.H. Jan, F.J. Hwang, and S.T. Chen, Topological optimization of a communication network subject to a reliable constraint, IEEE Trans. Reliability, vol.42, no.1, pp.63-70, 1994 https://doi.org/10.1109/24.210272
  2. K.K. Aggarwal and S. Rai, Reliability evaluation of computer-communication networks, IEEE Trans. Reliability, vol.R-30, no.1, pp.32-35, 1981 https://doi.org/10.1109/TR.1981.5220952
  3. R.S. Wilkov. Design of computer networks based on a new reliability measure, Symposium on Computer-Communications Networks and Teletraffic, Ploytechnic institute of Brooklyn, pp.371-384, 1972
  4. K.K. Aggarwal, Y.C. Chopra, and J.S. Bajwa, Topological layout of links for optimising the overall reliability in a computer communication, Microelectronics & Reliability, vol.22, no.3, pp.347-351, 1982 https://doi.org/10.1016/0026-2714(82)90007-5
  5. Y.C. Chopra, B.S. Sohi, R.K Tiwari, and K.K. Aggarwal, Network topology for maximizing the terminal reliability in a computer communication networks, Microelectronics & Reliability, vol.24, pp.911-913, 1984 https://doi.org/10.1016/0026-2714(84)90019-2
  6. A.N. Venetsanopoulos and I. Singh, Topological optimization of communication networks subject to reliability constraints, Problem of Control and Information Theory, vol.15, pp.63-78, 1986
  7. F. Glover, M. Lee, and J. Ryan, Least-cost network topology design for a new service: an application of an tabu search, Annals of Operations Research, vol.33, pp.351-362, 1991 https://doi.org/10.1007/BF02073940
  8. S.J. Koh and C.Y. Lee, A tabu search for the survivable fiber optic communication network design, Computer and Industrial Engineering, vol.28, no.4, pp.689-700, 1995 https://doi.org/10.1016/0360-8352(95)00036-Z
  9. M.M. Atiqullah and S.S. Rao, Reliability optimization of communication networks using simulated annealing, Microelectronics & Reliability, vo1.33, no.9, pp.l303-1319, 1993 https://doi.org/10.1016/0026-2714(93)90132-I
  10. P.C. Fetterlof and G. Anandalingam, Optimal design of LAN-WAN internetworks: an approach using simulated annealing, Annals of Operations Research, vol.36, pp.275-298, 1992 https://doi.org/10.1007/BF02094334
  11. S. Pierre, M. Hyppolite, J. Bourjolly, and O. Dioume, Topological design of computer communication networks using simulated annealting, Engineering Applications of Artificial Intelligence, vol.8, no.1, pp.61-69, 1995 https://doi.org/10.1016/0952-1976(94)00041-K
  12. M. Gen and R. Cheng, Genetic Algorithms and Engineering Design, John Wiley & Sons, New York, 1997
  13. M. Gen and R. Cheng, Genetic Algorithms and Engineering Optimization, John Wiley & Sons, New York, 2000
  14. A. Kumar, R.M. Pathak, Y.P. Gupta, and H.R. Parsaei, A genetic algorithm for distributed system topology design, Computer and Industrial Engineering, vol.28, no. 3, pp.659-670, 1995 https://doi.org/10.1016/0360-8352(94)00218-C
  15. A. Kumar, R.M. Pathak, and Y.P. Gupta, Genetic-algorithm-based reliability optimization for computer network expansion, IEEE Trans. Reliability, vol.44, no.1, pp.63-72, 1995 https://doi.org/10.1109/24.376523
  16. D.L. Deeter and A.E. Smith, Economic design of reliable network, IIE Transaction, vol.30, pp.1161-1174, 1999
  17. Dengiz, B., F. Altiparmak, and A. E. Smith, 'Efficient optimization of all-terminal reliable networks using evolutionary approach,' IEEE Transaction on Reliability, Vol.46, No.1, pp.18-26, 1997 https://doi.org/10.1109/24.589921
  18. B. Dengiz, F. Altiparmak, and A.E. Smith, Local search genetic algorithm for optimal design of reliable networks, IEEE Trans. Evolutionary Computation, vol.1, no.3, pp.179-188, 1997 https://doi.org/10.1109/4235.661548
  19. M. Ball and R.M. Van Slyke, Backtracking algorithms for network reliability analysis, Annals of Discrete Mathematics, vol,1, pp.49-64, 1977 https://doi.org/10.1016/S0167-5060(08)70726-X
  20. S. Skiena, Implementing Discrete Mathematics Combinatorics and Graph Theory with Mathematica, Addison-Wesley, Reading, MA, 1990
  21. C. Hanzhong and L. Dongkui, A new algorithm for computing the reliability of complex networks by the cut method, Microelectronics & Reliability, vol.34, no.1 , pp.175-177, 1994 https://doi.org/10.1016/0026-2714(94)90489-8
  22. D. Mandaltsis and J,M. Kontolen, Overall reliability determination of computer networks with hierarchical routing strategies, Microelectronics & Reliability, vol.27, no.1, pp.129-143, 1987 https://doi.org/10.1016/0026-2714(87)90627-5
  23. C. Liu, M. Dai, X.Y. Wu, and W.K. Chen, A network overall reliability algorithm, Proc. Neural, Parallel & Scientific Computations, pp.287-292, Atlanta, 1995
  24. H. Cancela and M.E. Khadiri, A recursive variancereduction algorithm for estimating communication network reliability, IEEE Trans. Reliability, vol.44, no.4, pp.595-602, 1995 https://doi.org/10.1109/24.475978
  25. G.S. Fishman, A comparison of four monte carlo methods for estimating the probability of s-t connectedness, IEEE Trans. Reliability, vol.R-35, no.2, pp.145-155, 1986
  26. S.J. Kamat and M.W. Riley, Determination of reliability using event-based monte carlo simulation, IEEE Trans. Reliability, vol.R-24, no.1, pp.73-75, 1975 https://doi.org/10.1109/TR.1975.5215337
  27. H. Kumamoto, K. Tanaka, and K. Inoue, Efficient evaluation of system reliability by monte carlo method, IEEE Trans. Reliability, vol.R-26, no.5, pp.311-315, 1977 https://doi.org/10.1109/TR.1977.5220181
  28. M.S. Yeh, J.S. Lin, and W.C. Yeh, A new monte carlo method for estimating network reliability, Proc 16th Inter. Conf. on Computer & Industrial Engineering, pp.723-726, 1994
  29. G. R. Raidl and B. A. Julstrom, 'Edge Sets: An effective evolutionary coding of spanning trees,' IEEE Transaction on Evolutionary Computation, Vol.7, No.3, pp.225-239, June, 2003 https://doi.org/10.1109/TEVC.2002.807275