吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (05): 1395-1400.doi: 10.7964/jdxbgxb201305039

• paper • Previous Articles     Next Articles

Modeling and quantification of network survivability based on continuous time Markov

WU Wen1, MENG Xiang-ru1, LIU Yun-jiang1, HUO Xing-lin2   

  1. 1. Information and Navigation Institute, Airforce Engineering University, Xi'an 710077, China;
    2. Unit 68321 of PLA, Xi'an 710600, China
  • Received:2012-05-16 Online:2013-09-01 Published:2013-09-01

Abstract:

The network survivability modeling and quantification methods were studied for comprehensive and efficient quantification and analysis of the network survivability. The Heegaard's failure and recovery model and its state transformation were introduced. Then an improved network failure and recovery model based on Continuous Time Markov Chain (CTMC) was proposed. The improved model includes the failure state model and reduces the number of failure and recovery states. Combined with network performance models, an improved network survivability model based on CTMC was proposed. The survivable state transformation process after failure was simulated. Taking the packet loss state as the quantification factor, a network survivability quantification method based on improved CTMC network survivability model was given, that simplified the calculation of the survivability. Simulation results show that the proposed modeling and quantification methods can quantify the network survivability more comprehensively and accurately.

Key words: communications technology, IP network, continuous time Markov (CTMC), survivability quantification, packet loss rate

CLC Number: 

  • TN915.01

[1] Sterbenz P G, Hutchison D, Ctinkaya E K, et al. Resilience and survivability in communication networks: strategies, principles, and survey of disciplines[J]. Computer Networks, 2010, 54(8): 1245-1265.

[2] 李黎, 管晓宏, 赵千川, 等. 网络生存适应性的多目标评估[J]. 西安交通大学学报, 2010, 44(10): 1-7. Li Li, Guan Xiao-hong, Zhao Qian-chuan, et al. Multi-objective evaluation of network survival fitness[J]. Journal of Xi'an Jiaotong University, 2010, 44(10): 1-7.

[3] 蔡均平, 肖治庭, 李雪冬. 基于云模型的军事信息网络可生存性评估[J]. 武汉理工大学学报, 2010, 32(20): 11-15. Cai Jun-ping, Xiao Zhi-ting, Li Xue-dong. Survivability evaluation of military information networks based on cloud model[J]. Journal of Wuhan University of Technology, 2010, 32(20): 11-15.

[4] 刘密霞, 张玉清, 洪毅. 基于模糊推理的网络可生存性的建模与分析[J]. 通信学报, 2009, 30(1): 31-37. Liu Mi-xia, Zhang Yu-qing, Hong Yi. Modeling and analysis of network survivability based on fuzzy inference[J]. Journal on Communications, 2009, 30(1): 31-37.

[5] Zhao Guo-sheng, Wang Hui-qiang, Wang Jian. A novel formal analysis method of network survivability based on stochastic process algebra[J]. Tsinghua Science and Technology, 2007, 12(Sup.1): 175-179.

[6] 林雪纲, 许榕生. 信息系统生存性分析模型研究[J]. 通信学报, 2006, 27(2): 153-159. Lin Xue-gang, Xu Rong-sheng. Research on analysis model of information systems survivability[J]. Journal on Communications, 2006, 27(2): 153-159.

[7] Heegaard P E, Trivedi K S. Network survivability modeling[J]. Computer Networks, 2009, 53(8): 1215-1234.

[8] Heegaard P E, Trivedi K S. Survivability modeling with stochastic reward nets[C]//Proceedings of the 2009 Winter Simulation Conference. Texas, USA: IEEE Press, 2009: 807-818.

[9] Markopoulou A, Iannaccone G. Characterization of failures in an operational IP backbonee[J]. IEEE/ACM Transactions on Networking, 2008, 16(4): 749-762.

[10] Ma Z S, Krings A W. Dynamic hybrid fault modeling and extended evolutionary game theory for reliability, survivability and fault tolerance analyses[J]. IEEE Transactions on Reliability, 2011, 60(1): 180-196.

[11] Booker G, Springtson A. Efficient traffic loss evaluation for transport backbone networks[J]. Computer Networks, 2010, 54(10): 1683-1691.

[1] ZHAO Dan-feng, ZHU Tie-lin, LIU Yuan. Dynamic iteration stopping algorithm based on APPD [J]. , 2012, (03): 766-770.
[2] ZHANG Jing-bo,ZHANG Shu-fang,HU Qing,WANG Jin-peng,SUN Xiao-wen,JIANG Yi. Carrier PLL bandwidth in GNSS digital receiver [J]. 吉林大学学报(工学版), 2011, 41(6): 1793-1797.
[3] HUANG Zhan,GU Xue-mai,GUO Qing . Design and implementation of CZMLIPSec over satellitebased internet [J]. 吉林大学学报(工学版), 2008, 38(06): 1463-1468.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] ZHU Jian-feng, LIN Yi, CHEN Xiao-kai, SHI Guo-biao. Structural topology optimization based design of automotive transmission housing structure[J]. 吉林大学学报(工学版), 2013, 43(03): 584 -589 .
[2] ZHOU Feng-dao, WANG Jin-yu, TANG Hong-zhong, ZHANG He, ZHOU Ji-yu. Multi-frequency digital drive signal generation technology in near surface electromagnetic detection domain[J]. 吉林大学学报(工学版), 2013, 43(03): 682 -687 .
[3] OUYANG Ji-hong, WANG Zhen-xin, JING Li. Expanding 9-intersection model with metric relations[J]. 吉林大学学报(工学版), 2013, 43(03): 695 -700 .
[4] GUO Tie-liang, ZHAO Dan-feng, YANG Da-wei. Efficient Doppler estimation for UWA OFDM systems[J]. 吉林大学学报(工学版), 2013, 43(03): 813 -818 .
[5] HE Yao, LIU Xing-tao, ZHANG Chen-bin, CHEN Zong-hai. Insulation detection algorithm for high-power battery system based on internal resistance model[J]. 吉林大学学报(工学版), 2013, 43(05): 1165 -1170 .
[6] LI Zhi-bin, JIN Mao-jing, LIU Pan, XU Cheng-cheng. Evaluation of impact variable speed limits on improving traffic efficiency on freeways[J]. 吉林大学学报(工学版), 2013, 43(05): 1204 -1209 .
[7] YUAN Zhe, MA Wen-xing, LIU Chun-bao, LIU Hao. Temperature field analysis of the open-type hydrodynamic retarder of heavy vehicle[J]. 吉林大学学报(工学版), 2013, 43(05): 1271 -1275 .
[8] SUI Zhou, CAI Zhong-yi, LAN Ying-wu, LI Ming-zhe. Shape control model for three-dimensional surface part in continuous flexible forming process[J]. 吉林大学学报(工学版), 2013, 43(05): 1302 -1306 .
[9] YANG Xiao-jun, SONG Qing-song, MA Xiang, LI Dong-hai. Fault-tolerance target tracking based on multi-model information filtering[J]. 吉林大学学报(工学版), 2013, 43(05): 1381 -1385 .
[10] YANG Zhao-sheng, MO Xiang-lun, YU Yao, ZHANG Biao. Estimation of travel time under abnormal state[J]. 吉林大学学报(工学版), 2013, 43(06): 1459 -1464 .