一种基于力学模型的电力通信网脆弱性评估方法
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摘要
为了合理评价电力通信网链路的脆弱性,提出一种基于力学模型的电力通信网脆弱性评估方法,将业务在链路上来往所占用的带宽容量与节点间业务相互来往的数目统称为节点间的相关性,并将链路业务间的往来相关程度视为一种关联的广义业务力。在业务统计过程中采用均分时隙的最大似然估计,以泊松(Poisson)过程为统计背景进行对业务的参数估计。将链路间的业务数目以及占用带宽变化视为广义业务力做功,通过引力公式得到节点间的链路逻辑距离,并以逻辑距离变化区间来度量通信网络的脆弱性。最后,利用MATLAB建立模型进行仿真计算,验证了该方法能够实时、准确地分析以及评价电力通信网业务链路的脆弱性。
In order to reasonably evaluate the vulnerability of the power communication network link, a vulnerability assessment method based on the mechanical model was proposed. The bandwidth capacity occupied by the traffic on the link and the number of inter-node services were collectively referred to as nodes. The correlation between the links and the degree of correlation between the link services was regarded as an associated generalized business force. In the process of business statistics, the maximum likelihood estimation of the time-slotted time slot was adopted, and the parameters of the service were estimated by using the Poisson process as a statistical background. The number of services between links and the occupied bandwidth were regarded as work of generalized service. The logical distance of the links between nodes was obtained by the gravitational formula, and the vulnerability of the communication network was measured by the interval of logical distance. Finally, MATLAB was used to establish a model for simulation calculation, it is verified that the method can analyze and evaluate the vulnerability of the service link of the power communication network in real time and accurately.
In order to reasonably evaluate the vulnerability of the power communication network link, a vulnerability assessment method based on the mechanical model was proposed. The bandwidth capacity occupied by the traffic on the link and the number of inter-node services were collectively referred to as nodes. The correlation between the links and the degree of correlation between the link services was regarded as an associated generalized business force. In the process of business statistics, the maximum likelihood estimation of the time-slotted time slot was adopted, and the parameters of the service were estimated by using the Poisson process as a statistical background. The number of services between links and the occupied bandwidth were regarded as work of generalized service. The logical distance of the links between nodes was obtained by the gravitational formula, and the vulnerability of the communication network was measured by the interval of logical distance. Finally, MATLAB was used to establish a model for simulation calculation, it is verified that the method can analyze and evaluate the vulnerability of the service link of the power communication network in real time and accurately.
引文
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[2]李彬,张洁,陈宋宋,等.基于复杂网络的电力通信网扩容保护策[J].电网技术,2018,42(6):1974-1980.LI B,ZHANG J,CHEN S S,et al.Expansion strategy of power communication network survivability based on complex network[J].Power System Technology,2018,42(6):1974-1980.
[3]周静,刘国军.一种电力通信网规划成效评价方法[J].电信科学,2015,31(3):155-159,170.ZHOU J,LIU G J.An effective method to evaluate the planning achievements of electric power communication network[J].Telecommunications Science,2015,31(3):155-159,170.
[4]张益辉,苏汉,陈香宇,等.基于评价树的电力通信网络业务质量评价方法[J].电信科学,2017,33(Z1):57-62.ZHANG Y H,SU H,CHEN X Y,et al.Service quality evaluation method of power communication network based on evaluation tree[J].Telecommunications Science,2017,33(Z1):57-62.
[5]樊冰,曾瑛,唐良瑞.基于信息熵的电力通信网脆弱性评价方法[J].电子与信息学报,2014,36(9):2138-2144.FAN B,ZENG Y,TANG L R.Vulnerability assessment of power communication network based on information entropy[J].Journal of Electronics&Information Technology,2014,36(9):2138-2144.
[6]樊冰,唐良瑞.电力通信网脆弱性分析[J].中国电机工程学报,2014,34(7):1191-1197.FAN B,TANG L R.Vulnerability analysis of power communication network[J].Proceedings of the CSEE,2014,34(7):1191-1197.
[7]王秀娟,孙博,廖彦文,等.贝叶斯属性攻击图网络脆弱性评估[J].北京邮电大学学报,2015,38(4):106-112.WANG X J,SUN B,LIAO Y W,et al.Computer network vulnerability assessment based on bayesian attribute network[J].Journal of Beijing University of Posts and Telecommunications,2015,38(4):106-112.
[8]彭静,卢继平,汪洋,等.广域测量系统通信主干网的风险评估[J].中国电机工程学报,2010,30(5):84-90.PENG J,LU J P,WANG Y,et al.Risk assessment of backbone communication network in WAMS[J].Proceedings of the CSEE,2010,30(5):84-90.
[9]金鑫.电力通信传输网业务可靠性分析方法研究[D].保定:华北电力大学,2010:7-18.JIN X.Research on service reliability analysis method of electricpower communication transmission network[D].Baoding:North China Electric Power University,2010:7-18.
[10]李思.基于业务重要度的电力通信网可靠性评估[D].保定:华北电力大学,2010.LI S.The reliability evaluation of power communication networks based on service importance[D].Baoding:North China Electric Power University,2010.
[11]刘涤尘,冀星沛,王波,等.基于复杂网络理论的电力通信网拓扑脆弱性分析及对策[J].电网技术,2015(12):3615-3621.LIU D C,JI X P,WANG B,et al.Topological vulnerability analysis and countermeasures of electrical communication network based on complex network theory[J].Power System Technology,2015(12):3615-3621.
[12]刘秉正,彭建华.非线性动力学[M].北京:高等教育出版社,2013:140-141.LIU B Z,PENG J H.Nonlinear dynamics[M].Beijing:Higher Education Press,201:140-141.
[13]LU Z M,LI X F.Attack vulnerability of network controllability[J].PLoS ONE,2016.
[14]冯杭,王胜兵.有限混合泊松分布参数优化的改进EM算法[J].兵工自动化,2017,36(1):80-82.FENG H,WANG S B.Improved EM algorithm of limited mixed Poisson distribution parameters optimization[J].Ordnance Industry Automation,2017,36(1):80-82.