面向级联失效的复杂网络动态增边策略

针对复杂网络级联失效现象,提出三种应对级联失效的动态增边策略,即随机增边策略、最大介数增边策略和最大剩余容量增边策略。基于级联失效的ML模型,从容忍参数、初始负荷参数和增边成本三方面对不同增边策略的效果进行仿真研究。仿真结果表明,在三种仿真网络中,最大剩余容量增边策略效果和成本在总体上优于其余两种增边策略;增边策略在随机网络中效果最稳定,在小世界网络中效果不稳定;在较低的容忍参数时,各增边策略的效果随初始负荷参数的改变而产生较大的波动。...

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Bibliographic Details
Published in计算机应用研究 Vol. 33; no. 8; pp. 2324 - 2327
Main Author 李从东 原智峰 邓原 王玉 曹策俊
Format Journal Article
LanguageChinese
Published 暨南大学 管理学院,广州,510632 2016
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ISSN1001-3695
DOI10.3969/j.issn.1001-3695.2016.08.019

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Summary:针对复杂网络级联失效现象,提出三种应对级联失效的动态增边策略,即随机增边策略、最大介数增边策略和最大剩余容量增边策略。基于级联失效的ML模型,从容忍参数、初始负荷参数和增边成本三方面对不同增边策略的效果进行仿真研究。仿真结果表明,在三种仿真网络中,最大剩余容量增边策略效果和成本在总体上优于其余两种增边策略;增边策略在随机网络中效果最稳定,在小世界网络中效果不稳定;在较低的容忍参数时,各增边策略的效果随初始负荷参数的改变而产生较大的波动。
Bibliography:51-1196/TP
compley network; cascading failure; adding link strategy
Li Congdong, Yuan Zhifengt, Deng Yuan, Wang Yu, Cao Cejun (School of Management, Jinan University, Guangzhou 510632, China)
In order to cope with the cascading failure in complex network, this paper put forward three adding link strategies: random adding strategy, maximum betweenness adding strategy, and maximum rest load adding strategy. Based on the ML cas- cading failure model, it tested these strategies by tolerance parameter, initial load parameter, adding link cost. The simulation experiments show that the maximum rest load adding strategy is better than the other two strategies in the effect and cost. In ad- dition, adding link strategies have stable effect in random network, while the effect of strategies is changeable in small word net- work. In the low level of tolerance parameter, the effect of adding link strategies is changeable.
ISSN:1001-3695
DOI:10.3969/j.issn.1001-3695.2016.08.019