TY - GEN
T1 - Resilience analytics of networks with dependency groups
AU - Bai, Yanan
AU - Huang, Ning
AU - Xu, Kan
AU - Zhang, Xin
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - Dependency property that binds the failure of some network components to the failure of other network components reduces network robustness, the absorptive capacity of network, while the recovery scheme can improve the restorative capacity. However, the effect of both dependency property and recovery scheme on network resilience is seldom addressed. In this paper, we introduce a dependency strength function which describe the way of evolution of dependency strength and select the common spontaneous recovery scheme for networks with dependency groups. Then, based on resilience framework, we investigate the effect of dependency strength and spontaneous recovery probability on network resilience by simulation. Numerical simulations employing the Erd's-Rényi networks show that the dependency strength has little impact on network resilience, and spontaneous recovery probability has a positive correlation with the network resilience. With the increase of time period T, the role of recovery probability in network resilience becomes smaller and smaller. Furthermore, improving the spontaneous recovery probability and the convexity of function of dependency strength significantly reduce the number of iterations of network back to normal operation under low recovery probability.
AB - Dependency property that binds the failure of some network components to the failure of other network components reduces network robustness, the absorptive capacity of network, while the recovery scheme can improve the restorative capacity. However, the effect of both dependency property and recovery scheme on network resilience is seldom addressed. In this paper, we introduce a dependency strength function which describe the way of evolution of dependency strength and select the common spontaneous recovery scheme for networks with dependency groups. Then, based on resilience framework, we investigate the effect of dependency strength and spontaneous recovery probability on network resilience by simulation. Numerical simulations employing the Erd's-Rényi networks show that the dependency strength has little impact on network resilience, and spontaneous recovery probability has a positive correlation with the network resilience. With the increase of time period T, the role of recovery probability in network resilience becomes smaller and smaller. Furthermore, improving the spontaneous recovery probability and the convexity of function of dependency strength significantly reduce the number of iterations of network back to normal operation under low recovery probability.
KW - dependency groups
KW - failure process
KW - network resilience
KW - recovery process
UR - https://www.scopus.com/pages/publications/85046664693
U2 - 10.1109/ICSRS.2017.8272870
DO - 10.1109/ICSRS.2017.8272870
M3 - 会议稿件
AN - SCOPUS:85046664693
T3 - 2017 2nd International Conference on System Reliability and Safety, ICSRS 2017
SP - 486
EP - 490
BT - 2017 2nd International Conference on System Reliability and Safety, ICSRS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on System Reliability and Safety, ICSRS 2017
Y2 - 20 December 2017 through 22 December 2017
ER -