A Novel Load Capacity Model with a Tunable Proportion of Load Redistribution against Cascading Failures

Zhang, Zhenghao; Song, Yurong; Xia, Lingling; Li, Yin-Wei; Zhang, Liang; Jiang, Guoping

doi:10.1155/2018/6254876

Cited by 8 publications

(3 citation statements)

References 27 publications

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“…Ji et al [25] analyzed the mechanism of fault cascading propagation in communication networks and proposed a fault prediction model based on the load capacity model. Zhang et al [26] proposed a novel load capacity model with a tunable proportion. Guo et al [27] proposed a development cascade fault model applied to complex network theory to simulate the disaster diffusion process in their project.…”

Section: Relevant Workmentioning

confidence: 99%

Reliability Analysis and Redundancy Optimization of a Command Post Phased-Mission System

Dui

Zhang

2022

Mathematics

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This paper divides the execution process of the command post system into four stages: information acquisition, information processing, decision control and response execution. It combines multilayer complex networks with a phased-mission system. Most studies have only evaluated the reliability of phased-mission systems. This paper evaluates and optimizes the reliability of a phased-mission system. In order to improve the mission success rate and maximize the reliability of a command post system, this paper provides a multitasking node criticality index, and the index is used to identify the key nodes in the command post’s four-stage network Then, the hot backup system of the node is selected to determine the redundant structure of the key node. Under the constraints of the operation and maintenance costs of key nodes, with the goal of maximizing the reliability of the information processing network layer, the multitask redundancy optimization model of each stage is established. Finally, the reliability of the missions before and after redundancy optimization is compared, using the case analysis of the four-layer network to verify the effectiveness of the proposed model.

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Section: Relevant Workmentioning

confidence: 99%

Reliability Analysis and Redundancy Optimization of a Command Post Phased-Mission System

Dui

Zhang

2022

Mathematics

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“…其中, h max 和 h min 分别表示在不同时刻不同节点的最大和最小节点负载. [28] 、负载容量模型 [29] 、线性阈值模型 [30] ) 均可模拟故障在网络中的传播过程, 进而分析故障的影响范围. 但由于轨道交通网络中受初始故障站点影响的其他站点依然具备运输乘客的能力, 这与负载容量模型 [31] 在故障扩散中保留故障节点部分功能的性质相符, 所以本文采用负载容量模型刻画轨道交通网络中的故障传播过程.…”

Section: 网络拓扑结构影响unclassified

A novel method to identify influential stations based on dynamic passenger flows

高超¹,

蒋世洪²,

王震³

et al. 2021

Sci. Sin.-Inf.

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“…Furthermore, due to the spatiotemporal characteristic of passenger flow in SN [19], the failure caused by the disrupted stations will diffuse to the global SN or at least to a large part of it [20]- [22], that is, the cascading failures occur in the SN [23], [24]. In order to explore the cascading failure caused by the passenger flow in SN, some cascading failure models (such as the load capacity model [25], coupled map lattice model [26] and linear threshold model [27], [28]) have been improved to simulate this cascading failure process. For example, both Ma et al and Shen et al have proposed an improved coupled map lattices model to analyze the cascading failure process of Xi'an SN [14] and Nanjing SN during a certain time period [15], respectively.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Robustness Analysis for Subway Network With Spatiotemporal Characteristic of Passenger Flow

et al. 2020

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The robustness is a crucial and essential problem of a subway network (SN), which can help us improve the efficiency of a transportation system. Several existing researches have analyzed the SN robustness based on the rail structure or the static distribution of passenger flow. However, the spatiotemporal characteristic of passenger flow also plays an important role in the SN robustness, since it can trigger some unexpected cascading failures in SN. Therefore, how to characterize the effect of this cascading failure on the SN robustness still remains an important and open problem. In this paper, we address the above problem as follows: (1) we propose a temporal subway network (TSN) to consider the dynamics of passenger flow in SN; (2) we adopt the linear threshold (LT) model to simulate the cascading failure process of TSN and propose a new robustness metric R(t) to evaluate the effect of this cascading failure on SN robustness. Based on the Shanghai subway smart card data, we carry out extensive experiments to analyze the effects of the cascading failure on the Shanghai SN robustness. Experiments show that the Shanghai TSN robustness varies over time. More significantly, the large volume of passenger flow can increase the impact of failure modes (i.e., random and malicious failure modes) on the Shanghai TSN robustness. INDEX TERMS Subway network, robustness, dynamic passenger flow, cascading failure.

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A Novel Load Capacity Model with a Tunable Proportion of Load Redistribution against Cascading Failures

Cited by 8 publications

References 27 publications

Reliability Analysis and Redundancy Optimization of a Command Post Phased-Mission System

Reliability Analysis and Redundancy Optimization of a Command Post Phased-Mission System

A novel method to identify influential stations based on dynamic passenger flows

Dynamic Robustness Analysis for Subway Network With Spatiotemporal Characteristic of Passenger Flow

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