Effects of traffic generation patterns on the robustness of complex networks

Wu, Jiajing; Zeng, Junwen; Chen, Zhenhao; Tse, Chi K.; Chen, Bokui

doi:10.1016/j.physa.2017.11.016

Cited by 20 publications

(3 citation statements)

References 33 publications

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“…In this paper, we adopt the data traffic model [30] to model the communication network and the nodes in the communication network are considered as selfish ones [31,32]. In this model, new packets are generated randomly with source and destination nodes selected and then transmitted along the shortest paths.…”

Section: Communication Network Modelmentioning

confidence: 99%

Robustness Assessment of Cyber–Physical System with Different Interdependent Mechanisms

Wang

et al. 2023

Electronics

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Cyber–physical systems (CPSs) are a new generation of intelligent system that integrate communication, control and computation functions and are widely used in traditional infrastructure networks, such as power network, transportation network and others. In order to ensure the stable operation and improve the robustness of CPSs, the studies of robustness assessment have attracted much attention from academia. However, previous models assume that the failure propagation conforms to a strongly interdependent relationship, and only consider the interaction between nodes, while ignoring the interaction between nodes and links. In this paper, we develop a novel simulation model with the consideration of both the coupling modes and the failure propagation objects. Based on the simulation model, we study how the interdependent mechanisms, failure propagation probability and protection strategies affect the robustness of CPSs. The simulations of our proposed model are demonstrated in a test CPS formed by coupling two classical complex networks. Compared with previous models, our proposed model shows different performances and comprehensively characterizes the interdependent relationship of CPSs. In detail, disassortative coupling shows the worst performance and the CPS becomes more sensitive to failure propagation when Node–Link is selected as the failure propagation object. In addition, compared to the communication network, the power network is more sensitive to failure propagation. Protecting electrical nodes is a more effective way to strengthen the robustness of CPSs when conservation resources are limited. Our work provides useful advice to operators on how to effectively design and protect a CPS.

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Section: Communication Network Modelmentioning

confidence: 99%

Robustness Assessment of Cyber–Physical System with Different Interdependent Mechanisms

Wang

et al. 2023

Electronics

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“…Among studies of infrastructure systems, modes of transport have a particular interest since they are straightforwardly related to human mobility [6,7], spreading disease [8], shipping [9,10], etc. Besides that, in recent years there have been many studies investigating structural features of transport systems through the application of complex network theory [11,12,13,14,15,16,17], which in turn offers materials for related works mainly on dynamical processes occurring on these structures.…”

Section: Introductionmentioning

confidence: 99%

q-Weibull distributions describing commercial service routes

Ferreira¹,

Silva²

2020

Physica A: Statistical Mechanics and its Applications

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We present an investigation of the mode of road transport in Brazil combining tools of complex networks and real-data. Our analysis involves a data-set based on the service routes inscribed on the Brazilian Transport Agency database. Although connectivity distributions of road networks worldwide are usually claimed as described by a power-law fashion, we report a better fit for the Brazilian case offered by the q-Weibull distribution. In our approach nodes assume the role of localities, whereas links represent service routes among them. Interestingly, a rapid drop takes place on the tail of the data distribution for a particular range of the number of outgoing connections. The mechanism responsible for driving this drop is revealed by investigating the spectral centrality of the network and different patterns of disassortative mixture, for both incoming and outgoing distributions. Besides a discussion about a power law description, we report a contrast with two different distributions. They are interpolated by the q-Weibull one: the Weibull and the q-exponential distributions. Moreover, we study the reciprocity of this network, which reflects the influence of mutual links over dynamical processes. This kind of analysis is indispensable for studies on human mobility, shipping, and a multi-modal perspective.

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“…Introduction. Cascading failure is common in practical network [26,12], which involves power grid system [21,25], transportation system [20,31], communication network [32], etc. If some nodes in the network fail as impacted by attacks, the scale of failure will expand continuously via the interaction of coupling nodes; as a result, the network is partially or overall collapsed.…”

mentioning

confidence: 99%

Research on cascading failure modes and attack strategies of multimodal transport network

Guo¹,

Xu²,

He³

et al. 2022

JIMO

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Cascading failure overall exists in practical network, which poses a risk of causing significant losses. Studying the effect of different cascading failure modes and attack strategies of the network is conducive to more effectively controlling the network. In the present study, the uniqueness of multimodal transport network is investigated by complying with the percolation theory, and a cascading failure model is built for the multimodal transport network by considering recovery mechanisms and dynamics. Under the three failure modes, i.e., node failure, edge failure and node-edge failure, nine attack strategies are formulated, consisting of random node attacking strategy (RNAS), highdegree attacking strategy (HDAS), high-closeness attacking strategy (HCAS), random edge attacking strategy (REAS), high-importance attacking strategy (HIAS1), high-importance attacking strategy (HIAS2), random node-edge attacking strategy (RN-EAS), high degree-importance1 attacking strategy (HD-I1AS), as well as high closeness-importance2 attacking strategy (HC-I2AS). The effect of network cascading failure is measured at the scale of the affected network that varies with the failure ratio and the network connectivity varying with the step. By conducting a simulation analysis, the results of the two indicators are compared; it is suggested that under the three failure modes, the attack strategies exhibiting high node closeness as the indicator always poses more effective damage to the network. Next, a sensitivity analysis is conducted, and it is concluded that HCAS is the most effective attack strategy. Accordingly, the subsequent study on the cascading failure of multimodal transport network should start with the nodes exhibiting high closeness to optimize the network.

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Effects of traffic generation patterns on the robustness of complex networks

Cited by 20 publications

References 33 publications

Robustness Assessment of Cyber–Physical System with Different Interdependent Mechanisms

Robustness Assessment of Cyber–Physical System with Different Interdependent Mechanisms

q-Weibull distributions describing commercial service routes

Research on cascading failure modes and attack strategies of multimodal transport network

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