Root Cause Analysis of Failures in Interdependent Power-Communication Networks

Das, Arun; Banerjee, Joydeep; Sen, Arunabha

doi:10.1109/milcom.2014.156

Cited by 34 publications

(14 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This module will support multi-layer interdependent network modeling utilizing IIM, and implement the techniques proposed for problems studied under the IIM setting, such as (i) identification of the K most vulnerable nodes [23], (ii) root cause analysis of failures [11], (iii) the entity hardening problem [2], (iv) the smallest pseudotarget set identification problem [13], (v) the robustness analysis problem [3], and (vi) progressive recovery from failure in multi-layer interdependent networks [18]. It may be noted that, as of writing this paper this module is currently under development and will be part of the tool upon its completion.…”

Section: Robust Multi-layer Interdependent Network Design Modulementioning

confidence: 99%

Raptor: a network tool for mitigating the impact of spatially correlated failures in infrastructure networks

et al. 2017

Self Cite

View full text Add to dashboard Cite

Current practices of fault-tolerant network design ignore the fact that most network infrastructure faults are localized or spatially correlated (i.e., confined to geographic regions). Network operators require new tools to mitigate the impact of such region based faults on their infrastructures. Utilizing the support from the U.S. Department of Defense, and by consolidating a wide range of theories and solutions developed in the last few years, the authors of this paper have developed RAPTOR, an advanced Network Planning and Management Tool that facilitates the design and provisioning of robust and resilient networks. The tool provides multi-faceted network design, evaluation and simulation capabilities for network planners. Future extensions of the tool currently being worked upon not only expand the tool's capabilities, but also extend these capabilities to heterogeneous interdependent networks such as communication, power, water and satellite networks.

show abstract

Section: Robust Multi-layer Interdependent Network Design Modulementioning

confidence: 99%

Raptor: a network tool for mitigating the impact of spatially correlated failures in infrastructure networks

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…To overcome the limitations of existing models, the authors of [18] have proposed an Implicative Interdependency Model that is able to capture such complex interdependency. Utilizing this model, several problems on multi-layer interdependent networks have been studied, such as (i) identification of the K most vulnerable nodes [18], (ii) root cause analysis of failures [19], (iii) the entity hardening problem [20], (iv) the smallest pseudo-target set identification problem [21], and (v) the robustness analysis problem [22]. This module will support multi-layer network interdependency modeling using the Implicative Interdependency Model, and analysis of multi-layer networks using the techniques proposed in [18][19][20][21][22].…”

Section: E Robust Multi-layer Interdependent Network Design Modulementioning

confidence: 99%

A Network Planning and Management Tool for mitigating the impact of spatially correlated failures in infrastructure networks

Das

Sen

Qiao

et al. 2016

2016 12th International Conference on the Design of Reliable Communication Networks (DRCN)

Self Cite

View full text Add to dashboard Cite

Current practices of fault-tolerant network design ignore the fact that most network infrastructure faults are localized or spatially correlated (i.e., confined to regions). Network operators require new tools to mitigate the impact of such region based faults on their infrastructures. Utilizing the support from the U.S. Department of Defense, and by consolidating a wide range of theories and solutions developed in the last few years, the authors of this paper have developed an advanced Network Planning and Management Tool (NPMT) that facilitates the design and provisioning of robust and resilient networks. The tool provides multi-faceted network design, evaluation and simulation capabilities for network planners. Future extensions of the tool currently being worked upon not only expand the tools capabilities, but also extend these capabilities to heterogeneous interdependent networks such as communication, power, water and satellite networks.

show abstract

“…The interdependency between CIs can be modeled, and such models must be complex enough and contain sufficient detail and accuracy (Svendsen & Wolthusen, ). The issue of identifying interdependent critical components has been studied for other infrastructure systems (e.g., power grid, communication, and gas; Das et al, ; Kocarev et al, ; Rahnamay‐Naeini & Hayat, ). Rahnamay‐Naeini and Hayat () construct a logical network model of a power grid and assume that the topology of that network model is deterministic, but they represent cascading failures with probability distributions to account for interdependency between electric grids and communication networks.…”

Section: Introductionmentioning

confidence: 99%

An Exact Multiobjective Optimization Approach for Evaluating Water Distribution Infrastructure Criticality and Geospatial Interdependence

Abdel-Mottaleb

Saghand

Charkhgard

et al. 2019

Water Resources Research

View full text Add to dashboard Cite

Failures within water distribution systems are usually not isolated and tend to propagate to corresponding transportation infrastructure, yet most criticality and resilience analyses of water distribution networks are conducted for the individual water infrastructure without accounting for interdependence. To address this research gap, this study investigates how the critical components identified within water distribution systems may be different when accounting for failure propagation to the transportation road network. In this study, failure propagation is assumed to be based on geospatial interdependence and unidirectional, starting from water distribution network components to transportation network components. A logical interaction network is constructed considering the interdependence between both infrastructures, and multiobjective optimization is used to solve for the critical water distribution components considering: quantity of failures, performance loss, and financial costs. This work presents a modular workflow for water distribution criticality analysis and proposes the Kolmogorov‐Smirnov distance statistic between solution sets as a measure of the significance of interdependency for decision making. Results from the case study suggest that as the magnitude of water infrastructure failure increases beyond a threshold, the interdependency between water distribution and transportation becomes more significant. The difference between identified critical components using only information from water distribution and using both water distribution and transportation is significantly different (with greater than 95% confidence) for the city of Tampa, when more than 40 components fail (are isolated). These results will assist utilities in asset management and strategy assessment, by helping prioritize component repair and better allocate resources for critical interdependent infrastructures.

show abstract

Root Cause Analysis of Failures in Interdependent Power-Communication Networks

Cited by 34 publications

References 13 publications

Raptor: a network tool for mitigating the impact of spatially correlated failures in infrastructure networks

Raptor: a network tool for mitigating the impact of spatially correlated failures in infrastructure networks

A Network Planning and Management Tool for mitigating the impact of spatially correlated failures in infrastructure networks

An Exact Multiobjective Optimization Approach for Evaluating Water Distribution Infrastructure Criticality and Geospatial Interdependence

Contact Info

Product

Resources

About