Literature DB >> 23368505

Network observability transitions.

Yang Yang1, Jianhui Wang, Adilson E Motter.   

Abstract

In the modeling, monitoring, and control of complex networks, a fundamental problem concerns the comprehensive determination of the state of the system from limited measurements. Using power grids as example networks, we show that this problem leads to a new type of percolation transition, here termed a network observability transition, which we solve analytically for the configuration model. We also demonstrate a dual role of the network's community structure, which both facilitates optimal measurement placement and renders the networks substantially more sensitive to "observability attacks." Aside from their immediate implications for the development of smart grids, these results provide insights into decentralized biological, social, and technological networks.

Year:  2012        PMID: 23368505     DOI: 10.1103/PhysRevLett.109.258701

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  8 in total

1.  Networkcontrology.

Authors:  Adilson E Motter
Journal:  Chaos       Date:  2015-09       Impact factor: 3.642

2.  Discovering independent parameters in complex dynamical systems.

Authors:  Claudia Lainscsek; Jonathan Weyhenmeyer; Terrence J Sejnowski; Christophe Letellier
Journal:  Chaos Solitons Fractals       Date:  2015-07       Impact factor: 5.944

3.  Building damage-resilient dominating sets in complex networks against random and targeted attacks.

Authors:  F Molnár; N Derzsy; B K Szymanski; G Korniss
Journal:  Sci Rep       Date:  2015-02-09       Impact factor: 4.379

4.  Observability Transitions in Networks with Betweenness Preference.

Authors:  Yang Shunkun; Yang Qian; Xu Xiaoyun; Lu Dan; Li Daqing
Journal:  PLoS One       Date:  2016-06-14       Impact factor: 3.240

5.  A symbolic network-based nonlinear theory for dynamical systems observability.

Authors:  Christophe Letellier; Irene Sendiña-Nadal; Ezequiel Bianco-Martinez; Murilo S Baptista
Journal:  Sci Rep       Date:  2018-02-28       Impact factor: 4.379

6.  Distinguishing cell phenotype using cell epigenotype.

Authors:  Thomas P Wytock; Adilson E Motter
Journal:  Sci Adv       Date:  2020-03-18       Impact factor: 14.957

7.  Dominating scale-free networks using generalized probabilistic methods.

Authors:  F Molnár; N Derzsy; É Czabarka; L Székely; B K Szymanski; G Korniss
Journal:  Sci Rep       Date:  2014-09-09       Impact factor: 4.379

8.  Resilience of and recovery strategies for weighted networks.

Authors:  Xing Pan; Huixiong Wang
Journal:  PLoS One       Date:  2018-09-11       Impact factor: 3.240

  8 in total

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