• DocumentCode
    153846
  • Title

    Root Cause Analysis of Failures in Interdependent Power-Communication Networks

  • Author

    Das, Arun ; Banerjee, Joydeep ; Sen, Arunabha

  • Author_Institution
    Sch. of Comput., Inf. & Decision Syst. Eng., Arizona State Univ., Tempe, AZ, USA
  • fYear
    2014
  • fDate
    6-8 Oct. 2014
  • Firstpage
    910
  • Lastpage
    915
  • Abstract
    Studies on communication network robustness, though extensive, have primarily focused on standalone networks. However, real world communication networks do not operate in isolation, but instead are part of complex interdependent ecosystems that function together as a comprehensive symbiotic unit. For instance, communication networks of today are highly dependent on the power infrastructure and hence, any efforts to improve the robustness of communication networks must necessarily take into account the vulnerabilities of the power infrastructure and their shared interdependencies. For example, event-induced failures (failures caused by natural disasters or terrorist attacks), on any of these two infrastructures can trigger further failures (triggered failures) into the system through a cascading process due to the interdependencies between the networks. In such an interdependent system where an event induced failure can cascade and result in a much larger combined (event-induced plus triggered) failure, it may be imperative to identify the original event-induced failure for the purpose of post fault diagnostics, or for pre-cascade network strengthening. This ascertainment of event-induced original failure, or the Root Cause of Failure, from combined failures in interdependent Power-Communication networks is the main focus of this paper. We model interdependencies between the two infrastructures using the recently proposed Implicative Interdependency Model. We introduce the Root Cause of Failure problem, and prove it to be NP-Complete. We also provide optimal solutions using ILP, and provide an O(ln(n)) approximation algorithm. Finally, we validate our analytical results through experiments in the power communication network of Maricopa County, Arizona.
  • Keywords
    approximation theory; computational complexity; fault diagnosis; integer programming; linear programming; telecommunication network reliability; telecommunication networks; Arizona; ILP; Implicative Interdependency Model; Maricopa County; NP-complete problem; approximation algorithm; complex interdependent ecosystem; event-induced original failure ascertainment; integer linear programming; interdependent power-communication network; natural disaster; post-fault diagnostics; pre-cascade network strengthening; root cause failure analysis; terrorist attack; Approximation algorithms; Approximation methods; Communication networks; Computational modeling; Power system faults; Power system protection; Silicon;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Military Communications Conference (MILCOM), 2014 IEEE
  • Conference_Location
    Baltimore, MD
  • Type

    conf

  • DOI
    10.1109/MILCOM.2014.156
  • Filename
    6956877