Reliability and importance measure analysis of networks with shared risk link groups. (July 2021)

• Record Type: Journal Article
• Authors: Vaisman, Radislav; Sun, Yuting
• Is Part Of: Reliability engineering & system safety. Volume 211(2021)
• Publication Date: 2021-07
• Subjects: Shared risk link groups -- Reliability -- Birnbaum importance measure -- Complex networks -- Optical communication; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2021.107578
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: We consider the problem of assessing the reliability and the Birnbaum importance measure of complex networks under the shared link risk group (SRLG) failure scenario. With a view to the fact that SRLG failures can cause a global system breakdown, the reliability and the importance measure analysis is of fundamental importance to the study of critical infrastructures such as sensor and cross-layer networks, supply chains, and other complex systems that support the essential functioning of our society and economy. The mathematical complexity of the reliability and the importance measure calculation implies that one has to rely on approximation techniques, since no analytical method for solving this problem in reasonable computation time is known to exist. This study will build upon the Permutation Monte Carlo paradigm. The major advantage of the proposed solution is that it allows us to obtain reliable estimates of both the network reliability and the Birnbaum importance measure using the same algorithmic machinery. We show that the suggested algorithm is easy to implement and that the method is scalable to meet real-life network sizes. Highlights: Complex networks with shared risk link groups. Reliability and Birnbaum importance measure analysis. Permutation Monte Carlo paradigm and efficiency analysis is considered. The same algorithm is used for reliability and importance measure analysis. A research software package that can handle real-life instances is provided.