Building reliability-improving network transformations.
Resumen:
A fundamental problem in network reliability analysis is to find the connectedness probability of a random graph subject to perfect nodes and independent link failures with identical probabilities. This connectedness probability is called the all-terminal reliability, and its determination is a challenging problem. In this paper we study the corresponding network design problem: which is the best way to connect q links among p nodes in order to maximize the all-terminal reliability? The optimal solutions to this problem are called uniformly most-reliable graphs. To the best of our knowledge, the literature offers a single reliability-improving network transformation called swing surgery, credited to Kelmans. Here, we offer two novel reliability-improving transformations which, even simple, they help to improve the reliability in a uniform sense (i.e., under all feasible link failure probability). Supported by the previous transformations, we prove that Yutsis graph is uniformly most-reliable, which is currently a computationally prohibitive problem. Conjectures and open problems are also discussed.
| 2019 | |
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Computer network reliability Reliability engineering Peer-to-peer computing Surgery Reliability theory Communication networks Network Reliability Analysis Uniformly Most-Reliable Graphs Swing Surgery Yutsis Graph |
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| Inglés | |
| Universidad de la República | |
| COLIBRI | |
| https://hdl.handle.net/20.500.12008/49702 | |
| Acceso abierto | |
| Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |