In an increasingly interconnected and distributed world, the ability to ensure communications becomes pivotal in day-to-day operations. Given a network whose edges are prone to failures and disruptions, reliability captures the probability that traffic will reach a target location by traversing edges starting from a given source. This paper investigates reliability in decentralized and complex networks. To evaluate reliability, we introduce a multi-agent method that involves pathfinding agents to reduce the graph. Performance of this method is tested on scale-free and small-world networks as well as real-world spatial networks. We also investigate reliability score which aims to rank the capability of nodes in terms of traffic dissemination traffic across all nodes. Analysis over spatial networks indicates that the reliability score correlates with central and sub-central regions in a geographical region.
CITATION STYLE
Mar, J., Liu, J., Tang, Y., Chen, W., & Sun, T. (2018). Evaluating and analyzing reliability over decentralized and complex networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10939 LNAI, pp. 740–751). Springer Verlag. https://doi.org/10.1007/978-3-319-93040-4_58
Mendeley helps you to discover research relevant for your work.