Mathematics > Combinatorics
[Submitted on 24 Jun 2022]
Title:Existence of Optimally-Greatest Digraphs for Strongly Connected Node Reliability
View PDFAbstract:In this paper, we introduce a new model to study network reliability with node failures. This model, strongly connected node reliability, is the directed variant of node reliability and measures the probability that the operational vertices induce a subdigraph that is strongly connected. If we are restricted to directed graphs with $n$ vertices and $n+1\leq m\leq 2n-3$ or $m=2n$ arcs, an optimally-greatest digraph does not exist. Furthermore, we study optimally-greatest directed circulant graphs when the vertices operate with probability $p$ near zero and near one.
In particular, we show that the graph $\Gamma\left(\mathbb{Z}_n,\{1,-1\}\right)$ is optimally-greatest for values of $p$ near zero. Then, we determine that the graph $\Gamma\left(\mathbb{Z}_{n},\{1,\frac{n+2}{2}\}\right)$ is optimally-greatest for values of $p$ near one when $n$ is even. Next, we show that the graph $\Gamma\left(\mathbb{Z}_{n},\{1,2(3^{-1})\}\right)$ is optimally-greatest for values of $p$ near one when $n$ is odd and not divisible by three and that $\Gamma\left(\mathbb{Z}_{n},\{1,3(2^{-1})\}\right)$ is optimally-greatest for values of $p$ near one when $n$ is odd and divisible by three. We conclude with a discussion of open problems.
References & Citations
Bibliographic and Citation Tools
Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.