On the Distance Between the Rumor Source and Its Optimal Estimate in a Regular Tree

01/10/2019
by   Tetsunao Matsuta, et al.
0

This paper addresses the rumor source identification problem, where the goal is to find the origin node of a rumor in a network among a given set of nodes with the rumor. In this paper, we focus on a network represented by a regular tree which does not have any cycle and in which all nodes have the same number of edges connected to a node. For this network, we clarify that, with quite high probability, the origin node is within the distance 3 from the node selected by the optimal estimator, where the distance is the number of edges of the unique path connecting two nodes. This is clarified by the probability distribution of the distance between the origin and the selected node.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

01/10/2019

On the Distance Between the Rumor Source and Its Optimal Estimate on a Regular Tree

This paper addresses the rumor source identification problem, where the ...
11/12/2021

The Distance Distribution between Mobile Node and Reference Node in Regular Hexagon

This paper presents a new method to obtain the distance distribution bet...
09/04/2012

Synthesis of Stochastic Flow Networks

A stochastic flow network is a directed graph with incoming edges (input...
05/01/2021

Theoretical Analysis for Determining Geographical Route of Cable Network with Various Disaster-Endurance Levels

This paper theoretically analyzes cable network disconnection due to ran...
06/02/2017

Learning causal Bayes networks using interventional path queries in polynomial time and sample complexity

Causal discovery from empirical data is a fundamental problem in many sc...
03/20/2021

Distance Assisted Recursive Testing

In many applications, a large number of features are collected with the ...
04/10/2018

Universal features of mountain ridge patterns on Earth

We study structure of the mountain ridge systems based on the empirical ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.