SearcharxivSearch

arXiv · 2412.03024

Broadcast Graph Is NP-complete

Abstract

The broadcast model is widely used to describe the process of information dissemination from a single node to all nodes within an interconnected network. In this model, a graph represents the network, where vertices correspond to nodes and edges to communication links. The efficiency of this broadcasting process is evaluated by the broadcast time, the minimum discrete time units required to broadcast from a given vertex. Determining the broadcast time is referred to as the problem Broadcast Time. The set of vertices with the minimum broadcast time among the graph is called the broadcast center. Identifying this center or determining its size are both proven to be NP-hard. For a graph with n vertices, the minimum broadcast time is at least ceil(log2 n). The Broadcast Graph problem asks in a graph of n vertices, whether the broadcast time from any vertex equals ceil(log2 n). Extensive research over the past 50 years has focused on constructing broadcast graphs, which are optimal network topologies for one-to-all communication efficiency. However, the computational complexity of the Broadcast Graph problem has rarely been the subject of study. We believe that the difficulty lies in the mapping reduction for an NP-completeness proof. Consequently, we must construct broadcast graphs for yes-instances and non-broadcast graphs for no-instances. The most closely related result is the NP-completeness of Broadcast Time proved by Slater et al. in 1981. More recently, Fomin et al. has proved that Broadcast Time is fixed-parameter tractable. In this paper, we prove that Broadcast Graph is NP-complete by proving a reduction from Broadcast Time. We also improve the results on the complexity of the broadcast center problem. We show Broadcast Center Size is in delta^2_p, and is DP-hard, implying a complexity upper bound of delta^2_p-complete and a lower bound of DP-hard.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Jinghan Xu, Zhiyuan Li. 2024-12-04. Broadcast Graph Is NP-complete. https://arxiv.org/abs/2412.03024

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

An FPTAS for Two-Machine Open-Shop Scheduling with a Single Unavailability Interval

We consider the two-machine open-shop scheduling problem in which one machine is unavailable during a fixed interval. We study the resumable setting: an operation interrupted by the unavailability interval may resume, without penalty, when the machine becomes available. The objective is to minimize the makespan. Although the problem is NP-hard and several approximation algorithms are known, whether it admits a fully polynomial-time approximation scheme (FPTAS) has remained open for two decades. We resolve this question affirmatively by giving the first FPTAS, thereby strengthening the previously known polynomial-time approximation scheme (PTAS). As an intermediate result, we develop a new pseudo-polynomial dynamic program with seven state dimensions, improving on the ten-dimensional formulation in the literature.

cs.DM

Generalized Graph Search Trees

Graph search algorithms and their corresponding graph search trees are commonly used in algorithmic graph theory. In recent years, the recognition problem of these graph search trees has received significant attention. So far, the research has focused on two types of search trees: first-in trees that behave like BFS-trees and last-in trees that behave like DFS-trees. The search tree paradigms differ from each other by the parent a vertex is connected to. In first-in trees, it is the first visited neighbor, while in last-in trees it is the last neighbor visited before that vertex. Here, we will generalize these concepts of graph search trees by allowing every preceding neighbor of a vertex to be the parent. We study the complexity of the recognition problem of these generalized graph search trees. We present NP-completeness proofs for most searches. We also show that the problem is trivial for Generic Search and polynomial-time solvable for several searches on bipartite graphs and chordal graphs. We also study the question how fixing the start vertex influences the complexity of the problem.

cs.DM

The exact asymptotic constant in the metric dimension of Jaccard space

Let $X$ be a finite set with $|X|=n$ and let $\mathrm{Jac}(a,b)=|a\,\triangle\, b|/|a\cup b|$ be the Jaccard distance on the power set $2^X$. Lladser and Paradise recently proved that the metric dimension of $(2^X,\mathrm{Jac})$ is $\Theta(n/\ln n)$, with the constant left open; their bounds are $(\ln 2)\,n/\ln n\lesssim \beta(2^X,\mathrm{Jac})\lesssim 2\ln(2e)\,n/\ln n$. We determine the constant: \[ \beta(2^X,\mathrm{Jac})=\frac{2n}{\log_2 n}\,(1+o(1))=(2\ln 2)\,\frac{n}{\ln n}\,(1+o(1)). \] The proof identifies the problem, on each ``slice'' of subsets of fixed cardinality, with the Erd\H{o}s--R\'enyi coin-weighing problem for a spring scale (the problem of \emph{detecting matrices}). The lower bound is the Erd\H{o}s--R\'enyi entropy argument applied to the middle slice; the upper bound follows from the explicit detecting families of Lindstr\"om and of Cantor and Mills, augmented by a single extra landmark that reveals cardinality.

cs.DM