Edge-Disjoint Branchings in Temporal Graphs
February 28, 2020 · Declared Dead · 🏛 International Workshop on Combinatorial Algorithms
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Victor Campos, Raul Lopes, Andrea Marino, Ana Silva
arXiv ID
2002.12694
Category
cs.DS: Data Structures & Algorithms
Citations
7
Venue
International Workshop on Combinatorial Algorithms
Last Checked
4 months ago
Abstract
A temporal digraph ${\cal G}$ is a triple $(G, γ, λ)$ where $G$ is a digraph, $γ$ is a function on $V(G)$ that tells us the timestamps when a vertex is active, and $λ$ is a function on $E(G)$ that tells for each $uv \in E(G)$ when $u$ and $v$ are linked. Given a static digraph $G$, and a subset $R\subseteq V(G)$, a spanning branching with root $R$ is a subdigraph of $G$ that has exactly one path from $R$ to each $v\in V(G)$. In this paper, we consider the temporal version of Edmonds' classical result about the problem of finding $k$ edge-disjoint spanning branchings respectively rooted at given $R_1,\cdots,R_k$. We introduce and investigate different definitions of spanning branchings, and of edge-disjointness in the context of temporal graphs. A branching ${\cal B}$ is vertex-spanning if the root is able to reach each vertex $v$ of $G$ at some time where $v$ is active, while it is temporal-spanning if $v$ can be reached from the root at every time where $v$ is active. On the other hand, two branchings ${\cal B}_1$ and ${\cal B}_2$ are edge-disjoint if they do not use the same edge of $G$, and are temporal-edge-disjoint if they can use the same edge of $G$ but at different times. This lead us to four definitions of disjoint spanning branchings and we prove that, unlike the static case, only one of these can be computed in polynomial time, namely the temporal-edge-disjoint temporal-spanning branchings problem, while the other versions are $\mathsf{NP}$-complete, even under very strict assumptions.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
📜 Similar Papers
In the same crypt — Data Structures & Algorithms
📚
📚
The Cartographer
R.I.P.
👻
Ghosted
Route Planning in Transportation Networks
R.I.P.
👻
Ghosted
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
R.I.P.
👻
Ghosted
Hierarchical Clustering: Objective Functions and Algorithms
R.I.P.
👻
Ghosted
Graph Isomorphism in Quasipolynomial Time
📚
📚
The Cartographer
Simulation optimization: A review of algorithms and applications
Died the same way — 👻 Ghosted
R.I.P.
👻
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
👻
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
👻
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
👻
Ghosted