{Linear Kernels for kk-Tupel and Liar's Domination in Bounded Genus Graphs}

A set $D\subseteq V$ is called a $k$-tuple dominating set of a graph $G=(V,E)$ if $\left| N_G[v] \cap D \right| \geq k$ for all $v \in V$, where $N_G[v]$ denotes the closed neighborhood of $v$. A set $D \subseteq V$ is called a liar's dominating set of a graph $G=(V,E)$ if (i) $\left| N_G[v] \cap D \right| \geq 2$ for all $v\in V$ and (ii) for every pair of distinct vertices $u, v\in V$, $\left| (N_G[u] \cup N_G[v]) \cap D \right| \geq 3$. Given a graph $G$, the decision versions of $k$-Tuple Domination Problem and the Liar's Domination Problem are to check whether there exists a $k$-tuple dominating set and a liar's dominating set of $G$ of a given cardinality, respectively. These two problems are known to be NP-complete \cite{LiaoChang2003, Slater2009}. In this paper, we study the parameterized complexity of these problems. We show that the $k$-Tuple Domination Problem and the Liar's Domination Problem are $\mathsf{W}[2]$-hard for general graphs but they admit linear kernels for graphs with bounded genus.Title changed from "Parameterized complexity of k-tuple and liar's domination" to "Linear kernels for k-tuple and liar's domination in bounded genus graphs

Parameterized algorithms of fundamental NP-hard problems: a survey

Parameterized computation theory has developed rapidly over the last two decades. In theoretical computer science, it has attracted considerable attention for its theoretical value and significant guidance in many practical applications. We give an overview on parameterized algorithms for some fundamental NP-hard problems, including MaxSAT, Maximum Internal Spanning Trees, Maximum Internal Out-Branching, Planar (Connected) Dominating Set, Feedback Vertex Set, Hyperplane Cover, Vertex Cover, Packing and Matching problems. All of these problems have been widely applied in various areas, such as Internet of Things, Wireless Sensor Networks, Artificial Intelligence, Bioinformatics, Big Data, and so on. In this paper, we are focused on the algorithms’ main idea and algorithmic techniques, and omit the details of them

A refined search tree technique for Dominating Set on planar graphs

We establish a refined search tree technique for the parameterized DOMINATING SET problem on planar graphs. Here, we are given an undirected graph and we ask for a set of at most k vertices such that every other vertex has at least one neighbor in this set. We describe algorithms with running times O(8kn) and O(8kk+n3), where n is the number of vertices in the graph, based on bounded search trees. We describe a set of polynomial time data-reduction rules for a more general "annotated" problem on black/white graphs that asks for a set of k vertices (black or white) that dominate all the black vertices. An intricate argument based on the Euler formula then establishes an efficient branching strategy for reduced inputs to this problem. In addition, we give a family examples showing that the bound of the branching theorem is optimal with respect to our reduction rules. Our final search tree algorithm is easy to implement; its analysis, however, is involved

Uma introdução à complexidade computacional parametrizada

Orientador : Prof. Dr. Renato CarmoDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa: Curitiba, 18/12/2013Inclui referências : f. 86-90Resumo: A Complexidade Parametrizada é uma maneira de analisar a complexidade computacional de um problema computacional. Nesta dissertação damos uma Introdução à Complexidade Computacional Parametrizada com atenção aos problemas computacionais em grafos, concluindo com uma aplicação ao Problema da Clique Máxima. Palavras-chave: Complexidade Parametrizada, Complexidade Computacional, Problema da Clique Máxima.Abstract: The Parameterized Complexity is a form of analizing the computational complexity of a computacional problem. In this dissertation we give a Introduction to Computational Parameterized Complexity with atention to computational problems in graphs, concluding with an aplication to Maximum Clique Problem. Key-words: Parameterized Complexity, Computational Complexity, Maximum Clique Problem