Elsevier

Information Processing Letters

Volume 142, February 2019, Pages 30-34
Information Processing Letters

A dichotomy for weighted efficient dominating sets with bounded degree vertices

https://doi.org/10.1016/j.ipl.2018.10.007Get rights and content

Highlights

  • An efficient dominating set (e.d.s.) in a graph G is a set of vertices the closed neighborhoods of which partition V(G).

  • An e.d.s. is said to be k-bounded if it only consists of vertices of degree at most k in G.

  • The k-Bounded Weighted Efficient Domination (k-BWED) problem asks for a minimum-weight k-bounded e.d.s. in a given graph.

  • A dichotomy for k-BWED is obtained: the problem is NP-hard for k3 and solvable in polynomial time for k2.

Abstract

In a finite undirected graph G, a vertex v dominates itself and its neighbors. A vertex set D is an efficient dominating set (e.d.s. for short) of G if every vertex of G is dominated by exactly one vertex of D. The Efficient Domination (ED) problem, which asks for the existence of an e.d.s. in G, is well known to be NP-complete for graphs of maximum degree 3. We say that an e.d.s. D of G is k-bounded (k-b.e.d.s. for short) if the degree of every vertex in D is at most k in G. The task of the k-Bounded Weighted Efficient Domination (k-BWED) problem is to determine whether a given vertex-weighted graph G admits a k-b.e.d.s., and if so, to compute one of minimum weight. It easily follows from the NP-completeness of ED for graphs of maximum degree 3 that the k-BWED problem is NP-complete for every k3, and clearly, the k-BWED problem is solvable in linear time for k1. In this note, we show that the 2-BWED problem is solvable in time O(|V(G)|(|V(G)|+|E(G)|)), thus obtaining a dichotomy of the complexity status of k-BWED over all k0.

Introduction

Throughout this note, let G=(V,E) be a finite nontrivial undirected graph and let |V|=n and |E|=m. A vertex v dominates itself and its neighbors. A vertex subset DV is an efficient dominating set (e.d.s. for short) of G if every vertex of G is dominated by exactly one vertex in D. Obviously, D is an e.d.s. of G if and only if the family of all closed neighborhoods of vertices in D forms a partition of V. Note that not every graph has an e.d.s.; the Efficient Dominating Set (ED) problem asks for the existence of an e.d.s. in a given graph G.

In [1], [2], it was shown that the ED problem is NP-complete, and it is well known that ED remains NP-complete for various graph classes while it is solvable in polynomial time on various other classes; for a list of such examples, see, e.g., [4], [5], [6].

The notion of efficient domination was introduced by Biggs [3] under the name perfect code; in [15], it is remarked that efficient dominating sets correspond to perfect 1-codes. Efficient dominating sets are also called independent perfect dominating sets in various papers – see, e.g., [7], [19] – and perfect dominating sets in [8].

The following is the weighted version of the ED problem:

The WED problem is motivated by various applications, including coding theory and resource allocation in parallel computer networks; see, e.g., [1], [2], [3], [7], [12], [13], [14], [16], [17], [18], [19]. The importance of the (W)ED problem for graphs is partly due also to the fact that ED for a graph G is a special case of the Exact Cover problem for hypergraphs (problem [SP2] of [9]); for a given hypergraph H=(V,E), the question is whether there is a subset EE such that E is a partition of V. Actually, the Exact Cover problem is NP-complete for hypergraphs all of whose hyperedges have size 3 as shown by Karp in [10] (called X3C in [9]). Clearly, ED is the Exact Cover problem for the closed neighborhood hypergraph of G.

In this note, we consider the following variant of the WED problem: For graph G=(V,E) and for vV, let d(v) denote the degree of v in G. For a non-negative integer k, we say that an e.d.s. D in G is k-bounded if for every vertex vD, d(v)k. For short, a k-bounded e.d.s. will also be referred to as a k-b.e.d.s. The task of the k-Bounded Weighted Efficient Domination (k-BWED) problem is to determine whether a given vertex-weighted graph G admits a k-b.e.d.s., and if so, to compute one of minimum weight.

Clearly, a graph G admits a 0-b.e.d.s. if and only if it is edgeless. It is also straightforward to see that G admits a 1-b.e.d.s. if and only if each connected component of G is either K1, K2, or the vertices of degree 1 in the component form an e.d.s. of the component. Therefore, the k-BWED problem is solvable in linear time for k{0,1}. On the other hand, since the ED problem is NP-complete for graphs of maximum degree 3 [8], [11], the k-BWED problem is NP-complete for every k3.

In the rest of this note, we will show that, in contrast to X3C, the 2-BWED problem can be solved in polynomial time, thus obtaining a dichotomy of the complexity status of the k-BWED problem for every value of k. This result was already mentioned in the extended abstract [6] (without proof) and in the corresponding arXiv version (without algorithm and time bound).

We will use the following notation. For a graph G=(V,E) and a vertex vV, let N(v)={uV:uvE} denote its (open) neighborhood, and let N[v]={v}N(v) denote its closed neighborhood. For a subset UV, we denote by G[U] the subgraph of G induced by U. The degree of a vertex v in G is d(v):=|N(v)|. Let Pk denote a chordless path with k vertices, say x1,,xk and edges xixi+1, 1ik1. Clearly, a P2 in G is an edge of G. An induced matching in G is a set of edges (i.e., P2's) with pairwise distance at least 2.

Section snippets

Solving the 2-bounded WED problem

A 2-b.e.d.s. of a vertex-weighted graph G is said to be finite if it is of finite total weight. With this terminology, the 2-BWED problem can be formally stated as follows:

In what follows, we describe an algorithmic approach for the 2-BWED problem which will show that the problem is solvable in polynomial time. First, we reduce in a sequence of steps the input graph to equivalent smaller ones. This is done in Section 2.1. Second, we show that once all the reductions are performed, the graph has

The algorithm

Now we summarize the previous reduction steps and the construction of the multigraph H.

Algorithm 2-BWED:

Input: A graph G=(V,E) with vertex weights ω:VN{}.

Output: A 2-bounded e.d.s. D of G of minimum finite total weight if such a set exists, ‘no’, otherwise.

  • (a)

    Determine the degrees d(v) of all vertices vV. Let X:={v:d(v)2 and ω(v)<} and Y:=VX. Set ω(y)= for all yY. Delete all edges in G between vertices of Y. (This is justified by Claim 1.) If there is an isolated vertex yY, then return no

Acknowledgements

The authors are grateful to the anonymous reviewers for their helpful comments. The work of M.M. is supported in part by the Slovenian Research Agency (I0-0035, research program P1-0285, and research projects N1-0032, J1-7051, and J1-9110).

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