Abstract 1 Introduction 2 The General Strategy 3 A Better Algorithm: Proof of Theorem 1 4 An Application in Graph Drawing 5 Conclusions References

Connected Dominating Sets in Triangulations

Prosenjit Bose ORCID School of Computer Science, Carleton University, Ottawa, Canada    Vida Dujmović ORCID School of Computer Science and Electrical Engineering, University of Ottawa, Canada    Hussein Houdrouge ORCID School of Computer Science, Carleton University, Ottawa, Canada    Pat Morin ORCID School of Computer Science, Carleton University, Ottawa, Canada    Saeed Odak ORCID Department of Computer Science, Aalto University, Espoo, Finland
Abstract

A dominating set of a graph G is connected if it induces a connected graph in G. For planar triangulations, it has been known since 1990 that every n-vertex triangulation admits a connected dominating set of size at most n/21, and no improvement to this bound was known for over three decades. We break this longstanding barrier by showing that every n-vertex triangulation has a connected dominating set of size at most 10n/21. Equivalently, every triangulation admits a spanning tree with at least 11n/21 leaves. Moreover, we present an algorithm that computes such a set in optimal linear time. Our result narrows the gap to the best known lower bound and has graph drawing applications, establishing a bound for one-bend free sets and improving the known bound for simultaneous planar embeddings.

Keywords and phrases:
connected domination, triangulations, planar graphs, graph drawing, collinear sets
Category:
Track A: Algorithms, Complexity and Games
Funding:
Prosenjit Bose: Research partially funded by NSERC.
Vida Dujmović: Research partially funded by NSERC and a University of Ottawa Research Chair.
Hussein Houdrouge: Research partially funded by NSERC.
Pat Morin: Research partially funded by NSERC.
Copyright and License:
[Uncaptioned image] © Prosenjit Bose, Vida Dujmović, Hussein Houdrouge, Pat Morin, and Saeed Odak; licensed under Creative Commons License CC-BY 4.0
2012 ACM Subject Classification:
Human-centered computing Graph drawings
; Theory of computation Computational geometry ; Mathematics of computing Graph algorithms
Related Version:
Full Version: https://doi.org/10.48550/arXiv.2312.03399
Editors:
Sayan Bhattacharya, Danupon Nanongkai, Michael Benedikt, and Gabriele Puppis

1 Introduction

A set X of vertices in a graph G is a dominating set of G if each vertex of G is in X or adjacent to a vertex in X.111Any graph G that we consider in this paper is a finite undirected graph without self-loops and without parallel edges, with vertex set V(G) and edge set E(G). A dominating set X of G is connected if the subgraph G[X] of G induced by the vertices in X is connected. There is an enormous body of literature on dominating sets. Several books are devoted to the topic [24, 23, 14, 22], including a book and book chapter devoted to connected dominating sets [14],[24, Chapter 4]. Connected dominating sets have numerous applications, particularly in areas such as wireless ad hoc networks, as well as broadcasting and multi-casting; see, for example [32].

A typical result in the area is an upper bound of the form: “Every n-vertex graph in some family 𝒢 of graphs has a (connected) dominating set of size at most f(n).” or a lower bound of the form “For infinitely many n, there exists an n-vertex member of 𝒢 with no (connected) dominating set of size less than g(n).”

One family of graphs that has received considerable attention in this context is the class of triangulations, that is, edge-maximal planar graphs. Matheson and Tarjan [29] proved that every n-vertex triangulation has a dominating set of size at most n/3=0.333¯n and that there exists n-vertex triangulations with no dominating set of size less than n/4=0.25n. The gap between these upper and lower bounds stood for over 20 years until a recent breakthrough reduced the upper bound to 17n/530.32075471698n [33]. This was swiftly followed by an improvement to 2n/7=0.2857142¯n [10].

The focus of the current paper is on the existence of small connected dominating sets in triangulations. In the following sections, we describe the history of this problem and then present our main results. At the end of the paper we present corollaries of our results for two applications in graph drawing.

Connected dominating sets are complementary to the leaves of spanning trees in the following sense: a set of vertices X is a connected dominating set of an n-vertex graph G if and only if G has a spanning tree in which the vertices of GX are all leaves in G. Thus, connected dominating sets are studied implicitly in the literature on spanning trees with many leaves [13, 28, 3, 4, 6, 30]. A closely related and extensively studied notion is that of spanning trees with no degree two vertices, known as homeomorphically irreducible spanning trees [8, 1, 9, 26, 25, 20]. Since an n-vertex tree with no degree 2-vertices has at least n/2+1 leaves, the existence of a homeomorphically irreducible spanning tree implies the existence of a spanning tree with at least n/2+1 leaves (and the existence of a connected dominating set of size at most n/21). As stated already, we consider connected dominating sets in triangulations. An easy consequence of the proof in [29] is that n-vertex triangulations have connected dominating sets of size at most 2n/3=0.666¯n. A more general result [28] shows that graphs of minimum-degree 3 in which each edge is included in a 3-cycle have connected dominating sets of size at most 2(n5)/3<0.666¯n. Albertson et al [1] prove that every triangulation has a homeomorphically irreducible spanning tree which, as discussed above, implies that every triangulation has a connected dominating set of size at most n/21<0.5n.

Chen et al [8] give a significant generalization of this result, which applies to any connected graph G in which the graph induced by the neighbours of each vertex is connected. Answering an open problem by [1] and confirming the conjecture of Archdeacon [21], the work in [9] generalizes this result to graphs in which every edge is in at least two 3-cycles.

Motivated by the fact that the 0.5n upper bound for triangulations has stood for over three decades, several authors have asked if it can be improved. Bradshaw et al [7, Question 4.2] ask if it can be improved to n/3. As it turns out, the answer is negative (see below for more on the lower bound). Noguchi and Zamfirescu [30] posed an even more modest question, asking whether the bound could be improved to (12ϵ)n for some ϵ>0, even when restricted to the special case of 4-connected triangulations.

Our main contribution is the first improvement to the longstanding n/2 upper bound for connected dominating sets in triangulations, as stated in the following theorem.

Theorem 1.

For every n3, every n-vertex triangulation G has a connected dominating set X of size at most 10n/21=0.476190¯n. Equivalently, G has a spanning tree T with at least 11n/21=0.523809¯n leaves. Furthermore, there exists an O(n) time algorithm for finding X and T.

Until recently, the best known lower bound for this problem, illustrated in Figure 1, was n/3=0.333¯n, obtained from a triangulation that contains n/3 vertex-disjoint pairwise-nested triangles Δ1,,Δn/3. In order to dominate Δ1Δ2, any connected dominating set must contain at least two vertices in Δ1Δ2. In order to dominate Δn/31Δn/3, any connected dominating set must contain at least two vertices in Δn/31Δn/3. Then, in order to be connected, any connected dominating set must contain a vertex in each of Δ3,,Δn/32.

Figure 1: A triangulation with n=3k vertices whose smallest connected dominating set has size n/3.

Since this example contains many separating triangles it is natural to consider the special case of 4-connected triangulations. Noguchi and Zamfirescu [30] describe, for infinitely many values of n, 4-connected n-vertex triangulations for which any connected dominating set has at least n/3 vertices. Very recently, the n/3 lower bound has been improved to 718n23 by Enami et al [19].

1.1 Outline

The remainder of this paper is organized as follows: In Section 2, we describe the general strategy we use for finding connected dominating sets in triangulations. In Section 2.2 we show that a simple version of this strategy can be used to obtain a connected dominating set of size at most 4n/7=0.571428¯n. In Section 3 we show that a more careful construction leads to a proof of Theorem 1. In Section 4, we discuss the connection between connected dominating sets and a graph drawing application. Finally, Section 5 concludes by pointing out directions for future work.

2 The General Strategy

Throughout this paper, we use standard graph-theoretic terminology as used, for example, by [12]. For a graph G, let |G|=|V(G)| denote the number of vertices of G. A bridge in a graph G is an edge e of G such that Ge has more connected components than G. For a vertex vG, NG(v):={wV(G):vwE(G)} is the open neighbourhood of v in G, NG[v]:=NG(v){v} is the closed neighbourhood of v in G. For a vertex subset SV(G), NG[S]:=vSNG[v] is the closed neighbourhood of S in G and NG(S):=NG[S]S is the open neighbourhood of S in G. A set XV(G) dominates a set BV(G) if BNG[X]. Thus, X is a dominating set of G if and only if X dominates V(G).

A plane graph is a graph equipped with a non-crossing embedding in 2. A plane graph is outerplane if all its vertices appear on the outer face. A triangle is a cycle of length 3. A near-triangulation is a plane graph whose outer face is bounded by a cycle and whose inner faces are all bounded by triangles. A generalized near-triangulation is a plane graph whose inner faces are bounded by triangles. Note that a generalized near triangulation may have multiple components, cut vertices, and bridges.

In several places we will make use of the following observation, which is really a statement about the triangulation contained in a cycle of length 3.

Observation 1.

Let H be a generalized near-triangulation and let xyz be a cycle in H. Then,

  1. 1.

    If the interior of xyz contains at least one vertex of H, then each of x, y, and z has at least one neighbour in the interior of xyz.

  2. 2.

    If the interior of xyz contains at least two vertices of H, then at least two of x, y, and z have at least two neighbours in the interior of xyz.

For a plane graph H, we use the notation B(H) to denote the vertex set of the outer face of H and define I(H):=V(H)B(H). The vertices in B(H) are boundary vertices of H and the vertices in I(H) are inner vertices of H. For any vertex v of H, the inner neighbourhood of v in H is defined as NH+(v):=NH(v)I(H), the vertices in NH+(v) are inner neighbours of v in H, and degH+(v)=|NH+(v)| is the inner-degree of v in H.

Let G be a triangulation. Our procedure for constructing a connected dominating set X begins with an incremental phase that eats away at G “from the outside.” The process of constructing X is captured by the following definition: A vertex subset XV(G) is outer-domatic if it can be partitioned into non-empty subsets Δ0,Δ1,,Δr1 such that

  1. (P1)

    Δ0B(G);

  2. (P2)

    ΔiB(G(j=0i1Δj)) for each i{1,,r1}; and

  3. (P3)

    G(j=0r1Δj) is outerplane.

Lemma 1.

Let G be a triangulation. Then any outer-domatic XV(G) is a connected dominating set of G.

We will present two algorithms that grow a connected dominating set in small batches Δ0,Δ1,,Δr2 that result in a sequence of sets X1,,Xr1 where Xi=j=0i1Δj. Each of these algorithms is unable to continue once they reach a point where each vertex in B(GXi) has inner-degree at most 1 in GXi. We begin by studying the graphs that cause this to happen.

2.1 Critical Graphs

A generalized near-triangulation H is critical if degH+(v)1 for each vB(H). We say that an inner face of H[B(H)] is marked if it contains an inner vertex of H.

Figure 2: Some critical graphs H with the marked faces of H[B(H)] shaded.
Lemma 2.

Let H be a critical generalized near-triangulation. Then each face f of H[B(H)] contains at most one vertex of I(H) and this vertex is adjacent to every vertex of f.

Lemma 3.

Let H be a critical generalized near-triangulation. Then |B(H)|3|I(H)| and there exists ΔB(H) of size at most |I(H)| that dominates I(H).

2.2 A Simple Algorithm

We start with the simplest possible greedy algorithm, that we call SimpleGreedy(G), to choose Δ0,,Δr1. Suppose we have already chosen Δ0,,Δi1 for some i0 and we now want to choose Δi. For i0, we let Xi:=j=0i1Δj, let Gi:=GXi, and let vi be a vertex in B(Gi) that maximizes degGi+(vi). During iteration i0, there are only two cases to consider:

  1. [g1]

    If degGi+(vi)2 then we set Δi:={vi}.

  2. [g2]

    If degGi+(vi)1 then Gi is critical and this is the final step, so r:=i+1. By Lemma 3, there exists ΔiB(Gi) of size at most |I(Gi)| that dominates I(Gi). Then Xr:=Xr1Δi and we are done.

Theorem 2.

When applied to an n-vertex triangulation G, SimpleGreedy(G) produces a connected dominating set Xr of size at most (4n9)/7.

Proof.

By the choice of Δ0,,Δr1, Xr is an outer-domatic subset of V(G) so, by Lemma 1, Xr is a connected dominating set of G. All that remains is to analyze the size of Xr. For each i{1,,r}, let Di:=NG[Xi] be the subset of V(G) that is dominated by Xi, let Ii:=V(G)Di be the subset of V(G) not dominated by Xi, and let Bi:=NG(Ii) be the vertices of G that have at least one neighbour in each of Xi and Ii. We use the convention that D0:=B(G).

First observe that, for i{0,,r2}, |Di+1||Di|+degGi+(vi) since Di+1Di and Di+1 contains the degGi+(vi) inner neighbours of vi in Gi. Therefore

|Dr1||D0|+i=0r2degGi+(vi)3+i=0r22=2r+1.

Since Dr1 and Ir1 partition V(G),

n=|Dr1|+|Ir1|2r+1+|Ir1|. (1)

Since Xr1 and Br1 are disjoint and Dr1Br1Xr1, we have |Dr1||Xr1|+|Br1|=r1+|Br1|. Therefore,

n =|Dr1|+|Ir1|r1+|Br1|+|Ir1|r1+4|Ir1|, (2)

where the last inequality follows from Lemma 3.

The final dominating set Xr has size |Xr|=|Xr1|+Δr1=r1+|Ir1|, so the size of |Xr| can be upper-bounded by maximizing r1+|Ir1| subject to Equations 1 and 2. More precisely, by setting x:=r and y:=|Ir1|, the maximum size of Xr is upper-bounded by the maximum value of x1+y subject to the constraints

x,y0
x1+4y n
2x+1+y n

This is an easy linear programming exercise and the maximum value of Xr is obtained when r=(3n5)/7 and |Ir1|=(n+3)/7, which gives |Xr|(4n9)/7.

3 A Better Algorithm: Proof of Theorem 1

Next we devise an algorithm that produces a smaller connected dominating set than what SimpleGreedy(G) can guarantee. This involves a more careful analysis of the cases in which SimpleGreedy is forced to take a vertex vi with degGi+(vi)=2. We will show that in most cases, any time the algorithm is forced to choose a vertex v that has inner-degree 2 in Gi, this can immediately be followed by choosing a vertex w that has inner-degree at least 3 in Giv. This is explained in Section 3.2.

When this is no longer possible, the algorithm will be forced to directly handle a graph Gi in which degGi+(v)2 for all vB(Gi) and Gi(Bi) is critical. In Section 3.5 we explain how this can be done using a set Xr1 whose size depends only on GiB(Gi). The results in Section 3.5 require that the graph GiB(Gi) not have any vertices of degree less than 2. The steps required to eliminate degree-1 and degree-0 vertices from GiB(Gi) are explained in Sections 3.4 and 3.3.

3.1 Dom-Minimal Dom-Respecting Graphs

We begin by identifying unnecessary vertices and edges that can appear in the graphs G1,,Gr1 during the construction of X. Refer to Figure 3. We say that a near-triangulation H is dom-minimal if

  1. (DM1)

    each vertex vB(H) has degH+(v)1;

  2. (DM2)

    for each vB(H) with degH+(v)=1, H[NH[v]] is isomorphic to K4; and

  3. (DM3)

    each edge vw on the boundary of the outer face of H is also on the boundary of some inner face vwx of H, where xI(H).

We say that a generalized near-triangulation H is dom-minimal if each of its biconnected components222A biconnected component of a graph G is a 2-connected maximal sub-graph. In other words, removing a vertex from this component keeps it connected. is dom-minimal.

Figure 3: A generalized near-triangulation that is not dom-minimal. The red vertices violate Item 1, the green vertex violates Item 2, and the red edges violate Item 3.
Observation 2.

Any dom-minimal generalized near-triangulation H is bridgeless.

Let H and H be two generalized near-triangulations. We say that H dom-respects H if

  1. (DP1)

    B(H)B(H);

  2. (DP2)

    I(H)=I(H); and

  3. (DP3)

    NH(v)I(H)NH(v)I(H) for all vV(H).

Observation 3.

Let H and H be generalized near-triangulations where H dom-respects H and let Δ be a subset of V(H) that dominates I(H) in H. Then Δ dominates I(H) in H.

Lemma 4.

For any generalized near-triangulation H, there exists a dom-minimal generalized near-triangulation H that dom-respects H.

Proof.

The proof is by induction on |V(H)|+|E(H)|. If H is already dom-minimal, then setting H=H satisfies the requirements of the lemma, so assume that H is not dom-minimal. Since Items 1, 2, and 3 are transitive relations, the dom-respecting relation is transitive: If H dom-respects H and H dom-respects H, then H dom-respects H. Therefore, it is sufficient to find H with fewer edges or fewer vertices than H that dom-respects H, and the inductive hypothesis provides the desired dom-minimal graph H that dom-respects H and H.

If H contains a vertex vB(H) with degH+(v)=0 then Hv is a generalized near-triangulation, B(Hv)B(H), I(Hv)=I(H), and NHv(v)I(H)=NH(v)I(H) for all vV(Hv). Therefore Hv dom-respects H and has fewer vertices than H so we can apply the inductive hypothesis and be done. We now assume that degH+(v)1 for all vB(H). Since H is not dom-minimal, H contains a biconnected component C that is not dom-minimal. If |C|=2 then C contains a single edge (a bridge of H) and removing this edge from H produces a graph with fewer edges that dom-respects H. Therefore, C has at least three vertices. (See Figure 4.)

Figure 4: Three cases on the way to making H dom-minimal.
  1. 1.

    Item 3: If there exists an edge vw on the outer face of C that is not incident to any inner face vwx with xI(C) then Hvw is a generalized near-triangulation, B(Hvw)=B(H), and I(Hvw)=I(H), and NHvw(v)I(H)=NH(v)I(H) for all vV(Hvw). Therefore, Hvw dom-respects H and has few edges than H. (This includes the case where C consists of the single edge vw.)

  2. 2.

    Item 1: If there exists a vertex vB(C) with degC+(v)=0 then v is incident to an edge vw that is on the outer face of C and on the outer face of H. Since degC+(v)=0, vw is not incident to any inner face vwx with xI(C) and we can proceed as in the previous case. (This eventually leads to all edges of C incident to v being removed from H.)

  3. 3.

    Item 2: If there exists a vertex vB(C) with degC+(v)=1 then H contains faces xvw and vyw where w is an inner vertex. If Case 1 does not apply to either of the two edges on the outer face of C incident to v then x and y are on the outer face of C. If H[NC[v]] is not isomorphic to K4, then xyE(H). In this case, let H be the graph obtained from H by removing the edge vw and replacing the edges xv and vy with the edge xy. Then H is a generalized near-triangulation, B(H)=B(H), I(H)=I(H), and NH(v)I(H)NH(v)I(H). Therefore H dom-respects H and has fewer edges than H.

3.2 Finding a 𝟐𝟑 Combo

Next, we show that in most cases our algorithm for constructing a connected dominating set is not forced to choose a single vertex of inner-degree 2. Instead, it can choose a pair v,w such that degH+(v)=2 and degHv+(w)3. Note that the next two lemmas each consider a graph H that is a near-triangulation, not a generalized near-triangulation.

Lemma 5.

Let H be a dom-minimal near-triangulation and let v0 be a vertex in B(H) with |NH(v0)B(H)|3. Then degH+(v0)2. In other words, if v0 is incident to a chord of the outerplane graph H[B(H)], then v0 is incident to at least two inner vertices of H.

Figure 5: The proof of Lemma 5.
Lemma 6.

Let H be a dom-minimal near-triangulation. Then either:

  1. 1.

    H is isomorphic to K4;

  2. 2.

    each vertex wB(HB(H)) has a neighbour v in B(H) with degH+(v)2.

Note that the next three lemmas consider the case where H is a generalized near-triangulation. The following lemma is illustrated in Figure 6.

Figure 6: Removing an inner-degree 2 vertex v is immediately followed by removing an inner-degree 3 vertex w and the vertex u is not in a dom-minimal graph that dom-respects H{v,w}.
Lemma 7.

Let H be a dom-minimal generalized near-triangulation. Then either:

  1. (1)

    HB(H) is critical;

  2. (2)

    B(H) contains a vertex v with degH+(v)3; or

  3. (3)

    H contains distinct vertices v0, vj, and w such that

    1. (a)

      v0B(H) and degH+(v0)=2;

    2. (b)

      wB(Hv0) and degHv0+(w)3; and

    3. (c)

      vjB(H) and NH+(vj)NH[w].

Figure 7: The proof of Lemma 7.

The following is a restatement of Lemma 7 in language that is more useful in the description of an algorithm for constructing a connected dominating set.

Corollary 1.

Let H be a dom-minimal generalized near-triangulation. Then either:

  1. (1)

    HB(H) is critical;

  2. (2)

    there is a vertex vB(H) and a dom-respecting subgraph H of Hv with |H||H|1 and |B(H)||B(H)|+2; or

  3. (3)

    there is an edge vwE(H) with vB(H), wB(HB(H)), and a dom-respecting subgraph H of H{v,w} with |H|=|H|3 and |B(H)|=|B(H)|+2.

3.3 Eliminating Inner Leaves

Next we show that, even when all vertices in B(H) have inner-degree at most 2 and HB(H) is critical, we can still efficiently dominate any vertex that has degree 1 in HB(H).

Lemma 8.

Let H be a dom-minimal generalized near-triangulation such that degH+(v)2 for all vB(H), HB(H) is critical, and HB(H) contains a vertex w with degHB(H)(w)=1. Then there exists vB(H) and a dom-respecting subgraph H of Hv such that |H||H|3 and |B(H)||B(H)|1.

H Hv H
Figure 8: The proof of Lemma 8.

3.4 Eliminating Inner Isolated Vertices

We now show that, even when all vertices in B(H) have inner-degree at most 2, HB(H) is critical, and HB(H) has no degree-1 vertices, we can still efficiently dominate degree-0 vertices in HB(H).

Lemma 9.

Let H be a dom-minimal generalized near-triangulation such that degH+(v)2 for all vB(H), HB(H) is critical, and HB(H) contains a vertex w with degHB(H)(w)=0 but does not contain any vertex w with degHB(H)(w)=1. Then there exists vB(H) and a graph H that dom-respects Hv such that |H||H|3 and |B(H)||B(H)|1.

Proof.

Refer to Figure 9 for an idea of the proof.

(i) (ii) (iii)
Figure 9: Eliminating isolated vertices in HB(H).

3.5 𝟐-Critical Graphs

We now explain what the algorithm does when it finally reaches a state where none of Corollary 1, Lemma 8 or Lemma 9 can be used to make an incremental step. The inapplicability of Lemmata 8, 9, and 1 leads to the following definition: A generalized near-triangulation H is 2-critical if

  1. (2-C1)

    degH+(v)2 for each vB(H);

  2. (2-C2)

    HB(H) is critical; and

  3. (2-C3)

    degHB(H)(w)2 for all wV(HB(H)).

(See Figure 10.) We will work our way up to a proof of the following lemma, which allows our algorithm to handle 2-critical graphs directly, in one step:

Figure 10: A 2-critical generalized near-triangulation.
Lemma 10.

Let H be a 2-critical generalized near-triangulation. Then there exists XV(H) of size at most (2|B(HB(H))|+I(HB(H)))/3 that dominates I(H) and such that each component of H[X] contains at least one vertex in B(H).

Lemma 11.

Let H be a dom-minimal 2-critical generalized near-triangulation. Then degH+(v)=2 for all vB(H).

Lemma 12.

Let H be a dom-minimal 2-critical generalized near-triangulation. Then |B(H)||B(HB(H))|.

For each integer r3, the r-wheel Wr is the near-triangulation whose outer face is bounded by a cycle v0,,vr1 that contains a single vertex x in its interior and that is adjacent to each of v0,,vr1. For even values of r, Wr is called an even wheel. Note that the following lemma, illustrated in Figure 11 is about critical graphs, not 2-critical graphs.

Figure 11: Lemma 13: Partitioning the vertices of a biconnected critical graph into three dominating sets.
Lemma 13.

Let H be a biconnected critical generalized near-triangulation with at least 3 vertices and not isomorphic to Wk for any even integer k. Then there exists a partition {X0,X1,X2} of V(H) such that

  1. (i)

    For each edge vw of H[B(H)], vXi and wXj for some ij;

  2. (ii)

    for each i{0,1,2}, Xi dominates H.

H H H
Figure 12: The proof of Lemma 13.

The following lemma, illustrated in Figure 13 explains how we deal with even wheels not covered by Lemma 13:

Lemma 14.

Let H:=Wk for some even integer k4 and let v be any vertex in B(H). Then there exists a partition {X0,X1,X2} of V(H) such that

  1. (i)

    For each edge vw of H[B(H)], vXi and wXj for some ij;

  2. (ii)

    X0 dominates V(H){v} and X1 and X2 each dominate H.

Figure 13: Lemma 14: Partitioning the vertices of an even wheel into sets X0, X1, and X2.

The following lemma, illustrated in Figure 14, drops the requirement that the critical graph be biconnected and applies even if some of the biconnected components of H are even wheels.

Figure 14: Lemma 15: Partitioning the vertices of a connected critical graph into dominating sets X0, X1, and X2.
Lemma 15.

Let H be a connected critical generalized near-triangulation with at least 3 vertices, no vertices of degree 1 and not isomorphic to Wk for any even integer k. Then there exists a partition {X0,X1,X2} of V(H) such that

  1. (i)

    for each edge vw of H[B(H)], vXi and wXj for some ij;

  2. (ii)

    for each i{0,1,2}, Xi dominates H,

Proof.

The proof is by induction on |H|. First, suppose that |H|=3. Since H is connected and has no vertices of degree 1, H is a triangle v0v1v2. We take Xi:={vi} for each i{0,1,2}. Clearly these sets satisfy the requirements of the lemma.

If H is biconnected then, since H is not an even wheel, we can immediately apply Lemma 13 and we are done. Otherwise, H contains a cut vertex v that separates H into components C1,,Ck and such that H:=H[V(C1){v}] is biconnected. Refer to Figure 15. Since H has no vertices of degree 1, H has at least three vertices. If H is isomorphic to Wk for some even integer k then we apply Lemma 14 to H and v to obtain sets X0, X1, and X2. Otherwise, we apply Lemma 13 to H to obtain sets X0, X1, and X2. In either case we may assume, without loss of generality that vX1, that X1 and X2 each dominate H and that X0 dominates V(H){v}.

Figure 15: Two cases in the proof of Lemma 15.

Let H′′:=HV(C1). First, suppose that degH′′(v)>1. If H′′ is isomorphic to Wk for some even integer k then we apply Lemma 14 to H′′ and v to obtain sets X0′′, X1′′, X2′′. Otherwise, we apply the inductive hypothesis to H′′ to obtain sets X0′′, X1′′, X2′′ that each dominate H′′. In either case we may assume, without loss of generality (by renaming) that vX1′′, that X1′′ and X2′′ each dominate H and that X0′′ dominates V(H′′){v}. Then the sets X0:=X0X2′′, X1:=X1X1′′ and X2:=X2X0′′ satisfy the requirements of the lemma. (The only concern is whether each set dominates v, but this is guaranteed by the fact that vX1, and that X2X2 and X2′′X0 each dominate v.)

Finally, if degH′′(v)=1 then we consider the maximal path v,v1,v2,,vr1,vr such that degH′′(vi)=2 for each i{1,,r1}. Let H′′′:=H′′{v,v1,,vr1} and we treat H′′′ exactly as we treated H′′ in the previous paragraph to obtain sets X0′′′, X1′′′ and X2′′′. Without loss of generality, we assume that vrX(r1)mod3, that X(r1)mod3 and X(rmod3) each dominate H′′′ and that X(r2)mod3 dominates V(H′′′){vr}. Let X0′′:=X0′′′{vi:i2(mod3)}, X1′′:=X1′′′{v}{vi:i0(mod3)}, and X2′′:=X2′′′{vi:i1(mod3)}. Then vX1′′, X1′′ and X2′′ each dominate H′′, and X0′′ dominates V(H′′){v}. We can now define the sets X0, X1, and X2 exactly as we did in the previous paragraph.

At last, the following lemma, illustrated in Figure 16, shows how we combine everything to find three sets whose total size is at most 2|B(HB(H))|+|I(HB(H))|.

Figure 16: Lemma 16: Finding three sets X0, X1, and X2 that dominate I(H) in a 2-critical graph H.
Lemma 16.

Let H be a 2-critical generalized near-triangulation. Then there exists X0,X1,X2V(H) such that

  1. (i)

    |X0|+|X1|+|X2|2|B(HB(H))|+|I(HB(H))|;

  2. (ii)

    for each i{0,1,2}, Xi dominates I(H) in H; and

  3. (iii)

    for each i{0,1,2}, each component of H[Xi] contains at least one vertex in B(H).

Proof of Lemma 10.

Take X to be the smallest of the three sets X0, X1, and X2 guaranteed by Lemma 16.

3.6 The Algorithm

All of this has been leading up to a variant SimpleGreedy(G) that we call BetterGreedy(G). Suppose we have already chosen Δ0,,Δi1 for some i0 and we now want to choose Δi. Let Xi:=j=0i1Δj, let Gi be a dom-minimal graph that dom-respects GXi, and let vi be a vertex in B(Gi) that maximizes degGi+(vi). During iteration i0, there are now more cases to consider:

  1. [bg1]

    If degGi+(vi)3 then we set Δi:={vi}.

  2. [bg2]

    Otherwise, if GiB(Gi) contains a vertex of degree 1 we set Δi:={vi} where vi is the vertex v guaranteed by Lemma 8.

  3. [bg3]

    Otherwise, if GiB(Gi) contains a vertex of degree 0 we set Δi:={vi} where vi is the vertex v guaranteed by Lemma 9.

  4. [bg4]

    Otherwise, if there exists distinct u,vB(Gi) and wB(GiB(Gi)) such that degGi+(v)=2, degGiv+(w)3, and NGi+(u)NGi(w) then set Δi:={v,w}.

  5. [bg5]

    Otherwise, Gi is 2-critical and i+1=:r. By Lemma 10, there exists Δr1V(Gi) of size at most 2|B(GiB(Gi))|/3+|I(GiB(Gi))|/3 that dominates I(Gi).

Theorem 3.

When applied to an n-vertex triangulation G, BetterGreedy(G) produces a connected dominating set Xr of size at most (10n18)/21.

Proof.

By Lemmata 8, 9, and 7 during each of the first r1 steps, one of the following occurs:

xt:

For some t3, we can add a single vertex vi that increases the size of the dominated set Di+1:=N[Xi+1] by t and increases the size of the boundary set Bi+1:=NG(I(GDi+1)) by at most t1.

a:

We can add a vertex vi that increases the size of the dominated set Di+1 by 2 and decreases the size of the boundary set Bi+1 by at least 1.

b:

We can add a vertex vi that increases the size of the dominated set Di+1 by 1 and decreases the size of the boundary set Bi+1 by at least 3.

c:

We can add a pair of vertices {vi,wi} that increase the size of the dominated set Di+1 by at least 5 and increases the size of the boundary set Bi+1 by at most 2.

:

We can directly complete the connected dominating set Xr=Xi+1 by adding a set Δr1=Δi of at most (2|B(GiB(Gi))|+|I(GiB(Gi))|)/3 additional vertices where, as before Gi:=G[Bi(V(G)Di)] and r=i+1.

Refer to Figure 17. Let a, b, c, and xtt3 denote the number of times each of these cases occurs in the first r1 steps, and let D:=Dr1, B:=Br1, and X:=Xr1. Then,

|D| 3+t3txt+2a+b+5c (3)
|B| 3+t3(t1)xta3b+2c (4)
|X| t3xt+a+b+2c. (5)
Figure 17: The sets X, D, B, R, and S.

Let R:=B(Gr1B(Gr1)) and S:=I(Gr1B(Gr1)). Since {D,R,S} is a partition of V(G),

|D|+|R|+|S|=n. (6)

By Lemma 12, |Br1||B(GiB(Gi))|, i.e., |B||R|. Putting everything together we get the constraints:

3+t3txt+2a+b+5c+|R|+|S|n (by Equation 3 and Equation 6) (7)
3+t3(t1)xta3b+2c|R| (by Equation 4 and since |B||R|) (8)

with all values non-negative. The size of the final connected dominating set Xr is then at most

|Xr|=|X|+|Δr1|t3xt+a+b+2c+2|R|/3+|S|/3. (9)
Claim 1.

If (a,b,c,|R|,|S|,x3,x4,) are non-negative and satisfy Equations 7 and 8, then setting x3x3+t4(t1)xt/3 and xt0 for all t4 also satisfy Equations 7 and 8 and do not decrease Equation 9.

Proof.

Suppose xt>0 for some integer t4, otherwise there is nothing to prove. Let i:=min{t4:xt>0} and set x3x3+(t1)xt/3 and xt0. This change causes the left-hand-side of Equation 7 to decrease by xt. This change does not affect the left-hand-side of Equation 8. This change increases the value of Equation 9 by (t1)xt/3xt0.

By Claim 1, maximizing Equation 9 subject to the constraints given by Equations 7 and 8 is a linear program in six variables (x3,a,b,c,|R|,|S|) which can be done easily. The maximum is achieved when x3=a=b=c=|S|=0, c=(n6)/7 and |R|=(2n+9)/7, at which point Equation 9 evaluates to (10n18)/21.

Theorem 3 establishes the combinatorial result in Theorem 1 and the following theorem establishes the algorithmic result.

Theorem 4.

There exists a linear-time algorithm that implements BetterGreedy(G).

4 An Application in Graph Drawing

This section demonstrates applications of connected dominating sets and, in particular, our main result to graph drawing. In particular, we present an application of our main result to two graph drawing problems: one-bend free sets and simultaneous embeddings.

4.1 One-Bend Free Sets

For a planar graph G, a set YV(G) is called a free set if, for every |Y|-point set P2, there exists a non-crossing drawing in the plane with edges of G drawn as line segments and such that the vertices of Y are drawn on the points of P. (For historical reasons, the set Y is also called a collinear set.) It is known that every n-vertex planar graph has a free set of size Ω(n) [5, 15, 16]. For bounded-degree planar graphs, this result can be improved to |Y|=Ω(n0.8) [17]. Determining the supremum value of α such that every n-vertex planar graph has a collinear set of size Ω(nα) remains a difficult open problem, but it is known that αlog23(22)<0.9859 [31]. A history of free sets and their applications in graph drawing and related areas is surveyed by [18].

It is common in graph drawing to consider non-crossing drawings of a graph G in which each edge of G is represented by a polygonal chain consisting of at most k+1 line segments. Such a representation is called a k-bend drawing of G (so a straight-line drawing is a 0-bend drawing). A subset Y of V(G) is a k-bend free set if, for every |Y|-point set P, G has a k-bend drawing in which the vertices of Y are mapped to the points in P. In [27], they show that, for any planar graph G, V(G) is a 2-bend free set, so every n-vertex planar graph has a 2-bend free set of size n. This leaves open the question of 1-bend free sets. In Lemma 17, we show that, for any spanning tree T of G, the leaves of T are a one-bend free set of G. Combined with Theorem 1, this gives:

Theorem 5.

For every n3, every n-vertex planar graph has a one-bend free set L of size at least 11n/21=0.523809¯n. Furthermore, there exists an O(n) time algorithm for finding L.

Note that if the point set P is contained in the x-axis then, in a 1-bend drawing, no edge with both endpoints in Y crosses the x-axis. Therefore, such a 1-bend drawing gives a 2-page book-embedding of the induced graph G[Y]. This implies that G[Y] is a spanning subgraph of some Hamiltonian triangulation G[Y]+. The Goldner–Harary graph is an 11-vertex triangulation that is not Hamiltonian. It follows that the graph G obtained by taking k vertex-disjoint copies of the Goldner-Harary graph has n:=11k vertices and has no one-bend free set of size greater than 10k=10n/11=0.9090¯n.

In the remainder of this subsection we prove Theorem 5. We start by introducing a topological equivalent of one-bend collinear sets as in [11].

A curve C is a continuous mapping from [0,1] to 2. We usually call C(0) and C(1) the endpoints of C. If C(0)=C(1) then the curve is closed. Otherwise, it is open. A curve C is called simple if C is C(x)C(y) for all 0x<y1 with the exception of x=0, y=1. C is a Jordan Curve if it is simple and closed.

Let G be plane graph, a Jordan curve C is a k-proper good curve if it contains a point in the interior of some face of G (good), and the intersection between C and each edge e of G is empty, or at most k points, or the entire edge e (k-proper).

In [11], they characterize collinear sets in the straight line drawing of a planar graph using 1-proper good curves.

Theorem 6 ([11] ).

Let G be a plane graph. A set SV(G) is a collinear set if and only if there exists a 1-proper good curve that contains S.

The following lemma, illustrated in Figure 18, gives a similar condition for one-bend collinear sets.


Figure 18: Subdividing G so that a 2-proper good curve C becomes a 1-proper good curve for the subdivided graph G+.
Observation 4.

Let G be a plane graph. A set SV(G) is a one-bend collinear set if G has a 2-proper good curve C that contains S.

We next prove that the leaves of a spanning tree of a planar graph induce a one-bend collinear set. Precisely, we prove the following theorem.

Lemma 17.

Let G be a planar graph and T be a spanning tree of G. Then, the leaves of T form a one-bend collinear set for G.

Proof.

Let Γ be a straight-line drawing of G. By Observation 4, it is enough to introduce a 2-proper good curve on Γ containing all the leaves of T. To navigate the curve on the drawing Γ, we construct an envelope around Γ as follows. For each vertex vV(G), we draw a small circle, Cv, centered at v. We make the radii of the circles small enough such that each vertex vV(G), Cv intersects only the edges incident to v and it is disjoint from all the other circles that correspond to the other vertices. Moreover, for each edge uvE(G), we draw two parallel segments on both sides of uv with endpoints on the boundary of corresponding circles of u and v. These parallel segments are close enough to the corresponding edges such that no two of them intersect. (see Figure 19). Note that each edge uvE(G) crosses the envelope exactly twice, once at Cu and once at Cv.


Figure 19: Constructing a 2-proper good curve for G that contains all the leaves of the tree T.

Assume T is rooted at an arbitrary vertex of degree at least 2. We build the curve on the envelope of Γ as follows. Starting from the root, we traverse the tree in depth first search order. For each edge uvE(T), we add the segment on the right side of the traversal direction of uv into the curve .

For each leaf u of T, let vu be its neighbor in T. To include all the leaves of T on the curve , we join u to the endpoint of segments around the edge uvuE(T) on Cu. To keep the curve closed, for each non-leaf vertex uV(T), we append to the circular arcs from Cu between the segments in in the order of the traversal. By the properties of the depth first traversal, is a closed curve. By construction, contains all the leaves of T and all the other vertices of T are inside . Moreover, for each edge uvE(G):

  1. (P1)

    If uvE(T) and neither u nor v is a leaf, then |uv|=0,

  2. (P2)

    If uvE(T) and either u or v is a leaf of T, then |uv|=1, and

  3. (P3)

    If uvE(T), then |uv|=2.

Properties P1-P3 guarantee that is a 2-proper curve. Since the tree T is not empty, intersects the circle of some vertex in T, so touches a face of Γ. Therefore, is 2-proper good curve and by Observation 4, there exists a one-bend collinear set for G formed by the leaves of T.

Proof of Theorem 5.

Let G be an n-vertex planar graph. Theorem 1 implies that G has a spanning tree with at least 11n/21 leaves that can be computed in O(n) time. Using this tree in Lemma 17 establishes Theorem 5.

4.2 Simultaneous Embedding with Fixed Edges and Without Mapping

A planar graph equipped with a non-crossing embedding is called a plane graph. We treat any subgraph G of a plane graph G as a plane graph that inherits its embedding from G. A plane graph in which all vertices appear on a single face is called an outerplane graph. Motivated by a graph drawing problem (called, simultaneous embedding with fixed Edges and without mapping), the authors of [2] prove the following result:

Theorem 7 ([2]).

Every n-vertex plane graph G (and therefore every triangulation) contains an induced outerplane graph G[L] with at least n/2 vertices.

Observe that if G is a connected plane graph and X is a connected dominating set of G, then the vertices of X are all contained in the interior of a single face F of GX. Since X is a dominating set, every vertex of GX is on the face F. Thus, all vertices of GX are on a single face, so GX is an induced outerplane graph.

Combined with Theorem 1, this implies the following improvement of Theorem 7:

Corollary 2.

Every connected n-vertex plane graph G contains an induced outerplane graph G with at least 11n/21=0.523809¯n vertices, and there exists an O(n) time algorithm to find the graph G.

Corollary 2 immediately implies an improved result for the graph drawing problem considered by [2], improving the bound from n/2 to 11n/21:

Theorem 8.

For every n-vertex planar graph G1 and every 11n/21-vertex planar graph G2, there exists point sets P1P2 with |P1|=n, |P2|=11n/21 and crossing-free embeddings of G1 and G2 such that

  1. (a)

    the vertices of Gi are mapped to the points in Pi for each i{1,2};

  2. (b)

    the edges of G2 are drawn as line segments; and

  3. (c)

    each edge e of G1 whose endpoints are both mapped to points in P2 is drawn as a line segment.

We end this section with the following observation. We argued above that if X is a connected dominating set in a triangulation G, then the induced graph G[V(G)X] is an outerplane graph. Although it is not immediately obvious, finding the largest induced outerplane graph in a triangulation G is equivalent to the problem of finding the smallest connected dominating set.

Theorem 9.

Let G be a triangulation with n4 vertices, let X be a minimum-sized connected dominating set of G, and let Y be a maximum-sized subset of V(G) such that all vertices of G[Y] lie on a common face of G[Y]. Then |X|+|Y|=n.

Proof.

Let X be a minimum-size connected dominating set of G and let Y=V(G)X. Then G[Y] is outerplane, since every vertex in Y:=V(G)X is on the boundary of the face of G[Y] that contains all vertices of X in its interior. Since Y has maximum size |X|+|Y||X|+|Y|=n.

Now consider a set Y of maximum size such that all vertices of G[Y] lie on a common face FY of G[Y] and, among all such maximum-size sets, choose Y to maximize the number of vertices of G that are contained in the interior of FY. Without loss of generality, suppose FY is the outer face of G[Y], so G[Y] is outerplane. Let X:=V(G)Y. Since n4, Y does not contain all three vertices on the outer face of G, so X dominates the vertices on the outer face of G. For any vertex wY not on the outer face of G, some neighbour of vNG(w) is in X since, otherwise G[NG(v)]G[Y] contains a cycle with w in its interior, contradicting the fact that G[Y] is outerplane. Therefore X is a dominating set of G.

We now show that all vertices of X are in the outer face of G[Y], which implies that G[X] is connected. Suppose, by way of contradiction, that some inner face F of G[Y] contains at least one vertex of X in its interior. Since G is connected, there is at least one vertex vV(F) such that NG(v) contains at least one vertex in the interior of F. Let Z:={wNG(v):w is in the interior of F}. Let Y:=YZ{v}. Then |Y||Y|, G[Y] is outerplane, and the outer face of G[Y] contains more vertices of G than FY. This contradicts the choice of Y.

Therefore X is a connected dominating set of G. Since X is of minimum size, |X|+|Y||X|+|Y|=n. Therefore n|X|+|Y|n, so |X|+|Y|=n, as required.

5 Conclusions

In this paper, we broke the longstanding n/2 barrier for connected dominating sets in triangulations, showing that every triangulation admits a connected dominating set of size at most 10n/21 (and that it can be computed in optimal, linear time). This result narrows the gap to the best-known lower bound and has applications to graph drawing.

We conclude with two natural open questions:

  1. 1.

    What is the minimum value c such that every n-vertex triangulation (with n3) has a connected dominating set of size at most cn+O(1)? Our main result, Theorem 1, and the recent lower bound [19] imply that 7/18c10/21.

  2. 2.

    What is the maximum value α such that every n-vertex planar graph contains a one-bend collinear set of size αnO(1)? Theorem 5 shows α11/21 and disjoint copies of the Goldner-Harary graph show that α10/11.

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