1. Introduction and Terminology
There are many articles in the literature investigating variables of either vertex or edge domination, while there are few papers in the literature investigating vertex-dominating edges. In many situations in real life, we need to dominate edges using vertices; for example, in the context of highway safety, if highways are considered as edges, and intersections (or towns) as vertices, the aim is to place services—such as road safety vehicles—at vertices with minimum cost; that is, we want to use as few road safety vehicles as possible. This highlights the usefulness of dominating edges using vertices or, as it is called in the literature, vertex–edge domination.
In this work, we introduce a variant of vertex–edge domination called vertex–edge Roman -domination, which involves adding an extra condition to vertex–edge domination. In the highway safety example, this additional condition enhances the reliability of highway safety. Vertex–edge Roman -domination relaxes the condition of vertex–edge Roman domination (the definition of this notion will be given later); thus, the vertex–edge Roman -domination number lies between the vertex–edge Roman domination number and vertex–edge domination number (the definition of this notion will be given later). This may improve the understanding of the previous two vertex–edge domination variants.
All graphs in this paper are finite, undirected, and simple (i.e., they contain no parallel edges and no loops). Let The set of all vertices adjacent to v in G is denoted by , which is called the open neighborhood of v. The closed neighborhood of v in G is the set . If G is clear from the context, we write and instead of and , respectively. The degree of a vertex is A vertex is called a leaf if . A vertex is called a support vertex if u is adjacent to a leaf; u is called a strong support vertex if u is adjacent to at least two leaves. We denote the set of leaves in a graph G by . We denote the number of leaves and the number of support vertices in G by and , respectively. A path with n vertices is denoted by . A cycle with n vertices is denoted by . A star graph with n vertices ( leaves and one non-leaf vertex) is denoted by . A double star graph is a connected graph that contains exactly two non-leaf vertices; a double star graph can be obtained from two star graphs by adding an edge between their centers. Let G be a connected graph. The distance between two vertices , denoted by , is the length of a shortest path between u and v in G. The diameter of G is A path in G is called a diametral path if its length is equal to , and it is a shortest path between its ends. A tree that has a vertex r identified as the root is called a rooted tree. The successors of a vertex v in a rooted tree are the neighbors of v that are not in the unique path between v and the root r. In some of the literature, the successors of v are called the children of v. If T is a rooted tree and , then denotes the subtree of T that is induced by v and its successors.
Let
be a graph. A set
is called
a vertex–edge dominating set of
G if, for every edge
, (
. The minimum cardinality of a vertex–
edge dominating set of
G is called the vertex–edge domination number of
G, and it is denoted by
Vertex–edge domination was introduced in [
1].
Let be a function, where . The weight of the function f is . Let , where . If H is a subgraph of G, then .
A function
is called
a Roman dominating function on
if every vertex
with
is adjacent to a vertex
u with
. The
Roman domination number of
G is the minimum weight of a Roman dominating function on
G. Roman domination was motivated by a defensive strategy used to protect the Roman Empire by Constantine the Great, who was born in 272 and died in 337 BC. The strategy was then studied as a mathematical concept in graph theory in [
2,
3,
4,
5,
6].
A function
is called
a vertex–edge Roman dominating function, abbreviated as veRDF, on
if, for every edge
with
,
. The
vertex–edge Roman domination number of
G is
Vertex–edge Roman domination was introduced in [
7] and investigated further in [
8]. A variant of vertex–edge Roman domination, called vertex–edge perfect Roman domination, was introduced and investigated in [
9].
A function
is called a Roman
-dominating function if, for every
with
,
The minimum weight of a Roman
-dominating function of
G is the Roman
-domination number of
G, and it is denoted by
. Roman
-domination was introduced in [
10]. For a recent survey of this notion, refer to [
11].
In this work, we begin the study of vertex–edge Roman -domination. A function is called a vertex–edge Roman -dominating function, abbreviated as veR2DF, on if, (★) for every edge with , . We say the edge is f-dominated if either or (★) holds. The vertex–edge Roman -domination number of G is It is not difficult to see that the vertex–edge Roman -domination number is bounded above by the Roman -domination number and bounded below by the vertex–edge domination number; that is, for any graph G,
Observe that, for every connected graph G with , we have that , as one can label a vertex with 0 and label each of the remaining vertices with 1 to obtain a veR2DF on G. Clearly, every veRDF is veR2DF. On the other hand, if f is a veR2DF on G, then the function , defined as , , is a veRDF on G with ; hence, we have the following result.
Proposition 1. Let G be a graph. Then, .
The next result follows directly from the definition of Roman -domination.
Proposition 2. For any graph G, .
The following result gives the exact value of the of cycles.
Theorem 1. Let Then, .
Proof. First, we show that for any . Let , and . Define a veR2DF f on such that if and if . Clearly, ; so, for any . Now, we prove by induction on n that for any . It is not difficult to see that if , then , and . This has proven the base step. Let be a cycle of order , and assume that the statement holds for all , where . Assume that there exists a veR2DF f on such that . Choose two distinct vertices such that and is as small as possible. From the definition of a vertex–edge Roman -dominating function, we must have . If , contract the shortest path between u and v to a single vertex w, and let the new formed cycle be . Observe that ; so, . Define a veR2DF on such that and for every . Then, . This contradicts the hypothesis; hence, the statement holds. Now, assume that ; so, we must have . Contract the shortest path between u and v to a single vertex w, and let the new formed cycle be . Observe that ; so, . Define a veR2DF on such that and for every . Thus, . This contradicts the hypothesis; hence, the statement holds. □
2. Paths and Trees
Paths and trees are important classes of graphs due to their applications. For example, paths represent connections and routes within a network, and trees are used to model hierarchical data and relationships. In this section, we provide the exact value of the vertex–edge Roman -domination number of paths, and we give a tight lower bound and a tight upper bound for the vertex–edge Roman -domination number of trees.
Theorem 2. Let Then, .
Proof. First, we show that . Let If define a veR2DF f on such that if and otherwise. Clearly, If define a veR2DF f on such that if and otherwise. Clearly, Thus,
Now, we show by induction on n that If , then ; if , then ; if , then . This establishes the base step. Let be a path of order , and assume that , where . Assume, for the sake of contradiction, that there exists a veR2DF f on with . We check the possibilities of the summation Clearly, .
- Case 1.
; then, either
or
. If we are in the first sub-case (i.e.,
), then we must have
; if we are in the second sub-case, then either
or
. By deleting the vertices
, we obtain the path
, and the restriction of
f on
gives a veR2DF
on
such that
contradicting the hypothesis.
- Case 2.
Assume that either
or
. By deleting
, we obtain the path
, and the restriction of
f on
gives a veR2DF
on
such that
contradicting the hypothesis. So, we may assume that
. By deleting
, we obtain the path
. Define a veR2DF
on
such that
, and
otherwise. Then,
contradicting the hypothesis.
Hence, the statement holds. □
We need a proposition and a lemma before providing a tight lower bound for the vertex–edge Roman -domination number of trees.
Proposition 3. Let G be a graph of order and θ a veR2DF on G such that . Then,
Proof. Assume that G contains a leaf v with . Let w be the support vertex adjacent to v. Define a veR2DF on G such that and for all . Clearly, , which contradicts the hypothesis. □
Lemma 1. Let G be a graph of order . Then, there exists a veR2DF θ on G such that , and .
Proof. Let f be a veR2DF on G that witnesses . By Proposition 3, If , we are finished. Assume that . Since then every is adjacent to a support vertex with Define a veR2DF on G such that and for every , and otherwise. Clearly, and, as , it follows that . □
Theorem 3. Let T be a tree of order with l leaves and s support vertices. If T is not a star graph, then .
Proof. We proceed by induction on n. If (this includes the case ), then T is a double star graph. It is clear that . This establishes the base step.
Assume that , and assume that the statement holds for every tree with Let , be a diametral path in T. Among all possible candidates of the diametral path, choose P such that is the maximum possible. Let be a veR2DF on T.
Assume that
T contains a strong support vertex
v. Let
u and
w be two leaves adjacent to
v. Let
be the tree obtained from
T by deleting
w; then,
,
, and
. Define a veR2DF
on
as follows. If
or
let
for every
; otherwise, let
and
for every
From the induction hypothesis, we have
so, the statement holds.
We may assume that
T does not contain a strong support vertex. Then, we must have
. Assume that
is a support vertex; then,
is adjacent to a leaf
. Let
be the tree obtained from
T by deleting
. Then,
,
, and
. Define a veR2DF
on
as follows. If
or
, set
for every
; otherwise, set
and
for every
From the induction hypothesis, we have
thus, the statement holds. We may assume that
is not a support vertex. Assume that
. Then,
is adjacent to a vertex
that is different than
and
, and
is adjacent to a leaf
. Let
be the tree obtained from
T by deleting
and
. Then,
, and
. Define a veR2DF
on
as follows. Let
. Observe that
. Let
for all
. From the induction hypothesis, we have
thus, the statement holds. We may assume that
. If
T is a path, the statement holds by Theorem 2. Assume that
T is not a path; so,
T has a leaf
different from
and
. Observe that
is not adjacent to
, as
T does not have a strong support vertex. Thus, the tree
has at least four vertices. Observe that
, and if
, then either
or
. Define a veR2DF
on
as follows. If
, let
, and let
for all
. If
, let
for all
From the induction hypothesis, we have
thus, the statement holds. □
The bound is tight, as , (by Theorem 2).
We need to define some rooted trees before moving to the next theorem. Let
,
,
,
, and let the middle vertex be labeled
w. Let
denote any tree obtained from the star graph
by subdividing each edge once, and denote the vertex in the center by
w. Denote the non-leaf vertex in
by
w; let
be the tree obtained from
by subdividing two edges once. Let
be any tree obtained from
by adding a pendant edge to
w. Let
. All the previous trees are rooted at
w (see
Figure 1).
Theorem 4. If T is a tree of order , then .
Proof. We proceed by induction on n. If , then , and it is clear that If (this includes the case then T is a star graph, and If , then T is a double star graph, and . It is clear that If , there exists a vertex such that, for every . Define a veR2DF on T, such that , and , for all So, . This establishes the base step. We may assume that T is a tree with , and if is a tree with , then Throughout the proof, we use the symbol to denote a fixed veR2DF on that witnesses and satisfies the condition (see Lemma 1).
Claim 1. If T contains a strong support vertex v, then the statement holds.
Proof. Let u and w be two leaves adjacent to v. Let be the tree obtained from T by deleting u. From the induction hypothesis, Let be a veR2DF on with minimum weight and (see Lemma 1); so, Observe that as , so either or . Define a veR2DF on T such that and for all . Clearly, , and we are finished. □
We may assume that T does not have a strong support vertex. Let , be a diametral path in T. Choose the diametral path P such that is the maximum possible. Observe that as T does not have a strong support vertex. Let be the root of the tree
Claim 2. If, then the statement holds.
Proof. Let be the tree obtained from T by deleting and all its successors (i.e., is the tree obtained from T by deleting ). From the induction hypothesis, Let be a veR2DF on with minimum weight; so, Define a veR2DF on T such that and for all the successors of , and for all . Clearly, , and we are finished. □
We may assume that ; so, either or .
Claim 3. If , then the statement holds.
Proof. The neighbors of are , , and a vertex v. The vertex v must be a leaf as . Assume that . Let be the tree obtained from T by deleting . From the induction hypothesis, Define a veR2DF on T such that , , and for all the successors x of , and for all . Clearly, , and we are finished.
We may assume now that
. Assume that
is adjacent to a leaf
w. Let
be the tree obtained from
T by deleting
From the induction hypothesis,
Define a veR2DF
on
T such that
,
, and
for all the successors
x of
. Thus,
, and we are finished. We may assume that
is not adjacent to a leaf. Then, for every
,
for some
. Let
, where
(as an example, the graph
H in
Figure 2,
and
; so,
,
, and
). Observe that
as
, and
Observe also that
as
. Let
be the tree obtained from
T by deleting
. From the induction hypothesis,
Assume that
. Define a veR2DF
on
T such that
, and
, if
,
, if
,
, for all other successors of
, and
for all
. Thus,
Inequality
comes from the fact that
and
.
Assume that
. Define a veR2DF
on
T such that
, and
, if
,
, if
,
, for all other successors of
, and
for all
. Thus,
Inequality
comes from the fact that
. □
We may assume that .
Claim 4. Ifthen the statement holds.
Proof. Assume that
is adjacent to a leaf
w. Let
be the tree obtained from
T by deleting
From the induction hypothesis,
Observe that
, and, if
then
. Define a veR2DF
on
T such that
,
, and
for all
Thus,
and we are finished. So, we may assume that
is not adjacent to a leaf.
Assume that is adjacent to a support vertex w. Let be the tree obtained from T by deleting From the induction hypothesis, Observe that, if , then we must have . Define a veR2DF on T such that , , and for all Thus, and we are finished. So, we may assume that is not adjacent to a support vertex.
Let
. Since
v is neither a leaf nor a support vertex, we must have
. From the way that
was chosen, we must have
. So,
; see
Figure 3.
Let
be the tree obtained from
T by deleting
From the induction hypothesis,
, where
. Define a veR2DF
on
T such that
for every support vertex in
,
for the remaining vertices in
, and
for all
Thus,
where inequality
comes from the assumption
(so
. Thus, the statement holds. □
Claim 5. If, then the statement holds.
Proof. Assume that . Let be the tree obtained from T by deleting From the induction hypothesis, Define a veR2DF on T such that , and for all Thus, and we are finished. So, we may assume that .
Assume that is adjacent to a leaf w. Let be the tree obtained from T by deleting From the induction hypothesis, Define a veR2DF on T such that , and for all Thus, and we are finished. So, we may assume that is not adjacent to a leaf.
For every
,
for some
. Let
, where
. Observe that
as
, and
as
. Let
be the tree obtained from
T by deleting
From the induction hypothesis,
where
. If
, define a veR2DF
on
T such that
,
, if
,
, if
(see
Figure 1),
, if
,
for the remaining vertices in
, and
for every
Thus,
where inequality
comes from the fact that
. If
, define a veR2DF
on
T such that
,
if
,
if
,
if
,
for the remaining vertices in
, and
for every
Thus,
where inequality
comes from the fact
. Thus, the statement holds. □
This completes the proof of the theorem.
The bound in Theorem 4 is tight as the following theorem indicates.
Theorem 5. Let n be a positive integer such that . Then, there exists a tree T of order n such that .
Proof. As
, there exists a positive integer
m such that
. For every
let
; so,
is a path with seven vertices. Let
be the tree obtained from the disjoint union of
,
by adding the set of edges
. The tree
is given in
Figure 4. From Lemma 1, there exists a veR2DF
on
such that
, and
. This means that
for every
; so, either
or
. Similarly, either
or
. If
and
, then we must have
. So,
for every
. Thus,
. From Theorem 4, we must have
, as required. □
3. Complexity
Graph complexity is crucial for understanding and analyzing various real-world systems represented as graphs. Understanding graph complexity helps in designing efficient algorithms and classifying the difficulty of computational problems. In this section, we show that vertex–edge Roman -domination is NP-complete even for bipartite graphs.
Consider the following decision problem.
veR2D
Instance: A graph and such that .
Question: Is there a veR2DF f with ?
We transform an NP-complete problem, called Exact 3-Cover (X3C) [
12], to veR2D.
X3C
Theorem 6. veR2D is NP-complete for bipartite graphs.
Proof. It is clear that veR2D is in the NP class. Let
, where
and
is an instance of X3C. For every
, let
. Let
be the disjoint union of
’s,
. For every
, let
. Let
be the disjoint union of
’s,
. Let
G be the graph obtained from the disjoint union of
and
by adding the edges
if
. Clearly,
G is a bipartite graph; see
Figure 5. Set
.
Assume that has an exact 3-cover . Define a veR2DF f as follows. For every , let , and ; for every , let if , and if . As is an exact 3-cover, the edges and the edges , where and are f-dominated. The remaining edges are obviously f-dominated; so, f is a veR2DF with .
Conversely, assume that G admits a veR2DF f with . Clearly, for every ; so, , and if , then , and . Clearly, for every ; so, , and if for some , then . Let , and . Then, . As , . On the other hand, . So, and . Hence, the set is an exact 3-cover. □
4. Conclusions
In this work, we introduced a variant of domination called vertex–edge Roman
-domination. The majority of the articles considering domination sets have studied vertex–vertex domination or edge–edge domination; however, in this work, vertices dominate edges. This type of domination can be applied to any real-life network where monitoring edges by nodes is required, for example, in the context of monitoring highway safety. In this domination, each vertex is assigned an integer between 0 and 2 such that, if there is an edge with endpoints each assigned 0, then the sum of the vertex weights on the neighborhood of those two endpoints is greater than or equal to 2. This new notion is related to a vertex–vertex domination called Roman
-domination (also called Italian domination). Vertex–edge Roman
-domination relaxes the condition of Roman
-domination; thus, the vertex–edge Roman
-domination number of a graph G is a lower bound for the Roman
-domination number of G. This new domination also adds an extra condition to a domination introduced in 1986, called vertex–edge domination; therefore, the vertex–edge Roman
-domination number of a graph G is an upper bound for the vertex–edge domination number of G. Vertex–edge Roman
-domination also relaxes the condition of vertex–edge Roman domination; as such, the vertex–edge Roman
-domination number of a graph G is a lower bound of the vertex–edge Roman domination number. In real-life contexts, adding an extra condition to a domination variant usually results in better service but with a higher cost; in contrast, relaxing the conditions of a domination variant reduces the cost and reduces the quality of service as well. Thus, vertex–edge Roman
-domination balances the quality of service and the cost between vertex–edge domination and vertex–edge Roman domination. In [
13], the authors proved that, for any tree
T of order
,
; furthermore, they proved that this bound is tight. In our work, we showed that
and this bound is tight; thus, as mentioned earlier, vertex–edge Roman
-domination costs more than vertex–edge domination. In [
14], the authors proved that, if
T is a tree of order
n with
l leaves and
s support vertices and
, then
, and this bound is tight. In our work, we proved that if
T is a tree of order
and
, then
, and this bound is tight. Therefore, the cost of vertex–edge Roman
-domination is lower than vertex–edge Roman domination.
In this work, we determined the exact vertex–edge Roman -domination number for cycles and paths and provided tight lower and upper bounds for the vertex–edge Roman -domination number of trees. In addition, we proved that the decision problem associated with vertex–edge Roman -domination is NP-complete for bipartite graphs.
In future work, we aim to characterize graphs G such that , as well as characterize graphs such that . We also aim to investigate the vertex–edge Roman -domination number for other classes of graphs, for example, cubic graphs.