1. Introduction
We consider connected simple undirected graphs in this paper. and are the vertex set and the edge set of a graph G, respectively. The size of a graph is the cardinality of its edge set. In a graph G, the set of neighbors of v is , while the degree of v is . The distance between u and v is the length of a shortest path between then. The eccentricity of a vertex v is the maximum distance from v to all the other vertices in a graph. The diameter and the radius of a graph G are, respectively, the maximum and the minimum eccentricity over all vertices in G.
Topological indices are tools to character entire graphs, especially in chemical graph theory. The average eccentricity
of a graph
G is the mean value of eccentricities over all vertices in
G, i.e.,
. The average eccentricity is another distance metric on a graph and introduced by [
1]. Directly relying on a polynomial algorithm for the All-Pairs Shortest Paths Problem [
2], the average eccentricity can be calculated in time complexity
where
n is the order of the graph. The properties, formulas, and bounds on the average eccentricity have recently been studied intensely [
3,
4,
5,
6,
7,
8,
9,
10,
11,
12]. Several other topological indices have also been well studied, such as Steiner (revised) Szeged index [
13], Wiener Polarity Index [
14], connective eccentricity index [
15], and eccentric connectivity index [
16]. Recently, Mao et al. [
17] surveyed the progress of Steiner-type topological indices. On chemical graphs, Ahmad et al. [
18] studied the chemical graphs of copper oxide and carbon graphite. They computed and gave close formulas of eccentricity based topological indices, such as total eccentricity index and average eccentricity index for chemical graphs of carbon graphite and copper oxide.
This paper is organized as follows. Basic terminologies and formulas are stated in
Section 2. We establish the equivalence relation and bounds of the average eccentricity on block graphs with order
n in
Section 3. As supports for
Section 3,
Section 4 and
Section 5 study the bounds over the set of block graphs with the same block order sequence and the set of path-like block graphs, respectively. In addition, we devise a linear time algorithm to extract the block order sequence for a block graph
G in
Section 6. Finally, we conclude our paper by looking forward to future work in
Section 7.
2. Preliminaries
In a path P, a vertex is named as an endpoint of P if its degree is exactly one in P. Otherwise, it is called an internal vertex in P. If u and v are the two endpoints of a path P, we shortly use or to stand for the path P. A path P is simple if every vertex is distinct from the other vertices of P. A vertex v is said to be a cut-vertex of a graph G if its deletion increases the number of connected components of G. Otherwise, it is said to be a non-cut-vertex. If every block of a graph is a clique, then the graph is named as a block graph.
A block graph is said to be a trivial block graph if and only if it has only one block. In a non-trivial block graph, a block is said to be a pendent block if it interacts with a unique block. Therefore a pendent-block has exactly one cut vertex. The other vertices in a pendent block must be non-cut-vertices. We call the non-cut-vertices of a pendent block pendent vertices of the block graph.
Lemma 1. There are at least two pendent blocks in a non-trivial block graph.
Proof. Let G be a non-trivial block graph. Let be the set of blocks in G where is the total number of blocks in G. Let C be the set of cut-vertices in G. We construct a new graph H as follows. The vertex set is where A is a new vertex set such that and there is a bijective function from the vertex set A to the block set . Two vertices are adjacent if and only if the following two situations occur simultaneously.
u and v are in A and C, respectively.
There is a vertex such that w and v are adjacent in the graph G.
Now, we show that H is exactly a tree. H is connected due to the connectedness of G. Suppose on the contrary that there is a cycle Q in H. As every vertex in A is not adjacent with the other vertices of A, and every vertex in C is also not adjacent with the other vertices of C, the vertices on the cycle Q come from A and C alternatively. Hence, at least two vertices, say u and v, of Q are from A. Therefore, the two blocks and are in the same block of G, which is a contradiction. Therefore, H is a tree.
According to the construction of
H, the degree of every vertex from
C must be at least two in
H. So every leaf of
H must be a vertex in
A. As
G is a non-trivial block graph,
A must has at least two vertices, so
H must has at least three vertices. Hence,
H has at least two leaves [
19]. Therefore,
G has at least two pendent blocks. □
Let and be an ordered pair set on the positive integer set . The set S is named as a block order sequence if for each ordered pair , is not less than two. Then, for every integer i ( ), stands for the order of some block and stands for the number of blocks with order . Therefore, k represents the cardinality of block orders. Let be the set of all block graphs with the block order sequence S.
By the above definitions, for a block graph , the number of blocks , the order n and the size m of G are presented in the following Theorem 1.
Theorem 1. Let be a block graph. Then we have:
The number of blocks in G is
Proof. By the definition of in a block order sequence, stands for the number of blocks with order . To sum all, there are, in total, blocks in block graphs with the given block order sequence. For every block with order , the number of edges in such a block is . Therefore, on the whole, there are edges in all blocks. This value is equal to the size of the block graph. In the following, we calculate the order of G.
By the definition, for every , the total number of vertices in all blocks with order is . In total, then, there are vertices in all blocks. However, this value is larger than the order of G, as some vertices are shared by more than one block.
Now we prove that there are shared vertices in a block graph with blocks. If , the block graph has just one block. Trivially, there are no shared vertices. Suppose ; there are shared vertices. We are going to prove that when , there are p shared vertices.
Let G be a block graph with blocks. By Lemma 1, let Q be a pendent block. Let v be the unique cut vertex in Q. Delete all vertices from G. Then we obtain a graph with exactly p blocks. By the induction, there are shared vertices in . Now we add Q to in order to obtain G. Q and must share exactly one vertex, so there are p shared vertices in G. Therefore, in total there are shared vertices in a block graph with blocks.
So the order of a block graph is . □
In particular, a block graph is said to be a star-like block graph if and only if there is a unique cut-vertex in it. By the definitions, we have,
Theorem 2. Let be a star-like block graph. The average eccentricity of G iswhere α is the number of blocks in G and calculated by Equation (1). Proof. If , there is a unique block in G. The unique block is a complete graph. So the eccentricity of every vertex is 1. Hence, the average eccentricity of G is 1.
If , by definition, there is only one cut-vertex in a start-like block graph. Therefore, the eccentricity of the unique cut-vertex is 1, while the eccentricity of each of the other vertices is 2. Hence, the average eccentricity of the star-like block graph is . □
In terms of contributions, this paper achieves the following two main results.
The lower and upper bounds of the average eccentricity on block graphs. We established an equivalence relation on the set of graphs with order n from the perspective of block order sequence, which is going to be presented in Theorem 3. The equivalence relation naturally partitions the set of block graphs with order n into several equivalent classes. Recall that all graphs in every such equivalent class have the same block order sequence. Thus, to bind the average eccentricity on block graphs with order, n is transformed to bind the value on every equivalent class. This transformation seems independently interesting.
A linear time algorithm to find out a block order sequence. Algorithm 1 is devised to find out the block order sequence of a block graph. The algorithm is proven to be in linear time by Theorem 16. This result shows that it is practicable and available to study the eccentricity on block graphs from the perspective of its block order sequence.
3. Extremal Values on Block Graphs with Order n
Let be the set of block graphs with order n. We define a binary relation over the set where, for every two graphs, , if and only if G and H have the same block order sequence. We name the relation the sequence-equivalence relation.
Theorem 3. The sequence-equivalence relation on is an equivalence relation.
Proof. It is easy to verify that the relation is reflexive, symmetric, and transitive as follows.
For every graph , , so it is reflexive.
if and only if for every two graphs , so it is symmetric.
for , if and , then must be in the relation , so it is transitive.
Therefore the sequence-equivalence relation is reflexive, symmetric and transitive. So it is an equivalence binary relation. □
As the sequence-equivalence relation
is an equivalence relation, it partitions the graph set
into several equivalence classes. Let
be the set of all equivalence classes where each
is an equivalence class formed by
and
is the cardinality of
. The set
is also named as the
quotient of
by
[
20].
Recall that all graphs in every equivalent class of
have the same block order sequence. Therefore, the minimum lower bound among all equivalent classes is the lower bound of the block graphs with order
n, while the maximum upper bound among all equivalent classes is the upper bound of the block graph with order
n. Therefore, the lower and upper bounds are written as:
Therefore, the problem of bounding the average eccentricity on block graphs with order n is transformed to the problem of bounding the average eccentricity on block graphs with the same block order sequence.
By Theorem 8 in
Section 4, for any block order sequence
S, the lower bound on block graphs with block order sequence
S is either
for
, or 1 for
. Recall that, if
, then the block graph is a complete graph with order
n, so the lower bound on block graphs with order
n is 1.
In addition, by Theorem 10 in
Section 4, for a given block order sequence
S, the upper bound of the average eccentricity on block graphs with block order sequence
S is
, where
is a path-like block graph with the maximum average eccentricity among the set of path-like block graphs with block order sequence
S which is defined in Theorem 13 in
Section 5. Therefore, the upper bound on block graphs with order
n is
. Thus, the average eccentricity of block graphs with order
n can be bounded by Theorem 4.
Theorem 4. Let G be a block graph of order n. Then we have Theorem 14 in
Section 5 decides the value of
and shows that the upper bound is
.
Integrating Theorems 4 and 14, we achieve the bounds of average eccentricity on block graphs with order n in the following Theorem 5.
Theorem 5. Let G be a block graph of order n. Then we have 4. Bounds on Block Graphs with a Fixed Block Order Sequence
Now we study the bounds and corresponding extremal graphs over the set of block graphs having the same block order sequence. Before establishing bounds and extremal graphs, we define a notations
as follows. Let
be an ordered vertex pair where
u is a cut vertex of
G and
. Let
be a graph obtained by removing the edges, each of which is not only incident with
u but also on
a simple path from
u to
v in
G. Let
be a connected component of
such that
contains the vertex
u (see
Figure 1 as an example). In particular, if
, then let
.
To obtain the lower bound and the corresponding extremal graph, we define a
block-slide transformation on a graph
in
Section 4.1. A graph
which is obtained by a block-slide transformation on
G satisfies both
and
. For the upper bound, we define a
block-shift transformation on a graph
in
Section 4.2. A graph
which is obtained by a block-shift transformation on
G satisfies both
and
.
4.1. The Lower Bound and Corresponding Extremal Graphs
Block-slide transformation: Let
be a block in a block graph
G depicted in
Figure 2, where
u and
v are two distinct cut-vertices of
. Let
and
be two subgraphs in G (see
Figure 2). Let
. The transformation from
G to
is named as a
block-slide transformation on
G. On the other side, the transformation from
to
G is named as an
inverse block-slide transformation on
, i.e.,
.
Theorem 6. Each block-slide transformation eliminates exactly one cut-vertex from a block graph.
Theorem 7. Let be a block graph which is obtained by a block-slide transformation on a block graph G (see Figure 2). Then holds. Proof. Let
be a block with order
in
G. Put the vertices of
on a cycle and label its vertices clockwise as
,
,
,…,
,
(see
Figure 3). Without loss of generality, let
. There are
parts in the graph
G. They are
,
,
,…,
, and
, where
,
, and each
is the subgraph
for
. Let
. There are mainly cases of the relationship over
,
, and
L. For each case, we consider the behavior of the average eccentricity on
G in the following.
Case 1: . For every vertex , we have . For every vertex , . For every vertex , . Hence, the average eccentricity of the whole graph does not increase after a block-slide transformation.
Case 2: . It is easy to verify that the eccentricity of every vertex in G does not change under the transformation. So the average eccentricity of the whole graph remains the same after a block-slide transformation.
Case 3: . It is easy to verify that if there is a subgraph such that , then the average eccentricity of the whole graph remains the same after the transformation. Let us consider the case that there is no integer such that .
holds for every vertex .
holds for every vertex .
holds for every vertex .
.
As holds, we have .
Above all, the block-slide transformation does not increase the value of average eccentricity of a block graph. Hence, the theorem holds. □
Corollary 1. Let G be a block graph which is obtained by an inverse block-slide transformation on a block graph (see Figure 2). Then holds. Theorem 8. Every block graph G with a fixed block order sequence satisfieswhere α is the number of blocks in G and calculated by Equation (1). Proof. Let
and
be the block order sequence of the block graph
G. We repeatedly apply the block-slide transformation on
G until no more such transformation can be applied. As each block-slide transformation eliminates one cut-vertex, the transformation procedure must stop at a state in which there is a unique cut-vertex in the graph. In other words, we achieve a star-like block graph when no more block-slide transformation could be applied to the graph. By Theorem 7, the whole transformation procedure does not increase the average eccentricity. Hence, an
n-order star-like block graph reaches the minimum value of the average eccentricity among all block graphs with order
n. Finally, by Equation (
4), if there is more than one block in
G, then
. Otherwise, the lower bound is exactly one. □
4.2. The Upper Bound and Corresponding Extremal Graphs
In this section, we define a block-shift transformation on a block graph and then we present an upper bound on a graph under the help of such a transformation.
Let t be a cut-vertex of a block graph G and be the set of edges which are all incident with t. Let be a partition of such that two edges belong to the same element of if and only if u and v are in the same block of G. For every element , the petal corresponding to a is defined as follows. is a connected component of such a graph which is obtained by deleting the edges in from G, and contains the cut-vertex t.
In this section, we will see a special kind of block graph which is named a path-like block graph. A block graph G is named a path-like block graph if it either is a complete graph or has exactly two pendent blocks while each of the other blocks contains exactly two cut-vertices.
Block-shift transformation: Let
be a block in a block graph
G where
t,
v, and
w are all cut-vertices in
as depicted in
Figure 4. Note that the three cut-vertices
t,
w, and
v do not need to be distinct to each other. Let
C be a petal at the vertex
t such that
C is a path-like block graph and does not contain the block
. Let
be a pendent vertex of
G. Let
A and
B be two sets of petals corresponding, respectively, to vertices
w and
v, such that
holds. Let
. Then the transformation from
G to
is said to be a
block-shift transformation on graph
G, while the transformation from
to
G is said to be an
inverse block-shift transformation on graph
, i.e.,
.
Theorem 9. Let be a block graph which is obtained by a block-shift transformation on a block graph G (see Figure 4). Then holds. Proof. It is obvious that the eccentricity of every vertex in A and B does not decrease under the block-shift transformation. As , the eccentricity of every vertex in the set also could not be decreased by the block-shift transformation. Above all, after a block-shift transformation, the average eccentricity of a block graph does not decrease. □
Corollary 2. Let G be a block graph which is obtained by an inverse block-shift transformation on a block graph (see Figure 4). Then holds. Repeatedly apply the block-shift transformation on a block graph G. Finally we will reach a state that the graph G turns into a path-like block graph. By Theorem 9, the transformation does not decrease the average eccentricity, so the upper bound on block graph set must be achieved by a path-like block graph in . Let be a path-like block graph with the maximum average eccentricity among all path-like block graphs in . The upper bound on the set can be written in the following Theorem 10.
Theorem 10. Let be a block graph with the set S as its block order sequence. Then, The following
Section 5 is to present a method to obtain a
.