1. Introduction
With the development of VLSI technology and software technology, multiprocessor systems with hundreds of thousands of processors have become available. With the continuous increase in the size of multiprocessor systems, the complexity of a system can adversely affect its fault tolerance and reliability. To the design and maintenance purpose of multiprocessor systems, appropriate measures of reliability should be found.
A network is often modeled by a graph
with the vertices representing nodes such as processors or stations, and the edges representing links between the nodes. One fundamental consideration in the design of networks is reliability [1] [2]. An edge cut of a connected graph
is a set of edges whose removal disconnects
. The edge connectivity
or connectivity
of
is the minimum cardinality of an edge cut or vertex cut
of
. The edge connectivity
or connectivity
is an important feature determining reliability and fault-tolerance of the network. In the definitions of
or
, no restrictions are imposed on the components of
. To compensate for this short coming, it would seem natural to generalize the notion of the classical connectivity by imposing some conditions or restrictions on the components of
. Following this idea, conditional connectivity were proposed in [3] by Harary.
Let
be a connected graph and
be graph-theoretic property. The conditional edge connectivity
or conditional connectivity
is the minimum cardinality of a set of edges or vertices, if it exists, whose deletion disconnects
and each remaining component has property
. In particular, we focus on that each component has the property of minimum degree
. The k-conditional edge connectivity
is the cardinality of the minimum edge cuts
, if any, whose deletion disconnects
and each component of
has property of minimum degree
. The k-conditional connectivity
can be obtained similarly. In recent years, numerous results about many kind of connectivities on networks have been reported [4]-[20].
Let
be a connected graph,
the neighbors of avertex
in
(simply
),
the edges incident to
. Moreover, for
,
is the subgraph induced by
,
,
,
and
denotes the subgraph of
induced by the vertex set of
. If
,
denotes the length of a shortest
-path. For
, denote by
the set of edges of
with one end in
and the other in
. For graph-theo- retical terminology and notation not defined here we follow [21]. All graphs considered in this paper are simple, finite and undirected.
Two binary strings
and
are pair-related, denoted
, if and only if
; if
and
are not pair-related, we write
.
The crossed cube
with
vertices was introduced by Efe [22]. It can be defined inductively as follows:
is
, the complete graph with labels 0 and 1. For
,
contains
and
joined according to the following rule: the vertex
from and the vertex
from
are adjacent if and only if
1)
if
is even, and
2) for
.
From the definition, we can see that each vertex of
with a leading 0 bit has exactly one neighbor with a leading 1 and vice versa. It is an n-regular graph. In fact, some pairs of parallel edges are changed to some pairs of cross edges. Furthermore,
can be obtained by adding a perfect matching
between
and
. Hence
can be viewed as
or
briefly. For any vertex
is the edge incident to
in
.
The crossed cube is an attractive alternative to hypercubes
. The diameter of
is approximately half that of
. For more references, we can see [23]-[29] (Figure 1).
In this paper, we obtain that:
, and we also prove other properties of
.
2. Conditional Connectivity of Crossed Cubes
The crossed cube
has an important property as follows.
Lemma 2.1. Any two vertices of
have at most two common neighbors for
if they have.
Proof: By induction. If
, then the result holds. We assume that it is true for
. Suppose
and any
such that
have at most two common neighbors.
If
, then the two common neighbors are in
according to inductive hypothesis. And there is not a relation between the common neighbors of
and the perfect matching
added to
. Hence
have at most two common neighbors in
.
By symmetry, we assume that
. The common neighbors must be obtained by adding the perfect matching
. Note that every vertex of
has only one neighbor in
and vice versa. Then we obtain the result.
Corollary 2.2. For any two vertices
,
1) if
, then they have at most two common neighbors;
2) if
, then they do not have common neighbors.
Corollary 2.3. The girth of
is
.
According to the definition of
, and similar to Lemma 2.1, we have
Lemma 2.4. Let
and
be any two vertices of
such that have only two common neighbors.
1) If
, then the one common neighbor is in
, and the other one is in
2) If
or
, then the two common neighbors are in
or
.
Lemma 2.5. Let
be an induced subgraph of
and
.
1)
.
2) If
, then
.
3) If
, then
is a 4-cycle
and
.
Proof:
Because
and The girth of
is 4,
. If
, then
is a 4-cycle
.
Assume that
. Let
. Since
,
has at least two neighbors in
, which is a contracted to the definition of
. Hence
. If
, then
.
Theorem 2.6.
.
Proof:
Take a 4-cycle
in
. Clearly,
and
is not connected and minimum degree of each component is at least two. Then
.
We will show
by induction. It is easy to check that holds for
. So we suppose
. Assume that it is true for
. Let
.
Let
with
. And
is not connected and minimum degree of each component is at least two. We have
or
. Without loss of generality, we set
. And
is connected from the inductive hypothesis. We will show that every vertex of
is connected to
.
If there is a vertex
of
with
, then by the hypothesis
is connected to
, a contradiction. Hence for any vertex
of
, we have
. Let
be an any component of
. Since
, we have
and
by Lemma 2.6. Suppose
and
. Let
be a some vertex of
. Because of
, at least one vertex of
has a neighbor in
. Then
is connected to
. Moreover,
is connected, a contradiction.
3. Conclusion
The conditional connectivity is a generalization of classical connectivity of graphs. We determined the r-conditional degree connectivity of
for the small r. In the future, we will study other properties of crossed cubes.
Acknowledgements
The authors would like to thank the referees for kind help and valuable suggestions.