1. Introduction
Multiprocessor systems have many advantages over their uniprocessor counterparts, such as high performance and reliability, better reconfigurability, and scalability. With the development of VLSItechnology 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. For the design and maintenance purpose of multiprocessor systems, appropriate measures of reliability should be found.
A graph 
 can simulate a network. The edges can represent links between the nodes, and the vertices can represent nodes that are processors or stations. Reliability is the essential consideration in network design [
1,
2]. For a connected graph 
G, the connectivity 
 is defined as the minimum number 
k of vertices that can be removed to reduce the graph connectivity or leave only one vertex. For the reliability of networks, connectivity is worst for most measures. To compensate for this shortcoming, it seems reasonable to generalize the notion of classical connectivity by imposing some conditions or restrictions on the components of 
, where 
F denotes faulty processors/links. Hence, many parameters that can measure the reliability of multiprocessor systems have been proposed. Suppose 
; if 
, then 
 is a 
t-component cut of 
G. The number of vertices in the least 
t-component cut is the 
t-component connectivity 
 of 
G. Correspondingly, the 
t-component edge connectivity 
 is obtained. The 
t-component (edge) connectivity was proposed in [
3,
4] independently. Fábrega et al. proposed extraconnectivity in [
5]. Let 
 be a vertex set. If 
 is disconnected and every component of 
 contains at least 
 vertices, then 
 is an extra-cut. The number of vertices in the smallest extra-cut is the extraconnectivity 
.
Suppose  is a connected graph,  (simply ), e is an edge, and w is an end of e}.
Q is a subset of 
V; 
 is the subgraph induced by the vertices in 
Q, 
; 
 is the subgraph of 
G that is induced by the vertices of 
. If 
, then 
 is the number of edges of the shortest 
-path. For 
, the edge set 
. We follow [
6] for terminology and notation. We only consider simple, finite, and undirected graphs.
 Definition 1.  BC networks:The one-dimensional bijective connection network  is the complete graph . Let  and G be an n-dimensional BC graph. Suppose  is an n-dimensional bijective connection graph}. An n-dimensional BC graph G can be defined recursively:
- (1) 
- For two non-empty subsets , ; 
- (2) 
- An edge set , Q is a perfect matching between  and , . 
 In the following, we denote 
 an 
n-dimensional BC network. The 
n-dimensional BC network 
 with 
 vertices and 
 edges was introduced by Fan et al. [
7]. An 
n-dimensional BC graph 
 is 
n regular Hamilton-connected. BC graphs contain most of the variants of the hypercube: hypercube, crossed cube, twisted cube, locally-twisted cube, and so on. We can see that 
, 
, 
, where 
 is a four-cycle, 
 is a three-dimensional hypercube, 
 is a three-dimensional crossed cube, 
 is a three-dimensional twisted cube, and 
 is a three-dimensional locally-twisted cube. 
 and 
 are isomorphs of 
.
According to the definition, every vertex of  has only one neighbor in , and every vertex of  also has only one neighbor in . Because  can be obtained by putting a perfect matching W between  and ,  can be viewed as  or . Suppose  is the edge incident to w in W.
The BC graphs are an attractive alternative to hypercubes 
. For more references about BC networks, see [
8,
9,
10,
11,
12,
13]. For more references about component connectivity, see [
14,
15,
16].
In this work, we get that:
- (1)
- Suppose ; . 
- (2)
- Suppose ; . 
- (3)
- Suppose ; . 
- (4)
- Suppose ; . 
- (5)
- Suppose ; . 
  2. Properties of BC Networks
The BC networks  has an important property as follows.
Lemma 1  ([
11])
. Let  be any two vertices. Then, . Corollary 1. Suppose that  are any two vertices. Then,
- (1) 
- if  is two, then ; 
- (2) 
- if , then . 
 From Lemma 1, we can see that the girth of  is . By the definition of , we obtain:
Lemma 2. Suppose that  are any two vertices such that .
- (1) 
- If , then  and . 
- (2) 
- If  or , then  or . 
 Lemma 3 ([
7])
. If , then . Theorem 1. If , .
 Theorem 2. Suppose , .
 Proof.  In a cycle 
, take 
 with 
. Then, 
 (see 
Figure 1) and 
. Hence, 
.
We will show  by induction; this is right for . Hence, let . Suppose that the case of  is true. Set .
By contradiction, suppose  and . Furthermore, , say  and . We have  or . We set  by symmetry. Hence,  must be connected.
If , then  by the inductive hypothesis, and . Since every vertex of  has one neighbor in , at most one vertex of  does not have neighbors in . Hence, , a contradiction.
Hence, . At most one connected component of  is not connected to . Then, , a contradiction again. □
 Lemma 4. Let  be an any vertex. The connectivity  is .
 Proof.  Since , . We need to prove . The case of  is true. Set  and .
By contradiction, suppose  with . Next, it will be proven that  is connected. Since ,  is connected. By Theorem 4, , then : one component is the vertex w, and the other component is . However,  for , and at least one vertex of  is connected to . Then,  is connected, and this contradicts the hypothesis. □
 Lemma 5. Suppose , then .
 Proof.  Pick an edge . Therefore,  is disconnected, and at least two vertices are contained in every connected component. That is .
It suffices to show  by induction. The case of  is true. Assume that , and this is right when . This will be proven for .
By contradiction, suppose  with . We will show that  is connected or  contains an isolated vertex. We suppose  by symmetry. Then,  is connected.
If each connected component of  contains more than one vertex, according to the inductive hypothesis,  and . At most one vertex of  does not have neighbors in . Hence,  is connected.
Suppose  is the isolated vertex of . Note that , and by Lemma 4, . If , then . Then,  has an isolated vertex , or  has an isolated vertex  whose degree is  in , or  is connected to , a contradiction.
Assume . Since , and ,  is connected by Lemma 4. However, ,  is connected to  or  has an isolated vertex , and this contradicts the hypothesis. □
 Theorem 3. Suppose , .
 Theorem 4. Suppose , .
 Proof.  Pick an edge 
, then 
. 
 (see 
Figure 2). That is, 
.
Next, we will show that  by induction. The cases of  are true. Therefore, we set , and this is right for . Next, for , it will be proven that this is right.
By contradiction, suppose , , and  has at least three components. Since , we have  or , say . Note that .
 Case 1.   is disconnected.
We obtain  and .
If  is disconnected, then . That is . However, every vertex of  has a path to one component of . Hence,  has at most two components, and this is a contradiction.
Since , if  is connected, then  has a path to one component of . Hence, , and this is a contradiction.
 Case 2.   is connected.
If  is connected, then it holds. Assume that  is not connected. At most one isolated vertex is in  since .
If , then  by the inductive hypothesis. Then, at most one of the components of  is not connected to , , a contradiction.
Therefore, we suppose that . However, , , a contradiction. □
 Theorem 5. Suppose , then .
 Proof.  Pick a path 
. Then, 
. Then, 
 (see 
Figure 3). That is, 
.
Next, we will show that  by induction. The cases of  are true. Therefore, we suppose  and assume all the cases of  are true. We will prove that the case of  holds.
By contradiction, assume that , , and . Since , we have  or , say . Since , .
 Case 1.   is connected.
If , then  according to the inductive hypothesis. At most two edges need to be deleted again. Because every vertex of  has a neighbor in  and , , a contradiction.
Suppose . If , then . Assume that . At most one edge needs to be delete again. Note that , and  and  are connected. Hence, , a contradiction. Then, . At least one component of  is connected to . Then, , a contradiction again.
Then, let . Because of , , a contradiction.
 Case 2.  .
Then,  and . Note that .
If , then  and . However,  and , , a contradiction.
Hence, . We have , and , a contradiction. □