Complexity
Equation (2) shows the changes of network system reliabil-
ity in the case of component from normal state to failure state.
us, Birnbaum measure can be defined as
𝐵
𝑖
(
)
=
(
)
𝑖
(
)
=
𝑒
𝑖
=1
(
)
−
𝑒
𝑖
=0
(
)
,
1≤≤.
()
Here
𝑒
𝑖
=1
()is the network system reliability when component
is normal and
𝑒
𝑖
=0
()is the network system reliability when
component is failure.
2.2. Critical Importance. In network system, the failure rate
of each component is dierent, so Lambert [] proposes a
critical importance to describe the probability of network
system failure caused by network system component .Itcan
also be functioned as
𝐶𝑀𝐹
𝑖
(
)
=
(
)
𝑖
(
)
×
𝑖
(
)
(
)
, 1≤≤.
()
From the perspective of the whole system, () can be further
converted to the following one:
𝐶𝑀𝐹
𝑖
(
)
=
𝐵
𝑖
(
)
×
𝑖
(
)
(
)
, 1≤≤.
()
Equation () shows that the reliability of network system is
the product of the Birnbaum measure of component and the
ratio of system failure rate, when the state of component is
from the normal to failure.
2.3. Network System Reliability Stability. Assuming that a
network system contains components, the risk growth
factor [] of component canbedenedas
𝑖
(
)
=
𝑒
𝑖
=0
(
)
−
(
)
=1−
𝑒
𝑖
=0
(
)
−
(
1−
(
))
=
(
)
−
𝑒
𝑖
=0
(
)
.
()
Here
𝑒
𝑖
=0
()isthenetworksystemfailureratewhencompo-
nent is in malfunction. is formula describes the impact of
the failure of component on system reliability. In addition,
based on (), the other two reliability metrics, average risk
and reliability stability, can be concluded, which measure
theimpactofsinglecomponentmalfunctiononnetwork
reliability. e average risk growth factor can be expressed as
follows by its own denition:
(
)
=
∑
𝑚
𝑖=1
𝑖
(
)
=
∑
𝑚
𝑖=1
(
)
−
𝑒
𝑖
=0
(
)
,
()
where is the average impact of all components failure indi-
vidually on the network system reliability. On the basis of (),
the network reliability stability [] can be formulated as
(
)
=
(
)
−
(
)
(
)
.
()
It can be known, by the denition of network system reliabil-
ity stability, that the network system reliability stability and
network system reliability are greatly related to the network
system average risk growth factor. When () → 1,the
network system component failure has little impact on the
network system reliability, and vice versa.
2.4. Experimental Analysis. For any network system, it is
noted that the complexity of network topology can make
network components decomposed as combination of series
and parallel system, and the complexity needed by optimal
solution grows exponentially with the network size []. Next
we will verify the validity of the previous measurements for
dierent network structures using typical data recommended
by [, ].
(1) Series System. Assuming that a system has components
connected in series conguration, the system will operate
as long as all components are working. For Figure (a), the
failure rates of components , , in the network are
1
0.001,
2
0.003,
3
0.004.When=50, their reliabilities
are, respectively,
1
= 0.95,
2
=0.86,and
3
= 0.82.By
[], the reliability of network system is ()=
1
×
2
×
3
=
0.6703, so the Birnbaum measurements of three components
are as follows.
𝐵
1
(
)
=
1
=
2
×
3
=0.7046
𝐵
2
(
)
=
2
=
1
×
3
=0.7788
𝐵
3
(
)
=
3
=
1
×
2
=0.8187
()
Obviously,
𝐵
1
() <
𝐵
2
() <
𝐵
3
(). Component has more
impact on the system. Increasing or decreasing the failure
of component will be the biggest change to the reliability
of the system, so component is the most important com-
ponent of the system. In addition, the critical importance
of components can be computed based on the Birnbaum
measurements and ().
𝐶𝑀𝐹
1
(
)
=
𝐵
1
(
)
×
1−
1
(
)
1−
(
)
=
𝐵
1
(
)
×
1−
1
1−
=0.1407
𝐶𝑀𝐹
2
(
)
=
𝐵
2
(
)
×
1−
2
(
)
1−
(
)
=
𝐵
2
(
)
×
1−
2
1−
=0.3636
𝐶𝑀𝐹
3
(
)
=
𝐵
3
(
)
×
1−
3
(
)
1−
(
)
=
𝐵
3
(
)
×
1−
3
1−
=0.4501
()
By
𝐶𝑀𝐹
1
() <
𝐶𝑀𝐹
2
() <
𝐶𝑀𝐹
3
() and the denition of
critical importance, the probability of component leads to
the malfunction when the system is failure.