System Modeling & Simulation July 2016 (2010 Scheme)

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ltcs82
USN
Eighth Semester B.E. Degree Examination, Jume/July 2016
System Modeling and Simulation
Time: 3 hrs.
Max. Marks:100
b.
g.
calls and try to answer questions and solve computer problems. The time between calls
ranges from 1to 4 rninutes with the distribution as shown in Tabie 1.1. Able is rnore
experienced and can provide service faster than Baker, vrhich means that, when both are
idle, Able takes the cal1. The distribution of their service tirrres are shown in Table 1.2 and
Table 1.3 respectively.
Table
l. tr:
t: Inter
lnter arrival
arrwa me A l ) dtstrtbutron
IAT (mins)
I
2
4
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Probability
0.2s
0.40
0.20
0.15
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Table 1.2: Service time distribution of Able
Service time (mins)
2
J
4
5
Frobability
0.30 0.28 0.25 0.i7
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Table 1.3: Service tirne distribution of Baker
a
Service time (rnins)
J
4
5
5
Probability
0.35 a.25 0.20 4.2
Randorn digits for inter-arrival tirnes are : 26,98, 90, 26, 42,74,80, 69,22,49,34, 45,24,34.
Random digits fbr service tirne are :95,21,51,92,89, 38, 13, d1, SCI,49,39,53,88, 01, 81.
Simulate this system for 10 customers, by finding
Average waiting tirne for a customer
ii) Average Inter Arrival tirne
iii) Average service time of Able
iv) Average service time of Baker
v) Average waiting time of those who wait.
(tr2 Marks)
prylain the various concepts used in discrete-event sirnulation with an example. (08 Marks)
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(I0 Marks)
(tr0 Marks)
2 a. A computer technical support center is staffed by twc people, Able and Baker, who take
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a.Withaneatflowchart,explain,,,,ffiusimulaticrnstudy&quot;
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Note: Amswer FIVE fwll qaestions, seleating
at least TWO qwestions fronn each part&quot;
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b.
Explain simulation in Java.
(06 Marks)
A companlz used 6 trucks to haul lxanganese from Kolar to industry. There are two loaders,
to load each truck. After loading, a truck flloves to the weighing scale to be weighed. The
queue discipline is FIFO. When it is weighed, a truck travels to the industry and retums to
follows :
10
5
5
10 15 10 i0 l5
Weiehine Time (mins) 8 t2 B t6 t2 L)o
Travel Time (mins)
30 60 80 40 50 70
End of simulation is completion of four weighing from the scale. Calculate the total busy
time of both loaders, scale, average loaderand scale utilization.,4ssume that fourtrucks are
at the loaders and Two are at the scale, at time &quot;0&quot;. The shopping of simulation is after 10
iterations'.
(tr41V[arks)
tr
of2
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10cs82
b.
c.
What is Poisson process? With example explain the properties of Poisson process. (06 Marks)
Explain the characteristics of a queuing systern.
(08 Marks)
Explain the various steady state parameters of M/G/1 Queue.
(06 Marks)
m
4a.
_-E
Use linear congnrential method to generate a sequence of 5 random numbers, with given
seed27, increment 43, and constant multiplier 17, modulus i00.
(04 Marks)
The sequence of random numbers A.54, A.13,0&quot;98, 0.11 and 0.58 has been generated. Use
K - S test with u : 0.05 to determine if the hypothesis that the numbers are uniformly
distributed on the interval [0, 1] can be rejected. Take Du : 0.565.
(08 Marks)
Test whether the 2no ,9tn , i6tn ........ Nurnbers in the following sequence are auto correlated
c.
g.
b.
:
lo
5a.
co
BAro
ib
by taking cr 0.05. Take Zon: i.96.
0.38, 0.48, 0.35, 0.01, 0.54,0.34,0.95, 0.06, 0.6i, 0.95, 0.49, 0.96, 0.14, 0.96, 0.99, 0.37,
0.49, 0.60, 0.04, 0.83, 0.42, A.83,0.37,0.21, 0.90, 0.99, 0.91, 0.79, CI.77, a.99,0.95, a.21,
0.4i, 0.81, 0.96, 0.3i, 0.09, a.06, a.23, a.71, 0.73, 0.47, 0.13, 0.55, 0.11, 0.75, A36, A.25,
4.23, 4.72,0.60, Ci.84, 0.70, 0.30, 0.26, 0.3 8, 0.05, 0. 19, A.73,
(08 Marks)
A.44.
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6a.
Explain acceptance - re&quot;iection technique for Foissor: distribution. Generate 5 Poisson
variates with mean cr : 0.25. R.andom numbers are: 0.073, 0.693,0.945,0.739,0.014, a342.
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Test whether tlie following data follows Poisson distribution using the chi-square test of
goodness of fit. Srith mean cx, : 0.05. Take l],rr., = 1 i.l
(10 Marks)
1
Arrivals iperiod n
I
2
J
4
5
6 7 8 I
l0 il
a
Frequencv
T2
10 t9 t7 l0 8 7 5 5 J
J
I
ia
b.
1^
U.
(05 Marks)
.p
c.
Explain the replication rnethod for steady - state simulations.
(10 Marks)
Differentiate between point estimation and interv'al estimation.
(05 Marks)
Differentiatq between terrninating and steady state sirnulations by giving one example each.
ed
7a.
a.
**r**
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b.
Explain.components of verification and validation process. Explain with neat dragram,
(12 Marks)
model buiiding, verification and validation process.
(08 Marks)
With neat diagrara, expiain the iterative process of calibrating a model.
2 of2
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