queueing therory q&a.pdf
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Queuing Theory
1
MISRIMAL NAVAJEE MUNOTH JAIN ENGINEERING COLLEGE
DEPARTMENT OF MATHEMATICS
PROBABILITY AND QUEUING THEORY (MA 2262)
SEMESTER-IV
QUESTION BANK IV
UNIT IV QUEUEING THEORY
PART- A
Problem 1 For / /1 : /M FIFO model, write down the Littles Formula.
Solution:
i) S SL W
ii) q qL W
iii)1
S qW W
iv)S qL L
Problem 2 For / / : /M C N FIFO model, write down the Formula fora) Average number of customers in the queue.
b) Average waiting time in the system.
Solution:
a)
0 1 1! 1
n c n c
qL n cC
when
c
b)1
1S SW L
1
1
0
i
n
n
C c n
1
S qL L
Problem 3 What is the probability that a customer has to wait more than 15 minutes toget his service completed in a / /1M M queuing system, if 6 per hour 10 perhour?
Solution:
Probability that the waiting time in the system exceeds t is
W t
t
e dW e
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Queuing Theory
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1
1 0 6 .14
150.3679
60SP W e e
Problem 4 What is the probability that an arrival to an infinite capacity 3 server Poisson
queueing system with 2
and 0
1
9P entries the service without waiting.
Solution:
P[Without waiting] 0 1 23P N P P P
0
1
!
n
nP P
n
when 3n c .
21 2 1 1 5
3 29 9 2 9 9
P N .
Problem 5 In a given / /1 : /M FCFS queue, 0.6 , What is the probabilitythat the queue contain 5 or more students?
Solution:
555 0, 6 0.0467P X
Problem 6 What is the effective arrival rate for / /1 : 4 /M FCFS queuing model
when 2 and 5
Solution:
1 1
0 1 5
1 / 1 2 / 55 1
1 / 1 2 / 5K
5
3 / 5 0.65 1 5 1
1 0.010241 2 / 5
0.6
5 1 5 1 0.6070.989
5 0.393 1.965 2
Problem 7 a) In / /1 : /M K FIFO write down the expression for P0.
b) In / /1 : / , 3/ , 4 / , 7M M K FIFO hr hr K Calculate P0Solution:
a) 0 1
1
1
KP of
1
1of
K
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b) 0 11
1
KP of
8
3
41 0.27783
14
Problem 8 In / / : / , 10 / , 15 / , 2M M S FIFO hr hr S Calculate P0
Solution:1
1
0
0
1 1! !
n s
S
n
sPn S s
12
1 10 1 10 301
1! 15 2! 15 30 10
1
2
Problem 9 In a two server system with infinite capacity and 20 / hr and 11/ hr ,
find P0.
Solution:1
1
0
0
1 1
! !
n sS
n
sP
n S s
12
20 1 20 11 21
11 2 11 22 20
1
21
Problem 10 Write the steady states equations in / /1 : /M K FIFO where
0,1,2... 1n for n K
0 for n k
1,2,3nand n
Solution:
1 1 1 1n n nP P P n K
1 0 0P P n
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Queuing Theory
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Problem 11 In / /1 : / , 3/ , 5 / , 7M M K FIFO hr hr K , what is theprobability that the server will be idle.
Solution:
The probabilities that the server will be idle
0 1 8
3 21 10.45 5 0.407
1 0.0168 0.983311
5
KP
Problem 12 In / / : / ,M S K FIFO write the expression for P0.
Solution:
11
0
0
1 1/ /
! !
n ss k
n s
n n s
Pn s s
Problem 13 What is effective arrival rate in / / : /M M S K FIFO
Solution:
Effective arrival rate
1
1
0
s
n
n
s s n
Problem 14 / / : /In M M S K FIFO with
3.76 / 4, 2, 7,hr and s k compute 5P where 0 0.3617P .
Solution:
5 01
/!
n
n sP P
s s
5
5 2
1 3.760.3617
2!2 4
0.0166
PART-B
Problem15 A repairman is to be hired to repair machines which break down at an
average rate of 3 per hour. The breakdown follows Poisson distribution. Non- productive
time of machine is considered to cost Rs.16/hr. Two repairmen have been invited. One is
slow but cheap while the other is fast and expensive. The slow repairman charges Rs.8
per hour and he services machines at rate of 4 per hour. The fast repairman demands
Rs.10 per hour and service at the average rate of 6 per hour. Which repair man should be
hired?
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Solution:
For the slow man: Model / /1 : / 3 / , 4 /M FIFO Hr hr
Expected waiting time of a machine 1 1 14 3
hr
Non productive cost =16 / hr
Non productive cost = 3 16 =Rs.48.Charges paid to the repairman 8 3 24 Total cost =48+24=72
For fast man: M
3 / , 6 / .hr hr
Expected waiting time1 1
3
hour
Non productive cost 13 16 163
Charge paid to repairman 10 1 10 Total cost =16+10=26Fast repairman can be hired.
Problem 16 A two person barber shop has 5 chairs to accommodate waiting customers.
Customers who arrive when all 5 chairs are full leave without entering barber shop.
Customers arrive at the average rate of 4 per hour and spend an average of 12 minutes in
the barbers chair. Compute 0 1,P P and average number of customers in the queue
Solution: This is model / / : / 0 4 / , 5 / , 2, 2 5 7M M C K FIF hr hr C N
1 7
0 20 2
12 5
1 1 1/ /
! ! 2
4 8 2 2 21 1 ...
5 25 5 5 5
0.4287
i
n n
nn n
Pn C
01
/ , 0!
n n cP P n
C C
7
7 7 2
1 4 / 5 0.42872 2!
P
0.0014.
0 2 1 1
! 1
C
C N C
q
PCL P N C
C
Where / C
2 5 5
2
0.40.4287. 0.8 1 0.4 5 0.6 0.4
2! 1 0.4
0.15 Customers
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Problem 17 Derive the formula for
i) Average number qL of customers in the queue.
ii) Average waiting time of a customer in the queue for / /1 : /M M FIFO MODEL.
Solution:
1 1 1
1q n n nn n n
L n P nP P
0 01 0 0
1n n nn n n
nP P P nP P
01sL P
2
1 1
ii) Average waiting time of a customer is the queue qW
0
w
qW W e dw
where
/ e w
is the probability density
function of the waiting time distribution of the queue.
0
.w
w e dw
00
w w
e e dwW
1
Problem 18 On average 96 patients over 24 hour day require the service of an
emergency classic. Also on average a patient requires 10 minutes of active attention.
Assume that the facility can handle any one emergency at a time. Suppose that it costs the
clinic Rs.100 per patient treated to obtain an average servicing time of 10 minutes and
that each minute of decrease in this average time would cost Rs.10 per patient treated.How much would have to be budgeted by the clinic to decrease the average size of the
queue from1
13
patient to1
2patient?
Solution: This is / /1 : /M M FIFO model96
4 /24
hr .
6 / hr
4 1. 1
3 3qL
Now1
13
customers to be reduced to1
2, then we have to find 1 such that
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2 11 4 32 02
ie
1 1 1
8 4 0 8 Patient /hr
Average time required to each patient'1 15
8 2hr
Decrease in the time required to attend a patient15 5
102 2
min.
Decrease in each minute cost Rs.10 per patient.
Cost5
10 252
.
Budget required for each patient= 100+25=125 to decrease the size of the queue.
Problem 19 Obtain the expressions for steady state probability of a M/M/C queuingsystem
Solution:
1n n n C
C n c
It can be treated as a birth death process with n for all n and n
is given by (1)
In a birth death process
1
01
ni
n
i
P Pi
and
1
1
0
1
1
1
ai
n i
n
P
i
for M/M/C.
0 110
1 2 1
.... nnn
P P
0... 1
1 2
nP
n if n C
0
1n
nof n c
ni P
1 .......... 1
1 2 1
n
n
c cP c if n c
n c
1.... 1 1
1 2
nn c
c c
1
!
nn
n
C of n cC
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Queuing Theory
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1
0
0 ! !
n nC
n c nn n cn
Pn c c
Problem 20 Arrivals at a telephone booth are considered to be Poisson with an average
time of 12 mins. The length of a phone call is assumed to be distributed exponentially
with mean 4 min. Find the average number of persons waiting in the system. What is the
probability that a person arriving at the booth will have to wait in the queue? Also
estimate the traction of the day. Where phone will be in use
Solution: This is model / /1 : /M FIFO
112, 12
per min
1 14,4
per min
1
12 0.5.1 1
4 12
SL
0 1 0 1S sP L P t P [No customer in the system]
01
1 1 1 / / .3
P
P Phone will be idle = 0213
P
P Phone will be in use =1
3Problem 21 There are three typists in an office. Each typist can type an average of 6letters per hour. If letters arrive for being typed at the rate of 15 letters per hour, what
fraction of time all the typists per hour will be busy? What is the average number of
letters waiting to be types?
Solution: This is / / : /M M C FIFO
3, 15 / , 6 /C hr hr P [all the three typists buy] 3P N
3
0
3! 13
P
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3
0 1
0
1
1 1
!! 1
r
n
P
n
nc
c
32 2.5
1
2.5 11 2.5
152!3! 1
6 3
0.0449.
3 0.7016P N 1
02
. ! 1
c
qL P
c c
4
2.50.0449 3.5078
253 6 1 2
3
Problem 22 A bank has two tellers working are savings account. The first teller handles
with drawals only the second teller handles deposits only. It has been found that the
service time distributions for both deposits and withdrawals are exponential with mean
service time of 3 minutes per customer. Depositors are found to arrive in a poisson
fashion through out the day with mean arrival rate of 16 per hour withdrawals also arrivein a poisson fashion with mean arrival rate of 14 per hour. What would be the effect on
the average waiting time for the customers if each teller could handle both withdrawals
and deposits?
Solution:
1. When the tellers handle separately withdrawals and deposits. This is Model
/ /1 : /M FIFO
.For depositors 16 / , 20 /hr hr
1
12min5
qW hr
For withdrawals 14 / , 20 /hr hr
7minqW
ii) If both tellers do both service, one it will be a / /1 : /M FIFO model.2 20 / 16 14 30 /C hr hr
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Queuing Theory
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11
0
0
1 1
! !
n ci
n
cP
n c c
12
30 1 30 40 11
20 2 20 40 30 7i
2
02 2
30
1 1 1 1 120
. ! 20 2.21 73011
40
c
qW Pc c
c
0.0642 3.857hr or
Problem 23 In a heavy machine shop, the overhead crane is 75% utilized. Time studyobservations gave the average slinging time as 10.5 minutes with a SD of 8.8 minutes.
What is the average calling rate for the service of the crane and what is the average delay
in getting service? If the average service time is cut to 8.0 minutes, with a standarddeviation of 6.0 minutes, how much reduction will occur on average in the delay ofgetting service?
Solution: This is model / /1 : /G FIFOAverage delay is getting service
2 21
/2 1 p
0.75, 5.71/ , 8.8.hr
220.75 8.8 60
1 5.712 1 0.75 60 5.71
Average calling rate 0.75 5.71 4.28 per hr. If the service time is cut to
8 minutes, then60 4.29
7.5 / , 0.5718 7.5
hr
utilization of the crane reduced to 57.1 percent and average delay in getting service
220.571 600 601 7.5
2 1 0571 60 7.5qW
8.3 minutes.
a reduction of 18.5 minutes approximately 70%
Problem 24 A Super market has two girls ringing up sales at the customers. If the servicetime for each customer is exponential with mean 4 minutes and if the people arrive in aPoisson fashion at the rate of 10 per hour
a) What is the probability of having to wait for service?
b) What is the expected percentage if idle time for each girl?
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Solution:
This is model / / : /M C FIFO
1 1 1, ; 2 .6 4 3
CC
121
0
0
1 4 1 4 2.1/ 4 1
! 6 2! 6 2.1/ 4 1/ 6 2
nc
n
Pn
1 0
2 1 1.
3 2 3P P
a) 2
1 1 12 1
2 3 6cP C Pc
b) Probability of any girl being idleExpected number of idle girls
Total number of girls .
0 1
1 12 1
2 1 42 3 0.672 6
P P
C
Hence expected percentage of idle time each girl is 67%.
Problem 25 At a one man barber shop, the customers arrive following poisson process at
an average rate of 5 per hour and they are serviced according to exponential distribution
with an average service. Rate of 10 minutes assuming that only 5 seats are available for
waiting customers find the average time a customer spends in the system.
Solution:
This is model / /1 : /M N FIFO
5 / .hr 1
60 6 510
per hour N
5
6P
0 61
51
1 0.16666 0.2505.
1 0.6651516
NP
SS
LW where
1 6
6
51 6
5 6
6 5 51 1 1
6
n
S
n
L
n
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Queuing Theory
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6.0335 2.015 5 198
1 0.335 0.665
'
01 P 6 1 0.2505 4.497
'
1 1.980.441
4.497s SW L hrs
Problem 26 At a railway station, only one train is handled at a time. The railway yard issufficient only for two trains to wait while the other is given signal to leave the station.
Trains arrive at the station at an average of 12 per hour. Assuming poisson arrivals and
exponential service distribution, find the steady state probabilities for the number of
trains in the system also find the average waiting time of a new train coming into the
yard. If the handling rate is reduced to half, what is the effect of the above results?
Solution:
This is Model / /1 : /M M K FIFO
Hence 6 / , 12 / , 3hr hr k
Steady state probability for the number of trains in the system 1 2 3,P P and P .
0 0 1
1
1
n
n KP P when P
4 4
61 0.5 0.512 0.53330.93751 0.56
112
1
1 0 0.2667P P
2
2 0P P
= 0.1334
3
3 0 0.0667P P
Average waiting time of a new train coming in the yard is1
s SW L
where
1
1
1
1
K
s K
K
L
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4
4
4 0.560.7333.
12 6 1 0.5
1 1 12 1.05333 5.6004c
0.73330.1309
5.6004sW hrs
Case II
If the handling rate is reduced to half, then 6 / , 6 / 3hr hr and k
Hence1 1
1 4nP
k
1 2 3
1
4
P P P
Average waiting time of a new train coring into the yard in
1
ss
LW
3
1.52 2
s
KL Since train
1 01
1 6 1 4.54
P
1
1
1.50.333 ( 20 )
4.5
ss
LW hrs or
Problem 27 At a port there are 6 unloading berths and 4 unloading crews. When all the
berths are full, arriving ships are diverted to an overflow facility 20 kms down the river.
Tankers arrive according to a poisson process with a mean of 1 for every 2 hrs. If it takes
for an unloading crew on the average, 10 hrs to unload a tanker, the unloading time
follows an exponential distribution Determine.
a) How many tankers one of the port on the average?b) How long does a tanker spend at the port as the average?
Solution:1
1 0 0.0361P P
2
2 0
10.0901
2!P P
3
3 0
10.1502
3!P P
4.8214 4 0.00721 3 0.0361 2 0.0901 0.1502 4.3539sL tankers.b) Time spend by a tanker at the port
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Queuing Theory
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1
1
10
1 c
S S n
n
W L Where C c n
1 0 1 2 34 3 2S P P P P
1
4 4 0.00721 3 0.0361 2 0.0901 0.150210
0.35324.3539
12.32500.3532
SW
Problem 28 A petrol pump has 2 pumps. The service time follows the exponential
distribution with a mean of 4 minutes and ears arrive for service in a poisson process at
the rate of 10 cars per hour. Find the probability that a customer has to want for service.
What proportion of time the pumps remain idle?
Solution:
This is model / / : /M C FIFO
1 410 / 15 / 2
60hr is hr C
P[ a customer has to wait ] P n c
0
! 1
c
c
P
C
2
0
10
152
102! 1
30
P n P where
11
0
0
1 1
! !
n cc
n
cP
n c c p
12
1 10 1 10 30
1 1! 15 2! 15 30 10
1
2 1 11
3 3 2
Probability that a customer has to want in
22
1 132 . 0.1667
2 2 62.
3
P n
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The traction of time when the pumps are busy =traffic intensity10 1
30 3c
Hence the pumps remain idle 1 1 2
1 67%3 3
Problem 29 A supermarket has two girls serving at the customers. The customers arrivein a Poisson fashion at the rate of 12 per hour. The service time for each customer is
exponential with mean 6 minutes. Find
i) The probability that an arriving customer has to want for service.
ii) The average number of customers in the system, andiii)The average time spent by a customer in the supermarket.
Solution: This is / / : /M M C FIFO . Here
1 612 / , 10 / , 2
60X hr hr c
i) Probability that an arrival customer has to wait is
0
1
C
P
P n c
Cic
2 1
0
12 1 12 20 1
10 2! 10 20 12 4
P
212 1
10 42 0.45
122! 1
20
P n
The probability that an arrival customer has to want=0.45
ii) Average number of customer is the system
1
021. !
1
c
sL Pc c
c
3
2
12
1 1 12101.875 2
2.2! 4 10121
20
customer
iii) Average time spent by a customer in the supermarket =Average waiting time
of a customer in the system
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1 1.8750.1563 9.375
12
s sW L hours
minutes.
Problem 30 Four counters are being run on the frontier of a country to check the
passports of the tourists. The tourists choose a counter at random. If the arrival at the
frontier is poisson at the rate and the service time is exponential with parameter2
,
find the steady average queue at each counter.
Solution:
This is / / : /M C FIFOAverage queue length
02
1
. !1
qL Pc c
c
1
3
0
0
1 1
!
n c
n
cP
n Ci c
12 3
42 2 1 21 2 22 6 4! 2
3
23
2
1 25 3 40.1739
4.4! 23 231
2
qL
Problem 31 In a given M/M/1 queuing system the average arrivals is 4 customers per
minutes 0.7 what are
1) Mean number of customers sL in the system
2) Mean number of customers qL in the queue.
3) Probability that the service is idle.
4) Mean waiting timesW in the system.
Solution:
0.7 0.72.33.
1 1 0.7 0.3sL
2.333 0.7 1.633.q sL L
0 1 1.07 0.3P
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2.3330.583
4
ss
LW
Problem 32 A TV repairman finds the time spend on his job has an exponentialdistribution with mean 30.If he repairs sets in the model in which they come in and of
the arrival of sets is approximately poisson with an average rate of 10 sets per 8 hoursday, what is the repairmans expected idle time each day ? How many jobs ahead of the
average set just brought in?
Solution:
We are given10 5
8 4 sets per hour
160 2
30 sets per hour
Then5
8
The probability of no unit in the queue is 05 3
1 18 8
P
Hence the idle time for repair man in an 8-hours day3
8 38
hrs
524 1
5 32
4
sL
jobs = 2 TV Sets (approx)
Problem 33 If for a period of 2 hours in the day trains arrive at the yard every 20minutes but the service time continuous to remain 36 minutes. Calculate the following forthe above period.
i) The Probability that the yard is empty
ii) The average number of trains on the assumption that the line capacity of the yard
is limited to 4 trains only.
Solution:
This model is / /1 : /M K FIFO Hence1
20 per min;
1
36 per min ,
4K .i) Probability that the yard is empty
0 1
1
,
1
KP
5
361
20 0.044736
120
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ii) Average number of trains
1
1
1
1
K
S K
K
L of
5
5
1 365
20 203027
1 1 361
36 20 20
=3 trains.
Problem 34 Suppose there are 3 typists is a typing pool. Each typist can type an averageof 6 letters / hr. If letters arrive to be typed at the rate of 15 letters/hr
a) What is the probabilities that there is only one letter in the system
b) What is the average number of letters waiting to be typed?
c) What is the average time a letter spends in the system?
Solution:
This is / / : /M S FIFO1
1
0
0
1 1
! !
n ss
n
sP
n s s
132
0
1 15 1 15 18
! 6 3! 6 18 5
n
n n
11 18
1 2.5 3.125 15.6256 3
0.04494.
a) 1 01
!
n
P P Since n sn
11 15
0.04494 0.112351! 6
b) Average numbers of letters waiting to be typed1
02
1
!1
S
qL Pss
s
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4
2
15
1 60.04494
3.3! 15118
3.51094 .Letters
C)1
s sW L
1qL
1 153.51094 0.40073
15 6hr
24.0438 .
Problem 35 An automobile inspection station has 3 inspection stalls. Assume that cans
wait in such a way that when a stall becomes vacancy the car at the head of the time pullsup to it. The Station can accommodate at most 4 cars waiting at one time. The arrival
pattern is poisson with a mean of I car every minute during the peak hours. The service
time is exponential with mean 6 min. Find the average number of customers is the queue
during peak hours and the average waiting time in the queue.
Solution:
This is / / : /M C K FIFO Model.
3, 7.c k 60 / 10 / .hr hr
11
0
0
1 1
! !
m C m ci k
m m v
Pm C c
132 7
3
0 3
1 1 66 6
! 3! 3
mm
m mm
1
2 3 2 3 41 11 6 6 6 1 2 2 2 22! 3!
7 1
7 18 36 31 1141 0.000.8764
i) Average no of customer is the queue.
0 2
11 1
! 1
c
K C K C
qL P K Cc
62
3Where
c
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3 4 42
2 16 .0.0008764 1 2 4 1 2 2
3! 1 2
3.09ii) Average waiting time in the queue.
1
'
'0
1 c
q q m
m
W L where c c m P
2
1
0
10 3 3 mm
m P
0 1 210 3 3 2P P P
10 3 3 0.00087 2 0.005256 0.015768
29.76 30 3.09
0.103 .30
qL hrs
0
1; 3
!
n
nHence P P n cn
1
1
16 0.0008764
1!P 0.005256
2
2
16 0.00087
2!P 0.015768
Problem 36 Patients arrive at a clinic according to Poisson distribution at a rate of 60patients per hour. The waiting room does not accommodate more than 14 patients
Investigation time per patient in exponential with mean rate of 40 per hour.
a) Determine the effective arrival rate at the clinic.
b) What is the probability that an arriving patient will not wait?
c) What is the expected time (waiting) until the patient is discharged from theclinic?
Solution: This is / / : /M I K FIFO model hence 60 patients / hr,40 / . 14 1 15hr K
a) Effective arrival rate
1 01 P
Where 0 1
1
1
KP of
6
601
40 0.000762460
140
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Queuing Theory
21
1 40 1 0.0007624 39.9695 / hr b) An arrived will rut want =there is no patient is the clinic.
P[ a patient will not wait ] 0 0.0007624P c) Effective waiting time
1
SS
LW
1
1
1
1
K
S K
K
When L
16
16
6016
60 4040 60 60
140
2 16.00 14 Patient
14
0.3503 21.01839.9695
sW hr or
Problem 37 A group of users in a computer browsing centre has 2 terminals. The
average computing job requires 20 min of terminal time and each user requires some
computation about once every half an hour .Assume that the arrival rate is poisson and
service rate is exponential and the group contains 6 users. Calculatea) The average number of users waiting to use one of the terminals and in the
computing job.
b) The total time lost by all users per day when the centre is opened 12 hrs/day.
Solution:
This is / / : /M S K FIFO Hence1 30 1 1 20 1
;60 2 60 3
2 / , 3 / 2, 6hr hr s k
a) The average number of users waiting to use terminals and in the
Computing job is nothing but me average number of uses in the system.
1
0
S
S q n
n
L L S S n P
1
1
0
0
1 1
! !
n s n sS k
n n s
Pn S s
12 2 3 4
2 1 2 1 1 1 11 1
3 2! 3 3 3 3 3
0.5004
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Queuing Theory
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0 2 1 1
! 1
s
K S k s
qL P y K S Where ysS
2 4 4
2
1
2 1 2 130.5004 . 1 43 3 3 32
2!3
0.0796
1
0
s
S q n
n
L L S S n P becomes
0 12qL S P P
0 02qL S P P
2
0.0796 2 2 0.5004 0.50043
0.7452 .
b) Average waiting time of a user in the queue qW
1
11
0
0 1
1
1
22 3 2 2 0.5004 0.5004
3
1.9968
1 0.07960.0399
1.9968
q q
S
n
n
q q
W L where
S S n P
S P P
W L hr
Problem 38 The railway marshalling yard is sufficient only for trains (there are 11
lines one of which is earmarked for the shutting engine to reverse itself from the crest ofthe hump to the rate of the train). Train arrive at the rate of 25 trains per day, inter-arrival
time and service time follow exponential distribution with an average of 30 minutes
Determine.a) The probability that the yard is empty.
b) The average queue length.
Solution:
This is model / / : /M K FIFO
Hence 25 trains /day,1
30 0.0333
train /min
0.0174
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10 11 1K a) Probability that the yard is empty.
0 1
1
1
KP if
11 11
0.01741
1 0.52250.0333 0.47791 0.52250.0174
10.0333
c) Average queue length.
1
1
1
1
K
S K
K
L of
11
11
0.017411
0.0174 0.0333
0.0333 0.0174 0.01741
0.0333
0.008721
1.09434 .0.9992
1.0856
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