Probability and Queuing Theory syllabus
AIM
The probabilistic models are employed in countless applications in all areas of science
and engineering. Queuing theory provides models for a number of situations that arise in
real life. The course aims at providing necessary mathematical support and confidence
to tackle real life problems.
OBJECTIVES
At the end of the course, the students would
UNIT I RANDOM VARIABLES
Discrete and continuous random variables - Moments - Moment generating functions
and their properties. Binomial, Poisson ,Geometric ,Negative binomial, Uniform,
Exponential, Gamma, and Weibull distributions .
UNIT II TWO DIMENSIONAL RANDOM VARIABLES
Joint distributions - Marginal and conditional distributions – Covariance - Correlation and
regression - Transformation of random variables - Central limit theorem.
UNIT III MARKOV PROCESSES AND MARKOV CHAINS
Classification - Stationary process - Markov process - Markov chains - Transition
probabilities - Limiting distributions-Poisson process.
UNIT IV QUEUEING THEORY
Markovian models – Birth and Death Queuing models- Steady state results: Single and
multiple server queuing models- queues with finite waiting rooms- Finite source models-
Little’s Formula
UNIT V NON-MARKOVIAN QUEUES AND QUEUE NETWORKS
M/G/1 queue- Pollaczek- Khintchine formula, series queues- open and closed networks
TEXT BOOKS
1. O.C. Ibe, “Fundamentals of Applied Probability and Random Processes”,
Elsevier, 1st Indian Reprint, 2007 (For units 1, 2 and 3).
2. D. Gross and C.M. Harris, “Fundamentals of Queueing Theory”, Wiley
Student edition, 2004 (For units 4 and 5).
REFERENCES:
1. A.O. Allen, “Probability, Statistics and Queueing Theory with Computer Applications”, Elsevier, 2nd edition, 2005.
2. H.A. Taha, “Operations Research”, Pearson Education, Asia, 8th edition, 2007.
3. K.S. Trivedi, “Probability and Statistics with Reliability, Queueing and Computer Science Applications”,
John Wiley and Sons, 2nd edition, 2002.
The probabilistic models are employed in countless applications in all areas of science
and engineering. Queuing theory provides models for a number of situations that arise in
real life. The course aims at providing necessary mathematical support and confidence
to tackle real life problems.
OBJECTIVES
At the end of the course, the students would
- Have a well – founded knowledge of standard distributions which can describe real life phenomena.
- Acquire skills in handling situations involving more than one random variable and functions of random variables.
- Understand and characterize phenomena which evolve with respect to time in a probabilistic manner.
- Be exposed to basic characteristic features of a queuing system and acquire skills in analyzing queuing models.
UNIT I RANDOM VARIABLES
Discrete and continuous random variables - Moments - Moment generating functions
and their properties. Binomial, Poisson ,Geometric ,Negative binomial, Uniform,
Exponential, Gamma, and Weibull distributions .
UNIT II TWO DIMENSIONAL RANDOM VARIABLES
Joint distributions - Marginal and conditional distributions – Covariance - Correlation and
regression - Transformation of random variables - Central limit theorem.
UNIT III MARKOV PROCESSES AND MARKOV CHAINS
Classification - Stationary process - Markov process - Markov chains - Transition
probabilities - Limiting distributions-Poisson process.
UNIT IV QUEUEING THEORY
Markovian models – Birth and Death Queuing models- Steady state results: Single and
multiple server queuing models- queues with finite waiting rooms- Finite source models-
Little’s Formula
UNIT V NON-MARKOVIAN QUEUES AND QUEUE NETWORKS
M/G/1 queue- Pollaczek- Khintchine formula, series queues- open and closed networks
TEXT BOOKS
1. O.C. Ibe, “Fundamentals of Applied Probability and Random Processes”,
Elsevier, 1st Indian Reprint, 2007 (For units 1, 2 and 3).
2. D. Gross and C.M. Harris, “Fundamentals of Queueing Theory”, Wiley
Student edition, 2004 (For units 4 and 5).
REFERENCES:
1. A.O. Allen, “Probability, Statistics and Queueing Theory with Computer Applications”, Elsevier, 2nd edition, 2005.
2. H.A. Taha, “Operations Research”, Pearson Education, Asia, 8th edition, 2007.
3. K.S. Trivedi, “Probability and Statistics with Reliability, Queueing and Computer Science Applications”,
John Wiley and Sons, 2nd edition, 2002.