MA8402- PROBABILITY AND QUEUING THEORY Syllabus 2017 Regulation

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MA8402- PROBABILITY AND QUEUING THEORY Syllabus 2017 Regulation

MA8402- PROBABILITY AND QUEUING THEORY Syllabus 2017 Regulation

MA8402                         PROBABILITY AND QUEUING THEORY                       L T P C                                                                                                                             4 0 0 4

OBJECTIVES:

  • To provide necessary basic concepts in probability and random processes for applications such as random signals, linear systems in communication engineering.
  • To understand the basic concepts of probability, one and two dimensional random variables and to introduce some standard distributions applicable to engineering which can describe real life phenomenon.
  • To understand the basic concepts of random processes which are widely used in IT fields.
  • To understand the concept of queueing models and apply in engineering.
  • To understand the significance of advanced queueing models.
  • To provide the required mathematical support in real life problems and develop probabilistic models which can be used in several areas of science and engineering.

UNIT I PROBABILITY AND RANDOM VARIABLES     12

Probability – Axioms of probability – Conditional probability – Baye‘s theorem – Discrete and continuous random variables – Moments – Moment generating functions – Binomial, Poisson, Geometric, Uniform, Exponential and Normal distributions.

UNIT II TWO – DIMENSIONAL RANDOM VARIABLES                                                                                            12

Joint distributions – Marginal and conditional distributions – Covariance – Correlation and linear regression – Transformation of random variables – Central limit theorem (for independent and identically distributed random variables).

UNIT III RANDOM PROCESSES                                   12

Classification – Stationary process – Markov process – Poisson process – Discrete parameter Markov chain – Chapman Kolmogorov equations – Limiting distributions.

UNIT IV QUEUEING MODELS                                      12

Markovian queues – Birth and death processes – Single and multiple server queueing models – Little‘s formula – Queues with finite waiting rooms – Queues with impatient customers : Balking and reneging.

UNIT V ADVANCED QUEUEING MODELS                   12

Finite source models – M/G/1 queue – Pollaczek Khinchin formula – M/D/1 and M/EK/1 as special cases – Series queues – Open Jackson networks.

                                                                                                     TOTAL : 60 PERIODS

OUTCOMES:

Upon successful completion of the course, students should be able to:

  • Understand the fundamental knowledge of the concepts of probability and have knowledge of standard distributions which can describe real life phenomenon.
  • Understand the basic concepts of one and two dimensional random variables and apply in engineering applications.
  • Apply the concept of random processes in engineering disciplines.
  • Acquire skills in analyzing queueing models.
  • Understand and characterize phenomenon which evolve with respect to time in a
    probabilistic manner

TEXTBOOKS:

1. Gross, D., Shortle, J.F, Thompson, J.M and Harris. C.M., ―Fundamentals of Queueing Theory”, Wiley Student 4th Edition, 2014.
2. Ibe, O.C., ―Fundamentals of Applied Probability and Random Processes”, Elsevier, 1st Indian Reprint, 2007.

REFERENCES :

1. Hwei Hsu, “Schaum‘s Outline of Theory and Problems of Probability, Random Variables and Random Processes”, Tata McGraw Hill Edition, New Delhi, 2004.
2. Taha, H.A., “Operations Research”, 9th Edition, Pearson India Education Services, Delhi, 2016.
3. Trivedi, K.S., “Probability and Statistics with Reliability, Queueing and Computer Science Applications”, 2nd Edition, John Wiley and Sons, 2002.
4. Yates, R.D. and Goodman. D. J., “Probability and Stochastic Processes”, 2nd Edition, Wiley India Pvt. Ltd., Bangalore, 2012.

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