2 FOURTH SEMESTER

WELCOME

SUBJECT CODE - MA1252 SUBJECT - PROBABILITY AND QUEUEING THEORY

OBJECTIVES

By the end of this paper, the student should be able to:

Recognize and understand Probability distribution functions, in general.

Calculate and interpret expected values. Recognize the probability distribution and

apply it appropriately. Recognize the joint probability

distribution and apply it appropriately (optional).

Recognize the queues and queueing network apply it appropriately (optional).

TEACHING PLAN

UNIT-I - 14 HRSUNIT-II - 12 HRSUNIT-III - 13 HRSUNIT-IV - 14 HRSUNIT-V - 14

HRS

TOTAL - 67 HRS

UNIT-I RANDOM VARIABLE & DISTRIBUTION FUNCTION RANDDOM VARIABLE CONTINUOUS RANDOM VARIABLE PROBABILITY DENSITY FUNCTION CUMULATIVE DISTRIBUTION FUNCTION DISCRETE RANDOM VARIABLE PROBABILITY DISTRIBUTION FUNCTION CUMULATIVE DISTRI BUTION FUNCTION MOMENT GENERATING FUNCTION PROPERTIES

DISTRIBUTION FUNCTION

BINOMIAL GEOMETRIC NEGATIVE BINOMIAL UNIFORM EXPONENTIAL GAMMA WEIBULL

UNIT-IITWO DIMENSIONAL R.V’S TWO DIMENSIONAL RANDOM

VARIABLES JOINT PROBABILITY DISTRIBUTION MARGINAL PROBABILITY

DISTRIBUTION COVARIANCE CORRELATION AND REGRESSION TRANSFORMATION OF RANDOM

VARIABLES CENTRAL LIMIT THEOREM

http://en.wikipedia.org/wiki/File:Dic_fundamentals.jpg

UNIT-IIIMARKOV PROCESSES & MARKOV CHAIN RANDOM PROCESSES STATIONARY PROCESSES MARKOV CHAIN KOLMOGROV DIFFERENTIAL

EQUATION TRANSISTION PROBABILITY POISSON PROCESSES

UNIT-IVQUEUEING THEORY MARKOVIAN MODELS SIMPLE QUEUE KENDALL’S NOTATION SINGLE SERVER QUEUEING

MODEL MULTI SERVER QUEUEING

MODEL FINITE SOURCE QUEUEING

MODEL

SIMPLE QUEUE

MULTIPLE QUEUE

UNIT-VNON-MARKOVIAN QUEUE & QUEUE NETWORK NON-MARKOVIAN QUEUEING

MODEL POLLACZEK-KHINTCHINE

FORMULA QUEUEING NETWORK OPEN QUEUEING NETWORK CLOSED QUEUEING NETWORK

CLOSED QUEUEING NETWORK

OPEN QUEUEING NETWORK

TEXT & REFERENCE BOOKS:

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