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Unit 11: Queuing Theory




          1.   Probability that an arrival is observed during a small time interval (say of length v) is  Notes
               proportional to the length of interval. Let the proportionality constant be  , so that the
               probability is  v.
          2.   Probability of two or more arrivals in such a small interval is zero.
          3.   Number of arrivals in any time interval is independent of the number in non-
               overlapping time interval.
          These assumptions may be combined to yield what probability distributions are likely to be,
          under Poisson distribution with exactly n customers in the system.

          Suppose function P is defined as follows:
          P (n customers during period t) =  the probability that n arrivals will be observed in a time
                                       interval of length t

                                          
                                        
          then,                P (n, t) =      (n = 0, 1, 2,……………)                  (1)
          This is the Poisson probability distribution for the discrete random variable n, the number of
          arrivals, where the length of time interval, t is assumed to be given. This situation in queuing
          theory is called Poisson arrivals. Since the arrivals alone are considered (not departures), it is
          called a pure birth process.
          The time between successive arrivals is called inter-arrival time. In the case where the number
          of arrivals in a given time interval has Poisson distribution, inter-arrival times can be shown to
          have the exponential distribution. If the inter-arrival times are independent random variables,
          they must follow an exponential distribution with density f(t) where,

                                  f (t) = e   (t > 0)                              (2)
                                         –t
          Thus for Poisson arrivals at the constant rate   per unit, the time between successive arrivals
          (inter-arrival time) has the exponential distribution. The average Inter - arrival time is denoted
          by   .
          By integration, it can be shown that E(t) =                              (3)
          If the arrival rate  = 30/hour, the average time between two successive arrivals are 1/30 hour
          or 2 minutes.
          For example, in the following arrival situations, the average arrival rate per hour,   and the
          average inter arrival time in hour, are determined.
          1.   One arrival comes every 15 minutes.

               Average arrival rate, l =   = 4 arrivals per hour.

               Average inter arrival time    = 15 minutes = ¼ or 0.25 hour.
          2.   Three arrivals occur every 6 minutes.
               Average arrival rate, l = 30 arrivals per hour.

               Average Inter-arrival time,   =   = 2 minutes =   or 0.33 hr.











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