Poisson Processes

  • Shunji Osaki


As shown in Section 2.1, a stochastic process can be described by the laws of probability at each point of time t ≥ 0. As shown in Fig. 2.1.1, we are very much interested in the random variable N(t), which denotes the number of arriving customers up to time t,where N(t) = 0, 1, 2,…. A counting process {N(t), t≥ 0} is one of the stochastic processes, and Fig. 2.1.1 shows a “sample function” or “sample path” of the counting process {N(t), t ≥ 0}. We can consider several examples of counting processes, where the “customer” is replaced by other relevant words such as the “call” in congestion theory, the “failure” of machines, and the arriving “job” or arriving “transaction” of computer systems.


Poisson Process Interarrival Time Counting Process Probability Mass Function Stationary Increment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin · Heidelberg 1992

Authors and Affiliations

  • Shunji Osaki
    • 1
  1. 1.Department of Industrial and Systems Engineering, Faculty of EngineeringHiroshima UniversityHigashi-Hiroshima 724Japan

Personalised recommendations