GSTF Journal on Computing (JoC)

, 3:5

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

Operational Analysis Revisited: Error Measure Limits of Assumptions

  • Neal M. BengtsonAffiliated withSchool of Business, Barton CollegeAerospace Engineering, Commputer Science, Management, North Carolina State UniversityIndustrial and Systems Engineering, The Univversity of AlabamaThe School of Industrial Engineering, Purdue University


The assumptions used to develop operational analysis computer performance measures, such as number of jobs at a device or response times, are stated in terms of the data itself, rather than the underlying system which produces the data. In spite of claims of validity and as an aid in introducing queueing theory in teaching, little has been written about operational analysis in the past ten years. Accuracy of operational analysis performance measures depend on data behavior assumptions which can be validated with data based error measures. Increased soundness of the operational analysis approach may be obtained by determining the limits of assumption errors as the time period of observation increases. Part I of this paper is a review of operational analysis and addresses some of the previous concerns with its approach. Part II develops further understanding of operational analysis assumption errors by examining their limits. Limits are found for the assumption errors of job flow balance, homogeneous arrivals and homogenous services. While the job flow balance assumption error measure is shown to approach zero over time, the homogeneity assumption error measures, in general, do not.

Index Terms

assumptions error measures limiting values operational analysis