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Author Suri, Rajan
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©1987
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Abstract A rigorous extension of the recent perturbation analysis approach to more general discrete event systems is given. First, a general class of systems and performance measures is defined, and some basic reprsentational and linearity properties are derived. Next a sample gradient of performance with respect to a parameter of the system is defined. Then, for certain parameters of such systems, an infinitesimal perturbation analysis algorithm is derived. It is proved that this algorithm gives $\textit{exact}$ values for the sample gradients of performance with respect to the parameters, by observing only $\textit{one}$ sample path of the DEDS. (However, the sample gradient may or may not be a good estimate of the gradient of the performance measure; this point is elaborated in the body of the paper.) The computational complexity of this algorithm is bound to be linear in the number of events. These results offer the potential for very efficient calculation of the gradients—a fact that can be used for design/operation of computer systems, communication networks, manufacturing systems, and many other real-world systems, particularly since restrictive assumptions (e.g., exponential distributions) are not required of the system.
ISSN 00045411
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1987-07-01
Publisher Place New York
e-ISSN 1557735X
Journal Journal of the ACM (JACM)
Volume Number 34
Issue Number 3
Page Count 32
Starting Page 686
Ending Page 717


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Source: ACM Digital Library