Efficient simulation experiments for comparing communication network routing algorithms
Article Abstract:
In this paper, we propose efficient statistical designs of simulation experiments and statistical methods for systematically comparing communication network routing algorithms via simulation. The design of experiments technique establishes the minimum number of observations or simulation runs without losing much information needed to gain insight into the real world system. Statistical models use this efficient set of observations in providing (1) insight into the intrinsic behavior of the algorithm (i.e., sensitivity of the algorithm to changes in factors), (2) a statistical basis for comparing alternate algorithms that perform common functions, and (3) predictor equations that can be used to predict algorithm performance for the user-specified values of influencing factors. The emphasis in the paper is on the use of statistical testing and comparison methods in a simulation setting and not on the nature of algorithms themselves. These methods should pave the way for performance analysis of other algorithms as well. The testing environment includes a parameter-driven simulator which has the capability to modularly include alternate routing algorithms one at a time. The model generates a threat scenario which transforms into the generation of appropriate messages. The impact analysis of five influencing factors on three measures of performance is proposed. (Reprinted by permission of the publisher.)
Publication Name: SIMULATION
Subject: Engineering and manufacturing industries
ISSN: 0037-5497
Year: 1989
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A simulation approach to PERT network analysis
Article Abstract:
This paper presents simulation as a useful analytical tool for project network analysis. Simulation is a powerful tool for evaluating many of the decision parameters involved in project management. A computer program, named STARC, is used to illustrate the effectiveness of computer simulation for project planning. STATGRAPHICS software is used to illustrate some of the post-simulation statistical analyses that can be conducted. (Reprinted by permission of the publisher.)
Publication Name: SIMULATION
Subject: Engineering and manufacturing industries
ISSN: 0037-5497
Year: 1991
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