A Study on the Sequential Regenerative Simulation

순차적인 재생적 시뮬레이션에 관한 연구

  • JongSuk R. (JongSuk R. Lee) ;
  • HaeDuck J. (HaeDuck J. Jeong)
  • Published : 2004.06.01

Abstract

Regenerative simulation (RS) is a method of stochastic steady-state simulation in which output data are collected and analysed within regenerative cycles (RCs). Since data collected during consecutive RCs are independent and identically distributed, there is no problem with the initial transient period in simulated processes, which is a perennial issue of concern in all other types of steady-state simulation. In this paper, we address the issue of experimental analysis of the quality of sequential regenerative simulation in the sense of the coverage of the final confidence intervals of mean values. The ultimate purpose of this study is to determine the best version of RS to be implemented in Akaroa2 [1], a fully automated controller of distributed stochastic simulation in LAN environments.

Keywords

References

  1. 13th European Simulation Multiconference Akaroa2: Exploiting Network Computing by Distributing Stochastic Simulation G.C.Ewing;K.Pawlikowski;D.McNickle
  2. Management Science v.28 no.5 Confidence Intervals for Steady-State Simulations: A Survey of Sequential Procedures A.M.Law;W.D.Kelton
  3. ACM Computing Surveys v.22 no.2 Steady-State Simulation of Queueing Processes: A Survey of Problems and Solutions K.Pawlikowski
  4. ACM Performance Evaluation Review v.8 no.1-2 Confidence Intervals for Queueing Simulations of Computer Systems C.H.Sauer
  5. IBM J. Research Development Sequential Stopping Rules for the Regenerative Method of Simulation S.S.Lavenberg;C.H.Sauer
  6. Simulation Practice and Theory v.6 Coverage of Confidence Intervals in Sequential Steady-State Simulation K.Pawlikowski;D.C.McNickle;G.Ewing
  7. Proceedings of the 22nd Australasian Computer Science Conference Confidence Interval Estimators for Coverage Analysis in Sequential Steady-State Simulation J.R.Lee;D.McNickle;K.Pawlikowski
  8. Proc. of the 1994 Winter Simulation Conference Distributed and Stochastic Discrete-event Simulation in Parallel Time Streams K.Pawlikowski;V.Yau;D.C.McNickle
  9. Communications of the ACM v.25 A Spectral Method for Confidence Interval Generation and Run Length Control in Simulations P.Heidelberger;P.D.Welch
  10. Department of Computer Science, Univ. of Canterbury, Technical Report TR-COSC 05/98 Sequential Estimation of Quantiles J.R.Lee;D.McNickle;K.Pawlikowski
  11. 13th European Simulation Multiconference Quantile Estimation in Sequential Steady-State Simulation J.R.Lee;D.McNickle;K.Pawlikowski
  12. Management Science v.24 Estimation and Simulation B.Fox
  13. Regenerative Stochastic Simulation G.S.Shedler
  14. Naval Res. Logist. Quarterly v.22 Simulating Stable Stochastic System V: Comparison of Ratio Estimators D.L.Iglehart
  15. An Introduction to the Regenerative Method for Simulation Analysis in Lecture Notes in Control and Information Sciences M.A.Crane;A.J.Lemoine
  16. Operations Research v.23 no.1 Simulating Stable Stochastic Systems: Ⅲ. Regenerative Processes and Discrete Event Simulations M.A.Crane;D.L.Iglehart
  17. 13th European Simulation Multiconference Quality of Sequential Regenerative Simulation J.R.Lee;D.McNickle;K.Pawlikowski