A survey of Speedup simulation techniques

Abstract

This paper gives a brief overview of speed-up techniques for discrete event simulation where the quantity of interest depends on rare events to occur. Both rare event simulation approaches like RESTART/splitting and importance sampling and other complementary techniques are described. A list of key references to the various techniques are included. As a pragmatic or engineering approach, it is recommended that the different techniques are combined whenever possible instead of seeking the universal optimal technique for all applications. Some comparisons and combinations are included. 1 MOTIVATION Simulation is considered to be a flexible means for performance evaluation of complex data and telecommunication networks. However, when the networks have very strict quality of service requirements, the direct simulation approach is very inefficient. The reason is that the performance measure, e.g. the blocking probability, depends on rare events to occur, e.g. cell losses < , or system failures < . Figure 1 illustrates the speed-up gain of a technique called importance sampling over direct simulation on a simple Erlang loss system. The number of samples required for direct simulation to retain the same confidence level, increases exponential as the probability of the rare event increases. By importance sampling (with optimal parameters) the required number is (nearly) unchanged, and hence a significant speed-up gain is observed. Note that already at a loss probability of approximately 5%, importance sampling might increase the efficiency

Similar works

Full text

thumbnail-image
oaioai:CiteSeerX.psu:10.1...Last time updated on 10/22/2014

This paper was published in CiteSeerX.

Having an issue?

Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.