Simulation of rare events in communications networks

Townsend, J.K.; Haraszti, Zsolt; Freebersyser, J.A.; Devetsikiotis, Michael

doi:10.1109/35.707815

Cited by 26 publications

(15 citation statements)

References 12 publications

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“…No universally applicable VRT can be found. However, such VRTs as Importance Sampling or Splitting (or Restart) can give spectacular speedup in the case of rare event simulation; see for example [29].…”

Section: Final Commentsmentioning

confidence: 99%

On credibility of simulation studies of telecommunication networks

2002

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In telecommunication networks, as in many other areas of science and engineering, proliferation of computers as research tools has resulted in the adoption of computer simulation as the most commonly used paradigm of scientific investigations. This, together with a plethora of existing simulation languages and packages, has created a popular opinion that simulation is mainly an exercise in computer programming. In new computing environments, programming can be minimised, or even fully replaced, by the manipulation of icons (representing pre-built programming objects containing basic functional blocks of simulated systems) on a computer monitor. One can say that we have witnessed another success of modern science and technology: the emergence of wonderful and powerful tools for exploring and predicting the behaviour of such complex, stochastic dynamic systems as telecommunication networks.But this enthusiasm is not shared by all researchers in this area. An opinion is spreading that one cannot rely on the majority of the published results on performance evaluation studies of telecommunication networks based on stochastic simulation, since they lack credibility. Indeed, the spread of this phenomenon is so wide that one can speak about a deep crisis of credibility. In this paper, this claim is supported by the results of a survey of over 2200 publications on telecommunication networks in recent proceedings of the IEEE INFOCOM and such journals as the IEEE Transactions on Communications, the IEEE/ACM Transactions on Networking, and the Performance Evaluation Journal. Credibility of simulation studies 2 Our ¤ discussion focuses on two important necessary conditions of a credible simulation study: use of appropriate pseudo-random generators of independent uniformly distributed numbers, and appropriate analysis of simulation output data. Having considered their perils and pitfalls, we formulate guidelines that, if observed, could help to assure a basic level of credibility of simulation studies of telecommunication networks.

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Section: Final Commentsmentioning

confidence: 99%

On credibility of simulation studies of telecommunication networks

2002

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“…A good introduction to "quick simulation" via importance sampling can be found in Bucklew [1990]. Townsend et al [1998] give a good introduction to this technique for evaluating rare events in communications networks (exactly the problem when, for example, simulating cell-loss probabilities in ATM networks). A more specialized use for the IS method is found in Li et al [1998], where it is used to accelerate the simulation of, specifically, self-similar traffic.…”

Section: Previous Techniques For Accelerated Network Simulationmentioning

confidence: 99%

“…Importance sampling (IS) [Townsend et al 1998;Deman and Boel 1998;Suzuki and Nakagawa 1998] has also been used to simulate rare events such as cell-loss probability in ATM networks. Fundamentally, IS is based on the notion of modifying, or biasing, the underlying probabilities in such a way that rare events occur much more frequently.…”

Section: Previous Techniques For Accelerated Network Simulationmentioning

confidence: 99%

A hybrid technique for accelerated simulation of ATM networks and network elements

2001

ACM Trans. Model. Comput. Simul.

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Conventional simulation of cell-or packet-switched networks involves the use of discrete event simulators that model each individual cell through the network, typically called cell-level simulation. Each cell's arrival at, or departure from, a network element is represented by an event. However, statistical considerations are such that very large numbers of cells have to be simulated to guarantee the accuracy of the results. This has always caused very long simulation times, often amounting to many hours of "real" time just to simulate a few minutes of "simulated" time. In this article we describe a novel methodology for accelerating simulation studies in cell-based communication networks, e.g., ATM, by using a hybrid analytical/ simulation combination. The methodology uses a mathematical technique to seperate foreground traffic from background traffic, and focuses on accelerating cell by cell simulation.

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“…Estimation of probability of rare events has therefore become of great interest, especially in financial engineering [1] , air traffic management [2] , optical fiber [3] , telecommunication networks [4] , climatology [5] and high reliability industrial system [6] . However, crude Monte Carlo estimators are no more efficient and specific techniques dedicated to rare events are required.…”

Section: Introductionmentioning

confidence: 99%