Importance sampling for stochastic simulations
Management Science
A Unified Framework for Simulating Markovian Models of Highly Dependable Systems
IEEE Transactions on Computers
Efficient estimation of cell blocking probability for ATM systems
IEEE/ACM Transactions on Networking (TON)
IEEE/ACM Transactions on Networking (TON)
Effective bandwidths for multiclass Markov fluids and other ATM sources
IEEE/ACM Transactions on Networking (TON)
Effective bandwidth and fast simulation of ATM intree networks
Performance '93 Proceedings of the 16th IFIP Working Group 7.3 international symposium on Computer performance modeling measurement and evaluation
Fast simulation of rare events in queueing and reliability models
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Importance sampling for large ATM-type queueing networks
WSC '96 Proceedings of the 28th conference on Winter simulation
An Introduction to the Regenerative Method for Simulation Analysis
An Introduction to the Regenerative Method for Simulation Analysis
Estimating small cell-loss ratios in ATM switches via importance sampling
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simulating GI/GI/1 queues and insurance risk processes with subexponential distributions
Proceedings of the 32nd conference on Winter simulation
A Simulation Environment for Job Scheduling on Distributed Systems
ICCS '02 Proceedings of the International Conference on Computational Science-Part I
Fast simulation of wavelength continuous WDM networks
IEEE/ACM Transactions on Networking (TON)
An adaptive approach to fast simulation of traffic groomed optical networks
WSC '04 Proceedings of the 36th conference on Winter simulation
An adaptive approach to accelerated evaluation of highly available services
ACM Transactions on Modeling and Computer Simulation (TOMACS)
FISTE: A black box approach for end-to-end QoS management
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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A significant difficulty when using Monte Carlo simulation for the performance analysis of communication networks is the long runtime required to obtain accurate statistical estimates. Under the proper conditions, importance sampling (IS) is a technique that can speed up simulations involving rare events in network (queuing) systems. Large speed-up factors in simulation runtime can be obtained with IS if the modification or bias of the underlying probability measures of certain random processes is carefully chosen. Fast simulation methods based on large deviation theory (LTD) have been successfully applied in many cases.In this paper, we set up an IS-based simulation of various elementary network topologies. These configurations are frequenly encountered in broadband ATM-based network components such as switches and multiplexers. Our objective in this study is to obtain the optimal or near-optimal biasing parameter values of the arrival processes for the importance sampling simulation. For this purpose we appropriately apply a technique presented by Chang et al. for certain portions of the networks (intree) while we develop a new algorithm, inspired by the work of De Veciana et al. on decoupling bandwidths, for the non-intree portion of the network.