Model-less Approach for an Accurate Packet Loss Simulation

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In network evaluation through simulations, accurately modeling traffic of real networks is difficult. Even if accurate traffic modeling is achieved, it is also difficult to accurately estimate a rate of rare packet loss events. For accurate estimations of rare events, Importance Sampling (IS) based on the change-of-measure technique using traffic models has been investigated. However, these studies are inapplicable for traffic traces of real networks since the applicable traffic models are extremely limited. In this paper, we propose a model-less approach to accurately estimate a packet loss rate through a simulation without directly modeling traffic. The change-ofmeasure is achieved based on traffic traces of networks in our model-less approach. We evaluated the applicability of the modelless approach on a G/M/1/K system with a traffic trace of a real network and confirmed that the model-less approach achieves up to 145 times accurate than normal a trace-driven Monte Carlo (MC) simulation.

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