@inproceedings{e209497072564a5ca31eb1cd88e14170,

title = "Efficient Simulation of Population Overflow in Parallel Queues",

abstract = "In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overﬂow in networks of parallel queues. This heuristic approximates the “optimal��? state-dependent change of measure without the need for dif��?cult mathematical analysis or costly optimization involved in adaptive methodologies. Comprehensive simulations of networks with an arbitrary number of parallel queues and different traf��?c intensities yield asymptotically ef��?cient estimates (with relative error increasing sub-linearly in the overﬂow level) where no other state-independent importance sampling techniques are known to be ef��?cient. The ef��?ciency of the proposed heuristic surpasses those based on adaptive importance sampling algorithms, yet it is easier to determine and implement and scales better for large networks.",

keywords = "EWI-9066, METIS-237909, IR-66871",

author = "V.F. Nicola and T.S. Zaburnenko",

year = "2006",

month = dec,

language = "Undefined",

isbn = "1424405017",

publisher = "WSC",

number = "06EX1382C",

pages = "398--405",

booktitle = "Proceedings of the 2006 Winter Simulation Conference, WSC'06",

note = "null ; Conference date: 03-12-2006 Through 06-12-2006",

}