P. E. Lassila, J. T. Virtamo. Efficient Importance Sampling for Monte Carlo Simulation of Loss Systems. Proc. 16th Int. Teletraffic Congress, 1999. Home/Search Document Details and Download
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Rare Event Simulation - Görg, Lamers, Fuß, Heegaard (Correct)
....the shortest longest path (SLP) and some other NP hard problems. The work in [44] is an important contribution to this field. Another network issue is estimation of the call blocking probabilities. These have been obtained by Monte Carlo simulation with importance sampling on loss networks [35] [33]. In [23] well engineered loss networks have been studied by simulation of Markov chain models with importance sampling. This is a flexible approach that is suitable for more general network problems, which has been recently extended in [7] Other work on multidimensional problems has focused on ....
P. E. Lassila, J. T. Virtamo. Efficient Importance Sampling for Monte Carlo Simulation of Loss Systems. Proc. 16th Int. Teletraffic Congress, 1999.
Blocking Probabilities of Multi-Layer Multicast Streams - Karvo, Aalto, Virtamo Self-citation (Karvo Virtamo) (Correct)
....and further work is needed. An exact algorithm with complexity for the network case with dynamic nonlayered multicast connections has been given in Nyberg et al. 9] Efficient Monte Carlo simulation method for dynamic multicast networks has been developed by Lassila et al. [10]. Aalto and Virtamo [11] developed an algorithm for the non layered case where all channels are statistically indistinguishable, using combinatorics to achieve complexity of # . Recently, there has been slight progress in the case where the multicast streams are layered. Karvo et al. ....
P. Lassila, J. Karvo, and J. Virtamo, "Efficient importance sampling for Monte Carlo simulation of multicast networks," in Proc. INFOCOM'01, Anchorage, Alaska, Apr. 2001, pp. 432--439.
Efficient Importance Sampling for Monte Carlo Simulation.. - Lassila, Karvo, Virtamo (1999) (1 citation) Self-citation (Lassila Virtamo) (Correct)
....which makes the interesting samples more likely than under the original distribution. The twist in the distribution is then corrected for by weighting the samples with the so called likelihood ratio. The use of IS in MC estimation of blocking probabilities has been previously studied in [5], 6] 7] and [8] However, the particular loss system that has been studied in these works is the so called multiservice loss system. The multicast network studied here is in many ways different from the multiservice loss system, but it possesses sufficiently common features with the ....
P. E. Lassila and J. T. Virtamo, "Efficient importance sampling for monte carlo simulation of loss systems," in Proceedings of the ITC-16. June 1999, pp. 787--796, Elsevier.
Efficient Importance Sampling for Monte Carlo Simulation.. - Lassila, Karvo, Virtamo (1999) (1 citation) Self-citation (Lassila Virtamo) (Correct)
....which makes the interesting samples more likely than under the original distribution. The twist in the distribution is then corrected for by weighting the samples with the so called likelihood ratio. The use of IS in MC estimation of blocking probabilities has been previously studied in [5], 6] 7] 8] However, the particular loss system that has been studied in these works is the so called multiservice loss system, i.e. the generalized call scale model for connection oriented networks. The multicast network studied here is in many ways different from the multiservice loss ....
P. E. Lassila and J. T. Virtamo, \Efficient importance sampling for monte carlo simulation of loss systems," in ########### ## ### ######. June 1999, pp. 787-796, Elsevier.
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