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In this paper we propose a fast adaptive importance sampling method for the efficient simulation of buffer overflow probabilities in queueing networks. The method comprises three stages. First we estimate the minimum cross-entropy tilting parameter for a small buffer level; next, we use this as a starting value for the estimation of the optimal tilting parameter for the actual (large) buffer level; finally, the tilting parameter just found is used to estimate the overflow probability of interest. We recognize three distinct properties of the method which together explain why the method works well; we conjecture that they hold for quite general queueing networks. Numerical results support this conjecture and demonstrate the high efficiency of the proposed algorithm.
In this paper, we propose a fast adaptive importance sampling method for the efficient simulation of buffer overflow probabilities in queueing networks. The method comprises three stages. First, we estimate the minimum cross-entropy tilting parameter for a small buffer level; next, we use this as a starting value for the estimation of the optimal tilting parameter for the actual (large) buffer level. Finally, the tilting parameter just found is used to estimate the overflow probability of interest. We study various properties of the method in more detail for the M/M/1 queue and conjecture that similar properties also hold for quite general queueing networks. Numerical results support this conjecture and demonstrate the high efficiency of the proposed algorithm.
The prevailing paradigm for enterprises in the new decade is undoubtedly speed. This enterprise view is driven by the availability of e-business technology that enables new forms of collaboration between companies. The rapid developments in e-business also have an impact on the future of engineering organizations. This paper focuses on the early phases of a product’s life cycle, i.e. between initial concept and release to manufacturing. New engineering workflow capabilities are presented, that have been tailored to speed up the engineering of new products.
We propose a semi-heuristic dynamic capacity allocation algorithm. Benchmarked by simulation against the Binary Linear Programming solution, our proposed algorithm, with polynomial complexity order, resulted in a satisfactory performance in terms of achievable capacity, and also in terms of packet mean sojourn time.
A stable-matching-based multiuser multicarrier capacity allocation algorithm is proposed. It responds to ONU backlogs and dynamic subchannel gains. Benchmarked against Binary Linear Programming, it results in just 5% less allocated capacity, at much lower complexity.
Nowadays, multicarrier transmission technique, e.g., optical OFDM, receives quite intense attention in the optical communications and networking field due to its potential to provide dispersion compensation. Adaptive modulation level is commonly and naturally employed in relation to multicarrier transmission, provided (sub)channel state information is available. The modulation level adaptation is usually done by a bitloading mechanism. In our work, given some modulation formats that are to be used, we attempt to reduce the computational complexity order of the bitloading algorithm from the one that has been presented in the literature. The bitloading algorithm is applied to a multicarrier multimode PON.
In this paper, an adaptive subcarrier assignment method based on a stable matching algorithm is considered. From the performance comparison with other assignment methods (Hungarian-algorithm-based, contiguous and interleaved), our assignment method, while of relatively low complexity, resulted in a satisfactory performance in terms of per-ONU and overall achievable throughputs, and also it responded to the traffic demands.
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