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Stochastic programming methods applied to network optimization

机译:随机规划方法应用于网络优化

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摘要

As communication technologies evolve, it becomes necessary to incorporate the stochastic effect of traffic flows into network models. This paper introduces the stochastic programming (SP) methodology for characterizing traffic. Two SP approaches, here-and-now (HN) and scenario tracking (ST), are described through case studies for a prototype network. A numerical optimization procedure is used to perform the simulation. It is clearly demonstrated that when the probability distributions can be estimated analytically, the HN approach can be attractive. Otherwise, the ST approach may be more appropriate.
机译:随着通信技术的发展,有必要将流量的随机影响纳入网络模型。本文介绍了用于表征流量的随机编程(SP)方法。通过对原型网络的案例研究,介绍了两种SP方法,即刻(HN)和方案跟踪(ST)。数值优化程序用于执行仿真。清楚地表明,当可以通过概率估计概率分布时,HN方法可能会很有吸引力。否则,ST方法可能更合适。

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