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首页> 外文期刊>SIAM Journal on Applied Mathematics >Refined asymptotic approximations to loss probabilities and their sensitivities in shared unbuffered resources
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Refined asymptotic approximations to loss probabilities and their sensitivities in shared unbuffered resources

机译:共享无缓冲资源中损失概率及其敏感度的精细渐近逼近

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We consider an unbuffered resource having capacity C, which is shared by several different services. Calls of each service arrive in a Poisson stream and request a fixed, integral amount of capacity, which may depend on the service. An arriving call is blocked and lost if there is not enough capacity. Otherwise, the capacity of the call is held for the duration of the call, and the holding period is generally distributed. It is assumed that C and the traffic intensities of the services are commensurately large and asymptotic approximations are obtained for the loss probabilities and their sensitivities to the traffic intensity of each service. These sensitivities are important in optimizing the performance of multiservice, multirate loss networks. Numerical results illustrate the accuracy of the asymptotic approximations. These results show that while prior asymptotic approximations to the loss probabilities are quite accurate, the new approximations are very accurate. Moreover, while the prior asymptotic approximations to the sensitivities are overall rather poor, the new approximations are very good. Experience with case studies has shown that computationally efficient asymptotic techniques are crucial to cope with the size and the number of service offerings of emerging broadband networks in their design and optimization. [References: 23]
机译:我们考虑一个容量为C的无缓冲资源,该资源由几个不同的服务共享。每个服务的呼叫以泊松流的形式到达,并请求固定的,完整的容量,这可能取决于服务。如果容量不足,则会阻止到达的呼叫并丢失。否则,将在通话期间保持通话容量,并且通常会分配保持时间。假定C和服务的业务强度相当大,并且对于损失概率及其对每种服务的业务强度的敏感性,获得了渐近近似。这些敏感性对于优化多服务,多速率损耗网络的性能非常重要。数值结果说明了渐近逼近的准确性。这些结果表明,尽管先前对损失概率的渐近逼近非常准确,但新的逼近却非常准确。此外,虽然以前对灵敏度的渐近逼近总体而言很差,但新的逼近效果却很好。案例研究的经验表明,高效计算的渐近技术对于在设计和优化中应对新兴宽带网络的服务规模和数量至关重要。 [参考:23]

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