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A fluid model for a relay node in an ad hoc network: the case of heavy-tailed input

机译:Ad hoc网络中中继节点的流体模型:重尾输入的情况

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摘要

Relay nodes in an ad hoc network can be modelled as fluid queues, in which the available service capacity is shared by the input and output. In this paper such a relay node is considered; jobs arrive according to a Poisson process and bring along a random amount of work. The total transmission capacity is fairly shared, meaning that, when n jobs are present, each job transmits traffic into the queue at rate 1/(n + 1) while the queue is drained at the same rate of 1/(n + 1). Where previous studies mainly concentrated on the case of exponentially distributed job sizes, the present paper addresses regularly varying jobs. The focus lies on the tail asymptotics of the sojourn time S. Using sample-path arguments, it is proven that P {S > x} behaves roughly as the residual job size, i.e., if the job sizes are regularly varying of index -nu, the tail of S is regularly varying of index 1 - nu. In addition, we address the tail asymptotics of other performance metrics, such as the workload in the queue, the flow transfer time and the queueing delay.
机译:可以将ad hoc网络中的中继节点建模为流动队列,其中可用的服务容量由输入和输出共享。在本文中,考虑了这种中继节点。职位根据泊松过程到达,并带来随机的工作量。总传输容量是公平分配的,这意味着,当存在n个作业时,每个作业都以1 /(n + 1)的速率将流量传输到队列中,而队列以1 /(n + 1)的相同速率排空。 。以前的研究主要集中在工作规模呈指数分布的情况下,本文研究的是定期变化的工作。重点在于停留时间S的尾部渐近线。使用样本路径参数,证明了P {S> x}大致表现为剩余作业大小,即,如果作业大小定期变化索引-nu ,S的尾部规律地变化索引1-nu。此外,我们还将解决其他性能指标的尾部渐近问题,例如队列中的工作量,流传输时间和排队延迟。

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