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Generalized processor sharing with light-tailed and heavy-tailed input

机译:通用处理器与轻尾和重尾输入共享

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We consider a queue fed by a mixture of light-tailed and heavy-tailed traffic. The two traffic flows are served in accordance with the generalized processor sharing (GPS) discipline. GPS-based scheduling algorithms, such as weighted fair queueing, have emerged as an important mechanism for achieving service differentiation in integrated networks. We derive the asymptotic workload behavior of the light-tailed traffic flow under the assumption that its GPS weight is larger than its traffic intensity. The GPS mechanism ensures that the workload is bounded above by that in an isolated system with the light-tailed flow served in isolation at a constant rate equal to its GPS weight. We show that the workload distribution is in fact asymptotically equivalent to that in the isolated system, multiplied with a certain pre-factor, which accounts for the interaction with the heavy-tailed flow. Specifically, the pre-factor represents the probability that the heavy-tailed flow is backlogged long enough for the light-tailed flow to reach overflow. The results provide crucial qualitative insight in the typical overflow scenario.
机译:我们考虑一个由轻尾和重尾流量混合而成的队列。根据通用处理器共享(GPS)准则为这两个流量提供服务。基于GPS的调度算法(例如加权公平队列)已经成为实现集成网络中服务差异化的重要机制。在GPS权重大于其交通强度的假设下,我们得出了轻尾交通流的渐近工作量行为。 GPS机制可确保工作量受限于隔离系统中的工作量,其中轻尾流以等于其GPS重量的恒定速率被隔离地服务。我们显示,工作量分布实际上渐近等于隔离系统中的工作量分布,并乘以一定的前置因子,这说明了与重尾流的交互作用。具体来说,预因子表示重尾流积压足够长的时间以使轻尾流达到溢出的概率。在典型的溢出情况下,结果提供了关键的定性见解。

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