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Consistent proportional delay differentiation: A fuzzy control approach

机译:一致比例延迟微分:一种模糊控制方法

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Proportional delay differentiation (PDD) is an important service model for providing relative differentiated services on the Internet. It aims to maintain pre-specified packet queueing-delay ratios between different classes of traffic at each hop. Existing rate-allocation approaches for PDD services assume the average queueing delay of a class is inversely proportional to its service rate. This assumption is not necessarily valid when the system is not heavily loaded. To provide consistent PDD services under various load conditions, in this paper, we propose a novel rate-allocation approach that applies fuzzy control theory to capture the nonlinear relationship between the queueing delay and the service rate. In the approach, a class's service rate is adjusted according to a set of fuzzy control rules defined over its error (the difference between the target delay ratio and the achieved one), the change of error, and the change of service rate. We prove that the fuzzy control system is stable and the service rate of a class converges to its equilibrium point at steady state. Simulation results demonstrate that, in comparison with other rate-allocation approaches, the fuzzy control approach is able to provide consistent PDD services under wide range load conditions. It is also shown robust under various system conditions, including with multiple classes, changing target delay ratios, changing load conditions, and different traffic patterns.
机译:比例延迟区分(PDD)是一种重要的服务模型,用于在Internet上提供相对区分的服务。它旨在维持每个跃点不同流量类别之间的预先指定的数据包排队延迟比率。现有的PDD服务速率分配方法假定一类的平均排队延迟与其服务速率成反比。当系统负载不重时,此假设不一定有效。为了在各种负载条件下提供一致的PDD服务,我们提出了一种新颖的速率分配方法,该方法采用模糊控制理论来捕获排队延迟和服务速率之间的非线性关系。在该方法中,根据针对其误差(目标延迟率与已实现延迟之间的差),误差的变化和服务率的变化定义的一组模糊控制规则来调整一类的服务率。我们证明了模糊控制系统是稳定的,一类的服务率在稳态下收敛到其平衡点。仿真结果表明,与其他速率分配方法相比,模糊控制方法能够在宽范围负载条件下提供一致的PDD服务。它还显示出在各种系统条件下(包括多种类别,不断变化的目标延迟比,不断变化的负载条件和不同的流量模式)的鲁棒性。

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