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Model predictive control versus traditional proportional delay differentiation algorithms

机译:模型预测控制与传统比例延迟微分算法

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摘要

An approximated quadratic programming optimization is proposed to determine a model predictive controller to guarantee end-to-end delay in the DiffServ architecture. The proposed algorithm, called the suboptimal mode! predictive control scheduler (SMPCS), regulates the service rates of aggregated traffic classes dynamically, such that some constraints on proportional or absolute delay can be guaranteed. This paper investigates SMPCS complexity and its implementation problems in high-speed routers. The main problem of model predictive control (and one which has limited its use to slow processes) is its complexity. Optimization is the most computationally complex part in a model predictive controller. To enable efficient implementation of such a computationally expensive algorithm, this paper proposes to reduce the precision of the optimizer while maintaining near-optimal values for the manipulated variables (service rates). Both control-theoretic analysis and simulations demonstrate that SMPCS performs stable and acceptable quality-of-service differentiations at core routers while maintaining end-to-end delay constraints.
机译:提出了近似二次规划优化来确定模型预测控制器,以确保DiffServ架构中的端到端延迟。提出的算法称为次优模式!预测控制调度程序(SMPCS)可动态调节聚合流量类别的服务速率,从而可以保证对比例或绝对延迟的某些约束。本文研究了SMPCS的复杂性及其在高速路由器中的实现问题。模型预测控制的主要问题(以及将其用于缓慢过程的一种方法)的复杂性。优化是模型预测控制器中计算最复杂的部分。为了能够有效地实现这种计算上昂贵的算法,本文提出了在保持受控变量(服务费率)接近最佳值的同时降低优化器的精度。控制理论分析和仿真均表明,SMPCS在核心路由器上执行稳定且可接受的服务质量差异,同时保持端到端延迟约束。

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