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An adaptive dual control framework for QoS design

机译：QoS设计的自适应双控制框架

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摘要

The widespread deployment of the advanced computer technology in business and industries has demanded the high standard on quality of service (QoS). For example, many Internet applications, i.e. online trading, e-commerce, and real-time databases, etc., execute in an unpredictable general-purpose environment but require performance guarantees. Failure to meet performance specifications may result in losing business or liability violations. As systems become distributed and complex, it has become a challenge for QoS design. The ability of on-line identification and auto-tuning of adaptive control systems has made the adaptive control theoretical design an attractive approach for QoS design. However, there is an inherent constraint in adaptive control systems, i.e. a conflict between asymptotically good control and asymptotically good on-line identification. This paper first identifies and analyzes the limitations of adaptive control for network QoS by extensive simulation studies. Secondly, as an approach to mitigate the limitations, we propose an adaptive dual control framework. By incorporating the existing uncertainty of on-line prediction into the control strategy and accelerating the parameter estimation process, the adaptive dual control framework optimizes the tradeoff between the control goal and the uncertainty, and demonstrates robust and cautious behavior. The experimental study shows that the adaptive dual control framework mitigate the limitations of the conventional adaptive control framework. Compared with the conventional adaptive control framework under the medium uncertainty, the adaptive dual control framework reduces the deviation from the desired hit-rate ratio from 40% to 13%.
机译：先进的计算机技术在商业和工业中的广泛应用要求对服务质量（QoS）提出高标准的要求。例如，许多因特网应用程序，即在线交易，电子商务和实时数据库等，在不可预测的通用环境中执行，但是需要性能保证。不符合性能规格可能会导致违反业务或责任的行为。随着系统变得分布式和复杂，这已成为QoS设计的挑战。自适应控制系统的在线识别和自动调整的能力使自适应控制理论设计成为QoS设计的一种有吸引力的方法。然而，在自适应控制系统中存在固有的约束，即，渐近良好的控制与渐近良好的在线识别之间的冲突。本文首先通过广泛的仿真研究来识别和分析网络QoS自适应控制的局限性。其次，作为减轻限制的一种方法，我们提出了一种自适应双重控制框架。通过将现有的在线预测不确定性纳入控制策略并加速参数估计过程，自适应双重控制框架优化了控制目标与不确定性之间的权衡，并表现出鲁棒和谨慎的行为。实验研究表明，自适应双重控制框架减轻了传统自适应控制框架的局限性。与中等不确定性下的传统自适应控制框架相比，自适应双重控制框架将与期望命中率的偏差从40％降低到13％。

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