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A hierarchical Quality of Service control architecture for configurable multimedia applications

机译:用于可配置多媒体应用程序的分层服务质量控制体系结构

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In order to achieve the best application-level Quality-of-Service (QoS), multimedia applications need to be dynamically tuned and reconfigured to adapt to fluctuating computing and communication environments. QoS-sensitive adaptations are critical when applications run in general-purpose systems, with no mechanisms provided for supporting resource reservations and real-time guarantees. Such adaptations are triggered by resource availability variations caused by best-effort resource allocations in unpredictable open environments. In this paper, we argue that adaptations are most effective to achieve a better QoS when performed within applications, where they may be optimized towards the best performance tradeoffs across various application parameters with different semantics. However, we believe that decisions about when and how adaptations should occur need to be coordinated, and formalized as a generic algorithm to be applied to a wide range of applications. For this purpose, we first identify an application model to focus on a set of application-specific tuning 'knobs' and critical parameters, then propose a polynomial-complexity QoS probing algorithm to quantitatively capture the run-time relationships between the two sets of parameters. Finally, we present a hierarchical adaptive QoS control architecture to bridge the gap between original 'triggers' of adaptation and actual tuning 'knobs' to be invoked. To prove the validity of our architecture and algorithms, we present Agilos, a middleware implementation of our hierarchical architecture. Under its control, we show that a configurable multimedia tracking application is able to deliver optimal performance even when operating in unpredictable open environments.
机译:为了获得最佳的应用程序级别的服务质量(QoS),需要对多媒体应用程序进行动态调整和重新配置,以适应不断变化的计算和通信环境。当应用程序在通用系统中运行且没有提供支持资源保留和实时保证的机制时,对QoS敏感的适应至关重要。此类调整是由在不可预测的开放环境中尽力而为资源分配引起的资源可用性变化触发的。在本文中,我们认为当在应用程序中执行适配时,适应最有效地获得更好的QoS,在这种情况下,可以针对具有不同语义的各种应用程序参数对最佳性能折衷进行优化。但是,我们认为,有关何时以及如何进行自适应的决策需要进行协调,并正式确定为适用于广泛应用的通用算法。为此,我们首先确定一个应用程序模型,以关注于一组特定于应用程序的调整旋钮和关键参数,然后提出一种多项式复杂度QoS探测算法,以定量地捕获两组参数之间的运行时关系。最后,我们提出了一种分层的自适应QoS控制体系结构,以弥合自适应的原始“触发器”与要调用的实际调整“旋钮”之间的差距。为了证明我们的体系结构和算法的有效性,我们介绍了Agilos,这是我们的分层体系结构的中间件实现。在它的控制下,我们证明了即使在不可预测的开放环境中运行时,可配置的多媒体跟踪应用程序也能够提供最佳性能。

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