QoS管理的资源分配模型

R. Rajkumar, Chen Lee, J. Lehoczky, D. Siewiorek
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引用次数: 524

摘要

服务质量(QoS)在网络、多媒体系统、实时系统和分布式系统等研究领域受到了广泛的关注。在大型分布式系统中,例如用于防御系统、按需服务和互联网络系统的系统,争夺系统资源的应用程序必须满足定时、可靠性和安全性约束以及特定于应用程序的质量要求。在这些情况下,为不同的应用程序分配足够的资源以满足各种需求是一个基本问题。因此,为性能驱动的资源分配建立一个基本而灵活的模型,有助于做出适当的权衡。本文提出了一个系统QoS管理的分析模型,该模型必须满足时效性、可靠的传输方案、加密安全性和数据质量等多个维度的应用需求。我们把这个模型称为Q-RAM(基于qos的资源分配模型)。该模型假设一个具有多个并发应用程序的系统,每个应用程序都可以基于可用的系统资源以不同的质量级别运行。该模型的目标是能够将资源分配给各种应用程序,以便在每个应用程序可以满足其最小需求的约束下最大化整个系统的效用。我们确定应用程序的资源配置文件,这些资源配置文件允许有效和实时地做出此类决策。我们还沿着不同的维度确定应用程序实用程序功能,这些功能可组合以形成独特的应用程序需求概要。我们使用视频会议系统来说明该模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A resource allocation model for QoS management
Quality of service (QoS) has been receiving wide attention in many research communities including networking, multimedia systems, real-time systems and distributed systems. In large distributed systems such as those used in defense systems, on-demand service and inter-networked systems, applications contending for system resources must satisfy timing, reliability and security constraints as well as application-specific quality requirements. Allocating sufficient resources to different applications in order to satisfy various requirements is a fundamental problem in these situations. A basic yet flexible model for performance-driven resource allocations can therefore be useful in making appropriate tradeoffs. We present an analytical model for QoS management in systems which must satisfy application needs along multiple dimensions such as timeliness, reliable delivery schemes, cryptographic security and data quality. We refer to this model as Q-RAM (QoS-based Resource Allocation Model). The model assumes a system with multiple concurrent applications, each of which can operate at different levels of quality based on the system resources available to it. The goal of the model is to be able to allocate resources to the various applications such that the overall system utility is maximized under the constraint that each application can meet its minimum needs. We identify resource profiles of applications which allow such decisions to be made efficiently and in real-time. We also identify application utility functions along different dimensions which are composable to form unique application requirement profiles. We use a video-conferencing system to illustrate the model.
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