An Adaptive Application Framework with Customizable Quality Metrics

An Adaptive Application Framework with Customizable Quality Metrics
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具有可定制质量指标的自适应应用程序框架

DOI:
10.1145/3477428
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发表时间:
2022
影响因子:
1.4
通讯作者:
Kremer, Ulrich
Kremer, Ulrich
中科院分区:
计算机科学4区
文献类型:
--
作者:
Liu, Liu;Isaacman, Sibren;Kremer, Ulrich

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许多嵌入式环境要求应用程序在不同的、可能不断变化的资源约束下产生结果。通过近似放宽应用程序语义可以在资源使用和结果质量之间进行权衡。尽管质量是一个高度主观的概念,但以前的工作假设给定的、固定的低级别质量度量通常与用户的更高级别的质量体验缺乏强烈的相关性。用户还可以根据他们愿意用于执行的资源预算,改变他们对质量预期的想法。这激发了对适应性应用程序框架的需求,其中用户提供执行预算和定制的质量概念。本文提出了一种新的自适应程序图表示法,它支持基于应用程序开发人员定义的基本质量方面的用户级、可定制的质量。开发人员还定义应用程序配置空间,并可能进行定制以消除不需要的配置。在运行时,图可以在用户提供的资源预算内动态选择具有最大定制质量的配置。基于该图表示的自适应应用框架已经在Android和Linux平台上实现,并在8个基准程序上进行了评估,其中4个程序具有完全可定制的质量。使用自定义质量代替默认质量,用户的主观质量体验值最高可提高3.59倍,在不同资源约束下平均提高1.76倍。开发人员能够利用他们的应用程序结构知识来定义配置空间,与现有的与结构无关的方法相比,配置空间平均要小68.7%。动态重新配置的开销平均不到整个应用程序执行时间的1.84%。
Many embedded environments require applications to produce outcomes under different, potentially changing, resource constraints. Relaxing application semantics through approximations enables trading off resource usage for outcome quality. Although quality is a highly subjective notion, previous work assumes given, fixed low-level quality metrics that often lack a strong correlation to a user’s higher-level quality experience. Users may also change their minds with respect to their quality expectations depending on the resource budgets they are willing to dedicate to an execution. This motivates the need for an adaptive application framework where users provide execution budgets and a customized quality notion. This article presents a novel adaptive program graph representation that enables user-level, customizable quality based on basic quality aspects defined by application developers. Developers also define application configuration spaces, with possible customization to eliminate undesirable configurations. At runtime, the graph enables the dynamic selection of the configuration with maximal customized quality within the user-provided resource budget.An adaptive application framework based on our novel graph representation has been implemented on Android and Linux platforms and evaluated on eight benchmark programs, four with fully customizable quality. Using custom quality instead of the default quality, users may improve their subjective quality experience value by up to 3.59×, with 1.76× on average under different resource constraints. Developers are able to exploit their application structure knowledge to define configuration spaces that are on average 68.7% smaller as compared to existing, structure-oblivious approaches. The overhead of dynamic reconfiguration averages less than 1.84% of the overall application execution time.
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