Elasticity of Workloads and Periods of Parallel Real-Time Tasks
Elasticity of Workloads and Periods of Parallel Real-Time Tasks
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并行实时任务的工作负载弹性和周期
DOI：
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发表时间：
2018
期刊：
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通讯作者：
C. Wong
中科院分区：
文献类型：
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作者：
James Orr;C. Gill;Kunal Agrawal;Sanjoy Baruah;Christian Cianfarani;Phyllis Ang;C. Wong
弹性任务模型允许连续的周期性实时任务（例如在多媒体播放器和自适应控制系统中发现的那些任务）动态地调整其周期以管理服务质量或适应其他任务。最近的理论进展表明，并行实时任务可以类似地适应它们的周期。本文进一步扩展了并行实时任务的弹性概念，允许它们适应自己的计算工作量而不是周期，例如当实时视频处理应用程序可以在给定的周期内进行更多的计算时，它可以提高图像质量。本文还提出了一种新的并发平台，其中每个并行实时任务可以调整其周期或工作负载，支持针对不同应用需求的异构形式的弹性。我们进行的经验评估(1)证明了该并发平台从先前的工作和本文开发的结果中强制执行理论保证的能力，以及(2)有助于量化和证明时间和计算弹性之间的权衡。
The elastic task model allows sequential periodic real-time tasks, such as those found in multimedia players and adaptive control systems, to adjust their periods dynamically to manage quality of service or to accommodate other tasks. Recent theoretical advances show that parallel real-time tasks can adapt their periods similarly. This paper further extends the concept of elasticity of parallel real-time tasks, to allow them to adapt their computational workloads instead of their periods, such as when a real-time video processing application can improve image quality if it can do more computation within a given period. This paper also presents a new concurrency platform in which each parallel real-time task can adapt either its period or its workload, supporting heterogeneous forms of elasticity for different application needs. Empirical evaluations we have conducted (1) demonstrate the ability of this concurrency platform to enforce theoretical guarantees from both prior work and results developed in this paper, and (2) help to quantify and demonstrate tradeoffs between temporal and computational elasticity.