Odessa: enabling interactive perception applications on mobile devices
Odessa: enabling interactive perception applications on mobile devices
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DOI：
10.1145/1999995.2000000
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发表时间：
2011-06
期刊：
影响因子：
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通讯作者：
Moo-Ryong Ra;Anmol Sheth;L. Mummert;Padmanabhan Pillai;D. Wetherall;Ramesh Govindan
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文献类型：
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作者：
Moo-Ryong Ra;Anmol Sheth;L. Mummert;Padmanabhan Pillai;D. Wetherall;Ramesh Govindan
资源受限的移动的设备需要利用附近服务器上的计算来运行响应应用程序，这些应用程序从实时视频中识别对象、人或手势。影响性能的两个关键问题是要卸载哪些计算，以及如何构建跨移动终端和服务器的并行性。为了回答这些问题，我们开发和评估三个交互式感知应用程序。我们发现，卸载和并行度的选择应该是动态的，即使对于一个给定的应用程序，性能取决于场景的复杂性以及环境因素，如网络和设备的能力。为此，我们开发了敖德萨，一种新颖的，轻量级的，运行时，自动和自适应的卸载和并行决策的移动的交互式感知应用。我们的评估表明，增量贪婪策略的敖德萨收敛到一个工作点，接近一个理想的离线分区。与领域专家建议的分区相比，它在应用程序性能方面提供了超过3倍的改进。敖德萨在各种执行环境中运行良好，并且对网络、设备和应用程序输入的变化具有敏捷性。
Resource constrained mobile devices need to leverage computation on nearby servers to run responsive applications that recognize objects, people, or gestures from real-time video. The two key questions that impact performance are what computation to offload, and how to structure the parallelism across the mobile device and server. To answer these questions, we develop and evaluate three interactive perceptual applications. We find that offloading and parallelism choices should be dynamic, even for a given application, as performance depends on scene complexity as well as environmental factors such as the network and device capabilities. To this end we develop Odessa, a novel, lightweight, runtime that automatically and adaptively makes offloading and parallelism decisions for mobile interactive perception applications. Our evaluation shows that the incremental greedy strategy of Odessa converges to an operating point that is close to an ideal offline partitioning. It provides more than a 3x improvement in application performance over partitioning suggested by domain experts. Odessa works well across a variety of execution environments, and is agile to changes in the network, device and application inputs.