利用计算质量提高移动计算系统的服务质量

Dominik Schäfer, Janick Edinger, Tobias Borlinghaus, Justin Mazzola Paluska, C. Becker
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引用次数: 4

摘要

移动设备无处不在,但其资源有限。然而,它们必须能够运行计算密集型软件,例如图像拼接、人脸识别和基于仿真的人工智能。作为一种解决方案,移动设备可以使用附近的资源来卸载计算。分布式计算环境提供了这些特性,但忽略了移动设备的特性,例如移动性、网络或电池变化。这会导致长时间的延迟,从而降低用户体验的质量。在本文中,我们提出了移动微线程,这是我们的分布式计算中间件的移动扩展。Mobile Tasklets的设计包括上下文监控、上下文感知调度机制和用于应用程序集成的Android API。我们认识到将移动设备集成到我们的分布式计算环境中的挑战。我们在一个具有不同上下文设置的真实测试平台中评估移动微线程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using quality of computation to enhance quality of service in mobile computing systems
Mobile devices are ubiquitous but their resources are limited. However, they must be capable to run computationally intensive software, for example for image stitching, face recognition, and simulation-based artificial intelligence. As a solution, mobile devices can use nearby resources to offload computation. Distributed computing environments provide such features but ignore the nature of mobile devices, such as mobility, network, or battery changes. This leads to long delays, which reduce the quality of experience for the user. In this paper, we present Mobile Tasklets, a mobile extension of our distributed computing middleware. The design of Mobile Tasklets includes context monitoring, context-aware scheduling mechanisms, and an Android API for application integration. We identify the challenges of the integration of mobile devices into our distributed computing environment. We evaluate Mobile Tasklets in a real-world testbed with different context settings.
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