AROM:移动物联网边缘的自适应资源优化模型

Ramesh Guntha, Sethuraman N. Rao, M. Ramesh, Maik Benndorf, T. Haenselmann
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引用次数: 0

摘要

利用手机进行灾后救援的众包方式正变得越来越流行。移动电话在估计、疏散和救援行动中起着至关重要的作用,因为它们可以用于感知和传输位置、海拔、加速度、图像和其他用户生成的消息等信息,但移动物联网边缘设备通常受到电池和网络的资源限制。在本文中,我们提出了一种自适应资源优化模型AROM,该模型通过考虑网络和电池约束来优化移动传感和通信系统。AROM的工作原理是自适应地计算资源临界分数,控制感知机制,并根据分数对网络通信进行限制和优先排序。我们还详细介绍了为验证我们的模型和分析结果而进行的性能测试。我们已经在2018年和2019年喀拉拉邦洪水期间部署的Amrita-Kripa救灾应用程序中实施了该架构,用于救援和救济活动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AROM: An Adaptive Resource Optimization Model for Mobile IoT Edge
Crowdsourced approach using mobile phones towards rescue and relief operations in post-disaster situations is becoming popular. The mobile phones play a critical role in estimation, evacuation and relief operations as they can be used for sensing and transmitting information such as location, elevation, acceleration, images and other user generated messages, but the mobile IoT edge devices are often resource constrained by battery and network. In this paper we present AROM, an Adaptive Resource Optimization Model for optimizing mobile sensing and communication systems, by considering network and battery constraints. AROM works by adaptively computing a resource criticality score and controlling sensing mechanisms and throttling and prioritizing network communications based on the score. We also present the details of performance tests done to validate our model and the analysis of results. We have implemented this architecture in our Amrita-Kripa disaster relief application which was deployed during 2018 and 2019 Kerala floods for rescues and relief activities.
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