异构共享感知基础设施上数据采集策略的自动化部署

Cyril Cecchinel, Sébastien Mosser, P. Collet
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引用次数: 4

摘要

智能建筑和智能城市依赖于相互连接的传感器网络来收集有关其环境的数据,以支持各种应用。开发和部署这些系统的数据收集架构是一个具有挑战性的问题。传感器平台的特殊性迫使软件工程师在较低的水平上工作。这使得该活动变得冗长乏味,生成的代码会严重地利用网络架构,并阻碍数据收集策略的重用。此外,不能保证在共享基础设施上部署多个数据收集程序。在本文中,我们提出了一种自动化方法,该方法支持(i)在更高的抽象层次上定义数据收集策略,(ii)不同平台和网络拓扑的表示,以及(iii)在遵循不同策略的异构传感基础设施之上自动组合和部署策略。该方法是工具,并已在现实和模拟部署中进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Deployment of Data Collection Policies over Heterogeneous Shared Sensing Infrastructures
Smart buildings and smart cities rely on interconnected sensor networks that collect data about their environment to support various applications. Developing and deploying the data collection architectures of these systems is a challenging problem. The specificities of the sensor platforms compel software engineers to work at a low level. This makes this activity tedious, producing code that badly exploits the network architecture, and hampering reuse of data collection policies. Moreover, several data collection programs cannot be guaranteed to be deployable on a shared infrastructure. In this paper, we present an automated approach that supports (i) the definition of data collection policies at a higher level of abstraction, (ii) the representation of the diverse platforms and the network topology, and (iii) the automatic composition and deployment of the policies on top of heterogeneous sensing infrastructures following different strategies. The approach is tooled and has been assessed on both realistic and simulated deployments.
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