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A framework for real time end to end monitoring and big data oriented management of smart environments

机译:一个实时结束到最终监控和大数据面向智能环境管理的框架

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Nowadays, the success of Internet of Things (IoT) applications depends on the intelligence of tools and techniques that can monitor, manage, and verify the correct operations of smart ecosystems including sensors and big data analytics tools, typically deployed in Cloud and Edge computing datacenters. In this paper, we propose a framework for the monitoring and management of IoT system that integrates the AllJoyn functionalities, useful to interconnect IoT devices, MongoDB, to implement Big Data storage, and Storm, to run real-time data analytics. We implemented the proposed framework and we tested its main functionalities in a smart home application scenario. In our experimentation, we investigated three different data patterns, i.e., regular, event-based, and automated, in order to evaluate performance of our framework in terms of response time under different operational conditions. Experimental results show that the latency of the monitoring and service strongly depends on the type of management application running in the system, whereas it is lightly affected by the data patterns. (C) 2018 Elsevier Inc. All rights reserved.
机译:如今,物联网的成功(IOT)应用程序取决于可以监视,管理和验证智能生态系统的正确操作的工具和技术的智能,这些工具包括传感器和大数据分析工具,通常部署在云和边缘计算数据中心。在本文中,我们提出了一个框架,用于监控和管理IOT系统,它集成了AllJoyn功能,可用于互连IoT设备,MongoDB,实现大数据存储和风暴,运行实时数据分析。我们实施了拟议的框架,我们在智能家庭应用方案中测试了其主要功能。在我们的实验中,我们调查了三种不同的数据模式,即定期,基于事件和自动化,以便在不同操作条件下的响应时间方面评估我们的框架的绩效。实验结果表明,监控和服务的延迟强烈取决于系统中运行的管理应用类型,而它受数据模式的轻微影响。 (c)2018 Elsevier Inc.保留所有权利。

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