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

机译:实时端到端监控和面向大数据的智能环境管理框架

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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(IoT)应用程序的成功取决于能够监视,管理和验证智能生态系统(包括传感器和大数据分析工具)正常运行的工具和技术的智能,这些工具通常部署在云和边缘计算数据中心中。在本文中,我们提出了一个用于IoT系统监视和管理的框架,该框架集成了AllJoyn功能,可用于互连IoT设备,MongoDB,实现大数据存储和Storm,以运行实时数据分析。我们实施了建议的框架,并在智能家居应用场景中测试了其主要功能。在我们的实验中,我们研究了三种不同的数据模式,即常规,基于事件和自动的数据模式,以便根据不同操作条件下的响应时间来评估我们框架的性能。实验结果表明,监视和服务的等待时间在很大程度上取决于系统中运行的管理应用程序的类型,而它受数据模式的影响很小。 (C)2018 Elsevier Inc.保留所有权利。

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