دانلود رایگان مقاله انگلیسی پلت فرم اینترنت اشیا بر پایه مه برای مدیریت کارآمد و جمع آوری داده ها - نشریه IEEE

Abstract

One of the most promising emerging technologies, Internet-of-Things, refers to the interconnection of thousands (or even millions) of smart objects, supporting a large number of applications like environmental monitoring, smart agriculture, ehealth, etc. Research groups in both the academia and industry, have proposed and/or developed a significant number of IoT architectures and platforms, however not focusing on platform management-related issues. Furthermore, the vast amount of the sensory data and the rapid proliferation of the smart devices (i.e. sensors) make a new approach regarding efficient data collection and storage inevitable. Fog Computing (FC) is an environment where data are stored and pre-processed before transmitting them to the cloud, having a number of advantages like scalable real-time services, fault detection and isolation, enhanced security and privacy, etc. In this work, we present a fog-enabled IoT platform used for sensory data collection, presenting several metrics that can be used as the basis for a Management-Platformas-a-Service, able to efficiently monitor the IoT platform and predict potential failures.

IV. CONCLUSIONS

In this paper we presented a fog-enabled three-layer IoT platform, capable of collecting not only sensory data but management data as well, like the device uptime, the energy consumption of the SNs, etc. This can be used as the first step towards the implementation of a Management-Platformas-a-Service with inter-operability capabilities. The evaluation results, based on the data collected from the SNs, show that the uptime metric can be efficiently use for characterising the availability of the SNs, that can be further used to detect potential failures, misconfigurations and network-related problems like bandwidth limitations and interference. In addition, the data availability measurements that are computed based on the inter-arrival time of the collected measurements can reveal similar inefficiencies.

The energy consumption measurements show that a signifi- cant amount of energy can be saved when CS is used as fewer packets are sent due to compression. These measurements can be used to compute the remaining energy of the SNs and take necessary actions for prolonging network’s lifetime. This can be done using various methods, like replacing SN’s battery as soon as a remaining threshold has been reached, or by adding more intelligence in the network, as for example to perform routing based on the SNs’ remaining energy.

The secure COAP measurements reveal that the overhead of COAPs is not significant, given that the sensory data are not collected very often. These results show that adding security to the connection is not costly once an active session has been established, hence a session should be kept alive as long as possible to avoid repeated handshakes.