NDLI: Big Sensing Data Curation in Cloud Data Center for Next Generation IoT and WSN

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Big Sensing Data Curation in Cloud Data Center for Next Generation IoT and WSN

Content Provider	Semantic Scholar
Author	Yang, Chi Puthal, Deepak Mohanty, Saraju P. Kougianos, Elias
Copyright Year	2017
Abstract	Modern sensing devices play a pivotal role in achieving data acquisition, communication and dissemination for the Internet-of-Things (IoT). Naturally, IoT applications and intelligent sensing systems supported by sensing devices, such as wireless sensor networks (WSN), are closely coupled. Modern intelligent sensing systems generate huge volumes of sensing data, well beyond the processing capabilities of common techniques and tools. Hence, to collect, manage, and process IoT big sensing data within an acceptable time duration is a new challenge for both research and industrial applications. The massive size, extreme complexity and high speed of big sensing data bring new technical requirements including data collection, data storage, data organization, data analysis and data publishing in real time when deploying real world IoT applications. To better facilitate these IoT applications, the convergent research of WSN, big data, IoT and Cloud Computing is a natural scientific development trend. In this paper, we concentrate on big sensing data curation and preparation issues with Cloud Computing under the theme of IoT. There are three especially critical issues that need to be addressed, namely scalable big sensing data cleaning, scalable big sensing data compression and Cloud based data curation response for IoT device optimization. Viewed from the IoT side, all IoT sensing devices are integrated together in an adaptive solution and upload their data onto the Cloud. The automatic responses from both the Cloud and intelligent sensors will change the status or behavior of sensing devices, hence the status of the IoT itself.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://www.smohanty.org/Publications_Journals/2017/Mohanty_IEEE-CEM_2017-Oct_Curation.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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