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When things matter: A survey on data-centric Internet of Things

Qin, Yongrui, Sheng, Quan Z., Falkner, Nickolas J. G., Dustdar, Schahram, Wang, Hua-Wei and Vasilakos, Athanasios V. (2016) When things matter: A survey on data-centric Internet of Things. Journal of Network and Computer Applications, 64. pp. 137-153. ISSN 1084-8045

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Abstract

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, but several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy and continuous. This paper reviews the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Schools: School of Computing and Engineering
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
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Depositing User: Yongrui Qin
Date Deposited: 07 Nov 2016 15:25
Last Modified: 30 Oct 2017 16:16
URI: http://eprints.hud.ac.uk/id/eprint/29760

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