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QDaS: Quality driven data summarisation for effective storage management in Internet of Things

journal contribution
posted on 2024-11-02, 07:29 authored by Jonathan Liono, Prem Jayaraman, A. K. Qin, Thuong Nguyen, Flora SalimFlora Salim
The proliferation of Internet of Things (IoT) has led to the emergence of enabling many interesting applications within the realm of several domains including smart cities. However, the accumulation of data from smart IoT devices poses significant challenges for data storage while there are needs to deliver relevant and high quality services to consumers. In this paper, we propose QDaS, a novel domain agnostic framework as a solution for effective data storage and management of IoT applications. The framework incorporates a novel data summarisation mechanism that uses an innovative data quality estimation technique. This proposed data quality estimation technique computes the quality of data (based on their utility) without requiring any feedback from users of this IoT data or domain awareness of the data. We evaluate the effectiveness of the proposed QDaS framework using real world datasets.

History

Journal

Journal of Parallel and Distributed Computing

Volume

127

Start page

196

End page

208

Total pages

13

Publisher

Academic Press

Place published

United States

Language

English

Copyright

© 2018 Elsevier

Former Identifier

2006085660

Esploro creation date

2020-06-22

Fedora creation date

2019-04-30

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