Data Collection in Smart Communities Using Sensor Cloud: Recent Advances, Taxonomy, and Future Research Directions

Ali, Ihsan and Gani, Abdullah and Ahmedy, Ismail and Yaqoob, Ibrar and Khan, Suleman and Anisi, Mohammad Hossein (2018) Data Collection in Smart Communities Using Sensor Cloud: Recent Advances, Taxonomy, and Future Research Directions. IEEE Communications Magazine, 56 (7). pp. 192-197. ISSN 0163-6804

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Official URL: https://doi.org/10.1109/MCOM.2017.1700549

Abstract

The remarkable miniaturization of sensors has led to the production of massive amounts of data in smart communities. These data cannot be efficiently collected and processed in WSNs due to the weak communication capability of these networks. This drawback can be compensated for by amalgamating WSNs and cloud computing to obtain sensor clouds. In this article, we investigate, highlight, and report recent premier advances in sensor clouds with respect to data collection. We categorize and classify the literature by devising a taxonomy based on important parameters, such as objectives, applications, communication technology, collection types, discovery, data types, and classification. Moreover, a few prominent use cases are presented to highlight the role of sensor clouds in providing high computation capabilities. Furthermore, several open research challenges and issues, such as big data issues, deployment issues, data security, data aggregation, dissemination of control message, and on time delivery are discussed. Future research directions are also provided.

Item Type: Article
Uncontrolled Keywords: Communication capabilities; Communication technologies; Control messages; Data aggregation; Data collection; Future research directions; On-time delivery; Research challenges
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Computer Science & Information Technology
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 25 Sep 2019 07:54
Last Modified: 25 Sep 2019 07:54
URI: http://eprints.um.edu.my/id/eprint/22561

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