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NSSSD: A New Semantic Hierarchical Storage for Sensor Data

Gheisari, Mehdi, Movassagh, Ali Akbar, Qin, Yongrui, Yong, Jianming, Tao, Xiaohui, Zhang, Ji and Shen, Haifeng (2016) NSSSD: A New Semantic Hierarchical Storage for Sensor Data. In: IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD), May 4-6, 2016, Nanchang, China.

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Abstract

Sensor networks usually generate mass of data, which if not structured for future applications, will require much effort on analytical processing and interpretations. Thus, storing sensor data in an effective and structured format is a key issue in the area of sensor networks. In the meantime, even a little improvement on data storing structure may lead to a significant effect on the lifetime and performance of the sensor network. This paper describes a new method for sensor storage that combines semantic web concepts, a data aggregation method along with aligning sensors in hierarchical form. This solution is able to reduce the amount of data stored at the sink nodes significantly. At the same time, the method structures sensed data in a way that we can respond to semantic web-based queries with less consumption of energy compared to previous conventional methods. Results show that, in some situations especially when the diversity of query responses and life of network are vital, the efficiency of our new solution is much better.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Schools: 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: 08 Nov 2016 09:59
Last Modified: 22 Jul 2017 03:03
URI: http://eprints.hud.ac.uk/id/eprint/29762

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