NSSSD: A new semantic hierarchical storage for sensor data

Mehdi Gheisari, Ali Akbar Movassagh, Yongrui Qin, Jianming Yong, Xiaohui Tao, Ji Zhang, Haifeng Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

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.

LanguageEnglish
Title of host publicationProceedings of the 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages174-179
Number of pages6
ISBN (Electronic)9781509019151
DOIs
Publication statusPublished - 13 Sep 2016
Event20th IEEE International Conference on Computer Supported Cooperative Work in Design - Nanchang, China
Duration: 4 May 20166 May 2016
Conference number: 20
http://2016.cscwd.org/ (Link to Conference Website)

Conference

Conference20th IEEE International Conference on Computer Supported Cooperative Work in Design
Abbreviated titleCSCWD 2016
CountryChina
CityNanchang
Period4/05/166/05/16
Internet address

Fingerprint

Sensor networks
Semantics
Semantic Web
Sensors
Agglomeration
Processing
Sensor
Data structures
Query
Semantic web

Cite this

Gheisari, M., Movassagh, A. A., Qin, Y., Yong, J., Tao, X., Zhang, J., & Shen, H. (2016). NSSSD: A new semantic hierarchical storage for sensor data. In Proceedings of the 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2016 (pp. 174-179). [7565984] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSCWD.2016.7565984
Gheisari, Mehdi ; Movassagh, Ali Akbar ; Qin, Yongrui ; Yong, Jianming ; Tao, Xiaohui ; Zhang, Ji ; Shen, Haifeng. / NSSSD : A new semantic hierarchical storage for sensor data. Proceedings of the 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 174-179
@inproceedings{5a3a5dd6cb1c4c1080f1262573e67b86,
title = "NSSSD: A new semantic hierarchical storage for sensor data",
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.",
keywords = "hierarchical storage, Knowledge modeling, sensor data",
author = "Mehdi Gheisari and Movassagh, {Ali Akbar} and Yongrui Qin and Jianming Yong and Xiaohui Tao and Ji Zhang and Haifeng Shen",
year = "2016",
month = "9",
day = "13",
doi = "10.1109/CSCWD.2016.7565984",
language = "English",
pages = "174--179",
booktitle = "Proceedings of the 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

Gheisari, M, Movassagh, AA, Qin, Y, Yong, J, Tao, X, Zhang, J & Shen, H 2016, NSSSD: A new semantic hierarchical storage for sensor data. in Proceedings of the 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2016., 7565984, Institute of Electrical and Electronics Engineers Inc., pp. 174-179, 20th IEEE International Conference on Computer Supported Cooperative Work in Design, Nanchang, China, 4/05/16. https://doi.org/10.1109/CSCWD.2016.7565984

NSSSD : A new semantic hierarchical storage for sensor data. / Gheisari, Mehdi; Movassagh, Ali Akbar; Qin, Yongrui; Yong, Jianming; Tao, Xiaohui; Zhang, Ji; Shen, Haifeng.

Proceedings of the 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 174-179 7565984.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - NSSSD

T2 - A new semantic hierarchical storage for sensor data

AU - Gheisari, Mehdi

AU - Movassagh, Ali Akbar

AU - Qin, Yongrui

AU - Yong, Jianming

AU - Tao, Xiaohui

AU - Zhang, Ji

AU - Shen, Haifeng

PY - 2016/9/13

Y1 - 2016/9/13

N2 - 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.

AB - 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.

KW - hierarchical storage

KW - Knowledge modeling

KW - sensor data

UR - http://www.scopus.com/inward/record.url?scp=84991573452&partnerID=8YFLogxK

U2 - 10.1109/CSCWD.2016.7565984

DO - 10.1109/CSCWD.2016.7565984

M3 - Conference contribution

SP - 174

EP - 179

BT - Proceedings of the 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2016

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Gheisari M, Movassagh AA, Qin Y, Yong J, Tao X, Zhang J et al. NSSSD: A new semantic hierarchical storage for sensor data. In Proceedings of the 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 174-179. 7565984 https://doi.org/10.1109/CSCWD.2016.7565984