抄録
WSNs are good options to help monitor the scene of interest and notify the unusual happening to control center. But sensors' high sampling rates lead to tremendous network traffic over the bandwidth-limited and energy-critical WSNs, hence how to reduce the network traffic while maintaining the unusual events monitoring function becomes important. In this paper, we investigate the intra-correlations of the data generated by each sensor at different time instances. And we propose a traffic deduction algorithm exploring the sensor data's intra-correlations which could reduce the data volume significantly and guarantee the parameters needed for unusual detection are delivered.
本文言語 | English |
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ホスト出版物のタイトル | 2015 IEEE SENSORS - Proceedings |
出版社 | Institute of Electrical and Electronics Engineers Inc. |
ISBN(印刷版) | 9781479982028 |
DOI | |
出版ステータス | Published - 2015 12月 31 |
イベント | 14th IEEE SENSORS - Busan, Korea, Republic of 継続期間: 2015 11月 1 → 2015 11月 4 |
Other
Other | 14th IEEE SENSORS |
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国/地域 | Korea, Republic of |
City | Busan |
Period | 15/11/1 → 15/11/4 |
ASJC Scopus subject areas
- 器械工学
- 電子材料、光学材料、および磁性材料
- 分光学
- 電子工学および電気工学