BMRC: A Bitmap-Based Maximum Range Counting Approach for Temporal Data in Sensor Monitoring Networks
Due to the rapid development of the Internet of Things (IoT), many feasible deployments of sensor monitoring networks have been made to capture the events in physical world, such as human diseases, weather disasters and traffic accidents, which generate large-scale temporal data. Generally, the cert...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2017-09-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/17/9/2051 |
| _version_ | 1811304303213674496 |
|---|---|
| author | Bin Cao Wangyuan Chen Ying Shen Chenyu Hou Jung Yoon Kim Lifeng Yu |
| author_facet | Bin Cao Wangyuan Chen Ying Shen Chenyu Hou Jung Yoon Kim Lifeng Yu |
| author_sort | Bin Cao |
| collection | DOAJ |
| description | Due to the rapid development of the Internet of Things (IoT), many feasible deployments of sensor monitoring networks have been made to capture the events in physical world, such as human diseases, weather disasters and traffic accidents, which generate large-scale temporal data. Generally, the certain time interval that results in the highest incidence of a severe event has significance for society. For example, there exists an interval that covers the maximum number of people who have the same unusual symptoms, and knowing this interval can help doctors to locate the reason behind this phenomenon. As far as we know, there is no approach available for solving this problem efficiently. In this paper, we propose the Bitmap-based Maximum Range Counting (BMRC) approach for temporal data generated in sensor monitoring networks. Since sensor nodes can update their temporal data at high frequency, we present a scalable strategy to support the real-time insert and delete operations. The experimental results show that the BMRC outperforms the baseline algorithm in terms of efficiency. |
| first_indexed | 2024-04-13T08:03:40Z |
| format | Article |
| id | doaj.art-8b863f3ee4504c089027632eb7c499f1 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T08:03:40Z |
| publishDate | 2017-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8b863f3ee4504c089027632eb7c499f12022-12-22T02:55:13ZengMDPI AGSensors1424-82202017-09-01179205110.3390/s17092051s17092051BMRC: A Bitmap-Based Maximum Range Counting Approach for Temporal Data in Sensor Monitoring NetworksBin Cao0Wangyuan Chen1Ying Shen2Chenyu Hou3Jung Yoon Kim4Lifeng Yu5College of Computer Science, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Computer Science, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Computer Science, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Computer Science, Zhejiang University of Technology, Hangzhou 310023, ChinaGraduate School of Game Gachon University 1342 Seongnam Daero, Sujeong-Gu, Seongnam-Si, Gyeonggi-Do 461-701, KoreaHithink Royal Flush Information Network Co., Ltd., Financial Information Engineering Technology Research Center of Zhejiang Province, Hangzhou 310012, ChinaDue to the rapid development of the Internet of Things (IoT), many feasible deployments of sensor monitoring networks have been made to capture the events in physical world, such as human diseases, weather disasters and traffic accidents, which generate large-scale temporal data. Generally, the certain time interval that results in the highest incidence of a severe event has significance for society. For example, there exists an interval that covers the maximum number of people who have the same unusual symptoms, and knowing this interval can help doctors to locate the reason behind this phenomenon. As far as we know, there is no approach available for solving this problem efficiently. In this paper, we propose the Bitmap-based Maximum Range Counting (BMRC) approach for temporal data generated in sensor monitoring networks. Since sensor nodes can update their temporal data at high frequency, we present a scalable strategy to support the real-time insert and delete operations. The experimental results show that the BMRC outperforms the baseline algorithm in terms of efficiency.https://www.mdpi.com/1424-8220/17/9/2051Internet of Things (IoT)sensor monitoring networksbitmapmaximum range counting |
| spellingShingle | Bin Cao Wangyuan Chen Ying Shen Chenyu Hou Jung Yoon Kim Lifeng Yu BMRC: A Bitmap-Based Maximum Range Counting Approach for Temporal Data in Sensor Monitoring Networks Sensors Internet of Things (IoT) sensor monitoring networks bitmap maximum range counting |
| title | BMRC: A Bitmap-Based Maximum Range Counting Approach for Temporal Data in Sensor Monitoring Networks |
| title_full | BMRC: A Bitmap-Based Maximum Range Counting Approach for Temporal Data in Sensor Monitoring Networks |
| title_fullStr | BMRC: A Bitmap-Based Maximum Range Counting Approach for Temporal Data in Sensor Monitoring Networks |
| title_full_unstemmed | BMRC: A Bitmap-Based Maximum Range Counting Approach for Temporal Data in Sensor Monitoring Networks |
| title_short | BMRC: A Bitmap-Based Maximum Range Counting Approach for Temporal Data in Sensor Monitoring Networks |
| title_sort | bmrc a bitmap based maximum range counting approach for temporal data in sensor monitoring networks |
| topic | Internet of Things (IoT) sensor monitoring networks bitmap maximum range counting |
| url | https://www.mdpi.com/1424-8220/17/9/2051 |
| work_keys_str_mv | AT bincao bmrcabitmapbasedmaximumrangecountingapproachfortemporaldatainsensormonitoringnetworks AT wangyuanchen bmrcabitmapbasedmaximumrangecountingapproachfortemporaldatainsensormonitoringnetworks AT yingshen bmrcabitmapbasedmaximumrangecountingapproachfortemporaldatainsensormonitoringnetworks AT chenyuhou bmrcabitmapbasedmaximumrangecountingapproachfortemporaldatainsensormonitoringnetworks AT jungyoonkim bmrcabitmapbasedmaximumrangecountingapproachfortemporaldatainsensormonitoringnetworks AT lifengyu bmrcabitmapbasedmaximumrangecountingapproachfortemporaldatainsensormonitoringnetworks |