ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things
Clock synchronization is still a vital and challenging task for underground coal wireless internet of things (IoT) due to the uncertainty of underground environment and unreliability of communication links. Instead of considering on-demand driven clock synchronization, this paper proposes a novel Ad...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/17/4981 |
| _version_ | 1797554795241799680 |
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| author | Kuiyuan Zhang Mingzhi Pang Yuqing Yin Shouwan Gao Pengpeng Chen |
| author_facet | Kuiyuan Zhang Mingzhi Pang Yuqing Yin Shouwan Gao Pengpeng Chen |
| author_sort | Kuiyuan Zhang |
| collection | DOAJ |
| description | Clock synchronization is still a vital and challenging task for underground coal wireless internet of things (IoT) due to the uncertainty of underground environment and unreliability of communication links. Instead of considering on-demand driven clock synchronization, this paper proposes a novel Adaptive Robust Synchronization (ARS) scheme with packets loss for mine wireless environment. A clock synchronization framework that is based on Kalman filtering is first proposed, which can adaptively adjust the sampling period of each clock and reduce the communication overhead in single-hop networks. The proposed scheme also solves the problem of outliers in data packets with time-stamps. In addition, this paper extends the ARS algorithm to multi-hop networks. Additionally, the upper and lower bounds of error covariance expectation are analyzed in the case of incomplete measurement. Extensive simulations are conducted in order to evaluate the performance. In the simulation environment, the clock accuracy of ARS algorithm is improved by 7.85% when compared with previous studies for single-hop networks. For multi-hop networks, the proposed scheme improves the accuracy by 12.56%. The results show that the proposed algorithm has high scalability, robustness, and accuracy, and can quickly adapt to different clock accuracy requirements. |
| first_indexed | 2024-03-10T16:37:09Z |
| format | Article |
| id | doaj.art-bda432a88f934d8297d77c28a2e9e62c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T16:37:09Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-bda432a88f934d8297d77c28a2e9e62c2023-11-20T12:20:55ZengMDPI AGSensors1424-82202020-09-012017498110.3390/s20174981ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of ThingsKuiyuan Zhang0Mingzhi Pang1Yuqing Yin2Shouwan Gao3Pengpeng Chen4School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, ChinaClock synchronization is still a vital and challenging task for underground coal wireless internet of things (IoT) due to the uncertainty of underground environment and unreliability of communication links. Instead of considering on-demand driven clock synchronization, this paper proposes a novel Adaptive Robust Synchronization (ARS) scheme with packets loss for mine wireless environment. A clock synchronization framework that is based on Kalman filtering is first proposed, which can adaptively adjust the sampling period of each clock and reduce the communication overhead in single-hop networks. The proposed scheme also solves the problem of outliers in data packets with time-stamps. In addition, this paper extends the ARS algorithm to multi-hop networks. Additionally, the upper and lower bounds of error covariance expectation are analyzed in the case of incomplete measurement. Extensive simulations are conducted in order to evaluate the performance. In the simulation environment, the clock accuracy of ARS algorithm is improved by 7.85% when compared with previous studies for single-hop networks. For multi-hop networks, the proposed scheme improves the accuracy by 12.56%. The results show that the proposed algorithm has high scalability, robustness, and accuracy, and can quickly adapt to different clock accuracy requirements.https://www.mdpi.com/1424-8220/20/17/4981adaptive robust synchronizationkalman filteringwireless internet of thingsunderground coal mines |
| spellingShingle | Kuiyuan Zhang Mingzhi Pang Yuqing Yin Shouwan Gao Pengpeng Chen ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things Sensors adaptive robust synchronization kalman filtering wireless internet of things underground coal mines |
| title | ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things |
| title_full | ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things |
| title_fullStr | ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things |
| title_full_unstemmed | ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things |
| title_short | ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things |
| title_sort | ars adaptive robust synchronization for underground coal wireless internet of things |
| topic | adaptive robust synchronization kalman filtering wireless internet of things underground coal mines |
| url | https://www.mdpi.com/1424-8220/20/17/4981 |
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