Abstract
Cyber-physical systems (CPS) are becoming increasingly ubiquitous with applications in diverse domains, e.g., structural health monitoring (SHM). Wireless sensor networks (WSNs) are being explored for adoption to improve the performance of centralized wired-based SHM. Existing work often separates the functions and designs of WSNs and civil/structural engineering SHM algorithms. These algorithms usually requires high-resolution data collection for the health monitoring tasks. However, the task becomes difficult because of inherent limitations of WSNs, such as low-bandwidth, unreliable wireless communication, and energy-constraint. In this paper, we proposes a data collection algorithm, which shows that changes (e.g., damage) in a physical structure affect computations and communications in the CPS. To make use of WSNs for SHM tasks, we focus on low-complexity data acquisitions that help reduce the total amount of data transmission. We propose a sensor collaborative algorithm suitable for a wireless sensor in making a damage-sensitive parameter to ensure whether or not it should (i) continue data acquisition at a high frequency and (ii) transmit the acquired data, thus extending system lifetime. The effectiveness of our algorithms is evaluated via a proof-of-concept CPS system implementation.
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Acknowledgments
This work is supported in part by the National Natural Science Foundation of China under Grant Nos. 61272151, 61472451, 61402543, 61202468, 61572206 and in part by ISTCP grant 2013DFB10070, in part by China Postdoctoral Science Foundation under Grant No. 2015T80885 and Central South University Postdoctoral Research Fund, and in part by the US National Science foundation (NSF) under grants CNS 149860, CNS 1461932, CNS 1460971, CNS 1439672, CNS 1301774, ECCS 1231461, ECCS 1128209, and CNS 1138963.
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Bhuiyan, M.Z.A., Wang, G., Wu, J., Wang, T., Liu, X. (2015). Resource-Efficient Vibration Data Collection in Cyber-Physical Systems. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9530. Springer, Cham. https://doi.org/10.1007/978-3-319-27137-8_11
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DOI: https://doi.org/10.1007/978-3-319-27137-8_11
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