Abstract
Privacy-preserving continuous data aggregation in wireless sensor networks has broad application prospects, such as environmental monitoring, health care, etc. However, the existing secure aggregation algorithms focus on snapshot data aggregation, so they are not suitable for continuous data aggregation in view of traffic and energy consumption. We propose a privacy preserving, energy-efficient and scalable continuous data aggregation (PECDA). PECDA takes advantage of secure channels to ensure data privacy to counter dramatic energy consumption caused by heavy encryption/decryption operations. In addition, PECDA filters data and thus greatly reduces traffic based on the temporal correlation of sensory data. Therefore, PECDA significantly reduces energy consumption and prolongs the lifetime of network. Theoretical analysis and experimental results show that PECDA has low communication overhead, energy-efficiency, high safety and scalability.
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Acknowledgements
This work is supported by the National Natural Science Foundation of China (61402014, 61373015, 61672039, 61602009), Fundamental Research Funds for the Central Universities, NUAA (NP2013307, NZ2013306), Natural Science Foundation of Anhui Province (1508085QF133), Research Program of Anhui Province Education Department (KJ2014A088).
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Wang, T., Qin, X., Ding, Y. et al. Privacy-Preserving and Energy-Efficient Continuous Data Aggregation Algorithm in Wireless Sensor Networks. Wireless Pers Commun 98, 665–684 (2018). https://doi.org/10.1007/s11277-017-4889-5
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DOI: https://doi.org/10.1007/s11277-017-4889-5