Reliable data transmission in wireless sensor networks with data decomposition and ensemble recovery

Fengyong Li; Gang Zhou; Jingsheng Lei; Fengyong Li; Gang Zhou; Jingsheng Lei

doi:10.3934/mbe.2019226

Mathematical Biosciences and Engineering

2019, Volume 16, Issue 5: 4526-4545. doi: 10.3934/mbe.2019226

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Research article Special Issues

Reliable data transmission in wireless sensor networks with data decomposition and ensemble recovery

College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai, P.R.China

Received: 11 March 2019 Accepted: 09 May 2019 Published: 22 May 2019

Wireless sensor networks (WSNs) are usually used to helps many basic scientific works to gather and observe environmental data, whose completeness and accuracy are the key to ensuring the success of scientific works. However, due to a lot of noise, collision and unreliable data link, data loss and damage in WSNs are rather common. Although some existing works, e.g. interpolation methods or prediction methods, can recover original data to some extent, they maybe provide an unsatisfactory accuracy when the missing data becomes large. To address this problem, this paper proposes a new reliable data transmission scheme in WSNs by using data decomposition and ensemble recovery mechanism. Firstly, the original data are collected by sensor nodes and then are expanded and split into multiple data shares by using multi-ary Vandermonde matrix. Subsequently, these data shares are transmitted respectively to source node via the sensor networks, which is made up of a large number of sensor nodes. Since each share contains data redundancy, the source node can reconstruct the original data even if some data shares are damaged or lost during delivery. Finally, extensive simulation experiments show that the proposed scheme outperforms significantly existing solutions in terms of recovery accuracy and robustness.
- wireless sensor networks,
- reliable transmission,
- data loss,
- matrix decomposition,
- ensemble recovery
Citation: Fengyong Li, Gang Zhou, Jingsheng Lei. Reliable data transmission in wireless sensor networks with data decomposition and ensemble recovery[J]. Mathematical Biosciences and Engineering, 2019, 16(5): 4526-4545. doi: 10.3934/mbe.2019226

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Abstract

Wireless sensor networks (WSNs) are usually used to helps many basic scientific works to gather and observe environmental data, whose completeness and accuracy are the key to ensuring the success of scientific works. However, due to a lot of noise, collision and unreliable data link, data loss and damage in WSNs are rather common. Although some existing works, e.g. interpolation methods or prediction methods, can recover original data to some extent, they maybe provide an unsatisfactory accuracy when the missing data becomes large. To address this problem, this paper proposes a new reliable data transmission scheme in WSNs by using data decomposition and ensemble recovery mechanism. Firstly, the original data are collected by sensor nodes and then are expanded and split into multiple data shares by using multi-ary Vandermonde matrix. Subsequently, these data shares are transmitted respectively to source node via the sensor networks, which is made up of a large number of sensor nodes. Since each share contains data redundancy, the source node can reconstruct the original data even if some data shares are damaged or lost during delivery. Finally, extensive simulation experiments show that the proposed scheme outperforms significantly existing solutions in terms of recovery accuracy and robustness.

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