Data Gathering in Wireless Sensor Networks Based on Reshuffling Cluster Compressed Sensing
The existing compressed sensing (CS) based data gathering (CSDG) methods in wireless sensor networks (WSNs) usually assume that the sensed data are sparse or compressible. However, the sparsity of raw sensed data in some case is not straightforward. In this paper, we present reshuffling cluster comp...
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| Format: | Article |
| Language: | English |
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Wiley
2015-11-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/260913 |
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| author | Lu Zhu Baishan Ci Yuanyuan Liu Zhizhang (David) Chen |
| author_facet | Lu Zhu Baishan Ci Yuanyuan Liu Zhizhang (David) Chen |
| author_sort | Lu Zhu |
| collection | DOAJ |
| description | The existing compressed sensing (CS) based data gathering (CSDG) methods in wireless sensor networks (WSNs) usually assume that the sensed data are sparse or compressible. However, the sparsity of raw sensed data in some case is not straightforward. In this paper, we present reshuffling cluster compressed sensing based data gathering (RCCSDG) method to achieve both energy efficiency and reconstruction accuracy in WSNs. By incorporating CS into the cluster protocol, RCCSDG is able to reduce the energy consumption and support larger networks. Moreover, the sparsity of raw sensed data can be greatly improved by reshuffling pretreatment. A theoretical analysis to energy consumption of cluster head is performed, and the cost of the pretreatment is small enough to be neglected. Based on these natures, the raw sensed data can be recovered from fewer samples. Also, considering the sensed data to be of excellent temporal stability in a short time, we reshuffle them just one time in this stable period to further reduce the energy consumption of WSNs. In addition, the delay of RCCSDG is analyzed based on TDMA 2 scheduling scheme. We carry out simulations on real sensor datasets. The results show that the RCCSDG can effectively compress the data transmission and decrease energy consumption of WSNs while ensuring the reconstruction accuracy. |
| format | Article |
| id | doaj-art-40a67f5521cc4ecf813118cb47f05158 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2015-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-40a67f5521cc4ecf813118cb47f051582025-02-03T06:45:31ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-11-011110.1155/2015/260913260913Data Gathering in Wireless Sensor Networks Based on Reshuffling Cluster Compressed SensingLu Zhu0Baishan Ci1Yuanyuan Liu2Zhizhang (David) Chen3 School of Information Engineering, East China Jiaotong University, Nanchang 330013, China School of Information Engineering, East China Jiaotong University, Nanchang 330013, China School of Information Engineering, East China Jiaotong University, Nanchang 330013, China Department of Electrical and Computer Engineering, Dalhousie University, Halifax, NS, Canada, B3J 2X4The existing compressed sensing (CS) based data gathering (CSDG) methods in wireless sensor networks (WSNs) usually assume that the sensed data are sparse or compressible. However, the sparsity of raw sensed data in some case is not straightforward. In this paper, we present reshuffling cluster compressed sensing based data gathering (RCCSDG) method to achieve both energy efficiency and reconstruction accuracy in WSNs. By incorporating CS into the cluster protocol, RCCSDG is able to reduce the energy consumption and support larger networks. Moreover, the sparsity of raw sensed data can be greatly improved by reshuffling pretreatment. A theoretical analysis to energy consumption of cluster head is performed, and the cost of the pretreatment is small enough to be neglected. Based on these natures, the raw sensed data can be recovered from fewer samples. Also, considering the sensed data to be of excellent temporal stability in a short time, we reshuffle them just one time in this stable period to further reduce the energy consumption of WSNs. In addition, the delay of RCCSDG is analyzed based on TDMA 2 scheduling scheme. We carry out simulations on real sensor datasets. The results show that the RCCSDG can effectively compress the data transmission and decrease energy consumption of WSNs while ensuring the reconstruction accuracy.https://doi.org/10.1155/2015/260913 |
| spellingShingle | Lu Zhu Baishan Ci Yuanyuan Liu Zhizhang (David) Chen Data Gathering in Wireless Sensor Networks Based on Reshuffling Cluster Compressed Sensing International Journal of Distributed Sensor Networks |
| title | Data Gathering in Wireless Sensor Networks Based on Reshuffling Cluster Compressed Sensing |
| title_full | Data Gathering in Wireless Sensor Networks Based on Reshuffling Cluster Compressed Sensing |
| title_fullStr | Data Gathering in Wireless Sensor Networks Based on Reshuffling Cluster Compressed Sensing |
| title_full_unstemmed | Data Gathering in Wireless Sensor Networks Based on Reshuffling Cluster Compressed Sensing |
| title_short | Data Gathering in Wireless Sensor Networks Based on Reshuffling Cluster Compressed Sensing |
| title_sort | data gathering in wireless sensor networks based on reshuffling cluster compressed sensing |
| url | https://doi.org/10.1155/2015/260913 |
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