Energy-efficient data gathering scheme based on Kalman prediction and compressed sensing
A novel Kalman prediction and compressed sensing based energy-efficient data gathering scheme was proposed. Specially, in the intra-cluster transmission, the cluster members utilized the Kalman prediction to selectively send the data to their cluster heads. In the inter-cluster transmission, the clu...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2019-01-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000−0801.2019017/ |
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| _version_ | 1841530438618710016 |
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| author | Ying ZHOU Lihua YANG Longxiang YANG Meng NI |
| author_facet | Ying ZHOU Lihua YANG Longxiang YANG Meng NI |
| author_sort | Ying ZHOU |
| collection | DOAJ |
| description | A novel Kalman prediction and compressed sensing based energy-efficient data gathering scheme was proposed. Specially, in the intra-cluster transmission, the cluster members utilized the Kalman prediction to selectively send the data to their cluster heads. In the inter-cluster transmission, the cluster heads leveraged the hybrid compressed sensing to transfer the data to the sink via multi-hop links. Moreover, the communication cost was derived to verify the efficiency of the proposed method. Simulation results show that the proposed method has higher energy efficiency compared with the available schemes, and the sink can obtain measurements with reasonable quality by using the proposed method. |
| format | Article |
| id | doaj-art-3e4e1bf961714b269ae51a48ad3d3023 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2019-01-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-3e4e1bf961714b269ae51a48ad3d30232025-01-15T03:03:29ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012019-01-0135748059591527Energy-efficient data gathering scheme based on Kalman prediction and compressed sensingYing ZHOULihua YANGLongxiang YANGMeng NIA novel Kalman prediction and compressed sensing based energy-efficient data gathering scheme was proposed. Specially, in the intra-cluster transmission, the cluster members utilized the Kalman prediction to selectively send the data to their cluster heads. In the inter-cluster transmission, the cluster heads leveraged the hybrid compressed sensing to transfer the data to the sink via multi-hop links. Moreover, the communication cost was derived to verify the efficiency of the proposed method. Simulation results show that the proposed method has higher energy efficiency compared with the available schemes, and the sink can obtain measurements with reasonable quality by using the proposed method.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000−0801.2019017/wireless sensor networkKalman predictioncompressed sensingspatial-temporal correlationenergy efficiency |
| spellingShingle | Ying ZHOU Lihua YANG Longxiang YANG Meng NI Energy-efficient data gathering scheme based on Kalman prediction and compressed sensing Dianxin kexue wireless sensor network Kalman prediction compressed sensing spatial-temporal correlation energy efficiency |
| title | Energy-efficient data gathering scheme based on Kalman prediction and compressed sensing |
| title_full | Energy-efficient data gathering scheme based on Kalman prediction and compressed sensing |
| title_fullStr | Energy-efficient data gathering scheme based on Kalman prediction and compressed sensing |
| title_full_unstemmed | Energy-efficient data gathering scheme based on Kalman prediction and compressed sensing |
| title_short | Energy-efficient data gathering scheme based on Kalman prediction and compressed sensing |
| title_sort | energy efficient data gathering scheme based on kalman prediction and compressed sensing |
| topic | wireless sensor network Kalman prediction compressed sensing spatial-temporal correlation energy efficiency |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000−0801.2019017/ |
| work_keys_str_mv | AT yingzhou energyefficientdatagatheringschemebasedonkalmanpredictionandcompressedsensing AT lihuayang energyefficientdatagatheringschemebasedonkalmanpredictionandcompressedsensing AT longxiangyang energyefficientdatagatheringschemebasedonkalmanpredictionandcompressedsensing AT mengni energyefficientdatagatheringschemebasedonkalmanpredictionandcompressedsensing |