Compressed Sensing With Dynamic Retransmission Algorithm in Lossy Wireless IoT
Wireless sensor networks (WSNs) based on compressed sensing (CS) can complete data sampling and data compression simultaneously, thereby greatly reducing the data transmission volume and the energy consumption of the network. However, many studies have not considered the loss of data packets due to...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9146136/ |
| _version_ | 1818616862312759296 |
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| author | Bo Jiang Guosheng Huang Fufang Li Shaobo Zhang |
| author_facet | Bo Jiang Guosheng Huang Fufang Li Shaobo Zhang |
| author_sort | Bo Jiang |
| collection | DOAJ |
| description | Wireless sensor networks (WSNs) based on compressed sensing (CS) can complete data sampling and data compression simultaneously, thereby greatly reducing the data transmission volume and the energy consumption of the network. However, many studies have not considered the loss of data packets due to the unreliable wireless communication, which leads to the data reconstruction not being as accurate as the applications require. In this paper, a Compressed Sensing with Dynamic Retransmission (CSDR) algorithm is proposed to guarantee high data reconstruction accuracy, high network lifetime and high energy utilization. The CSDR algorithm dynamically determines the max packet loss retransmission times of different nodes according to their residual energies, for Internet of Thing (IoT) devices with relative high energy consumption, fewer max retransmission times is adopted to maintain a longer network lifetime. For energy-rich IoT devices, more max retransmission times is used to improve the data transmission accuracy and the performance of data reconstruction. Strict theoretical analysis and experimental results show that the CSDR algorithm significantly improves the main performance indicators compared to the previous strategy: The Normalized Mean Absolute Error (NMAE) is reduced by 64.5%, and the effective utilization of energy is improved by 34.1% on average, under the condition that the network lifetime is no less than the previous scheme. |
| first_indexed | 2024-12-16T16:56:32Z |
| format | Article |
| id | doaj.art-c9e0f3acf6294e14a4bbd775be822c29 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T16:56:32Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-c9e0f3acf6294e14a4bbd775be822c292022-12-21T22:23:52ZengIEEEIEEE Access2169-35362020-01-01813382713384210.1109/ACCESS.2020.30111509146136Compressed Sensing With Dynamic Retransmission Algorithm in Lossy Wireless IoTBo Jiang0https://orcid.org/0000-0002-1349-6194Guosheng Huang1https://orcid.org/0000-0002-9853-0311Fufang Li2https://orcid.org/0000-0002-1448-5665Shaobo Zhang3School of Computer Science and Engineering, Central South University, Changsha, ChinaSchool of Information Science and Engineering, Hunan First Normal University, Changsha, ChinaSchool of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, ChinaSchool of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, ChinaWireless sensor networks (WSNs) based on compressed sensing (CS) can complete data sampling and data compression simultaneously, thereby greatly reducing the data transmission volume and the energy consumption of the network. However, many studies have not considered the loss of data packets due to the unreliable wireless communication, which leads to the data reconstruction not being as accurate as the applications require. In this paper, a Compressed Sensing with Dynamic Retransmission (CSDR) algorithm is proposed to guarantee high data reconstruction accuracy, high network lifetime and high energy utilization. The CSDR algorithm dynamically determines the max packet loss retransmission times of different nodes according to their residual energies, for Internet of Thing (IoT) devices with relative high energy consumption, fewer max retransmission times is adopted to maintain a longer network lifetime. For energy-rich IoT devices, more max retransmission times is used to improve the data transmission accuracy and the performance of data reconstruction. Strict theoretical analysis and experimental results show that the CSDR algorithm significantly improves the main performance indicators compared to the previous strategy: The Normalized Mean Absolute Error (NMAE) is reduced by 64.5%, and the effective utilization of energy is improved by 34.1% on average, under the condition that the network lifetime is no less than the previous scheme.https://ieeexplore.ieee.org/document/9146136/Compressed sensingWSNIoTdata collectiondynamic retransmissionenergy consumption |
| spellingShingle | Bo Jiang Guosheng Huang Fufang Li Shaobo Zhang Compressed Sensing With Dynamic Retransmission Algorithm in Lossy Wireless IoT IEEE Access Compressed sensing WSN IoT data collection dynamic retransmission energy consumption |
| title | Compressed Sensing With Dynamic Retransmission Algorithm in Lossy Wireless IoT |
| title_full | Compressed Sensing With Dynamic Retransmission Algorithm in Lossy Wireless IoT |
| title_fullStr | Compressed Sensing With Dynamic Retransmission Algorithm in Lossy Wireless IoT |
| title_full_unstemmed | Compressed Sensing With Dynamic Retransmission Algorithm in Lossy Wireless IoT |
| title_short | Compressed Sensing With Dynamic Retransmission Algorithm in Lossy Wireless IoT |
| title_sort | compressed sensing with dynamic retransmission algorithm in lossy wireless iot |
| topic | Compressed sensing WSN IoT data collection dynamic retransmission energy consumption |
| url | https://ieeexplore.ieee.org/document/9146136/ |
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