A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization Algorithms
Clustering of sensor nodes is a prominent method applied to wireless sensor networks (WSNs). In a cluster-based WSN scenario, the sensor nodes are assembled to generate clusters. The sensor nodes also have limited battery power. Therefore, energy efficiency in WSNs is crucial. The load on the sensor...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/11/6/869 |
| _version_ | 1797471845552750592 |
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| author | Xun Wang Huarui Wu Yisheng Miao Huaji Zhu |
| author_facet | Xun Wang Huarui Wu Yisheng Miao Huaji Zhu |
| author_sort | Xun Wang |
| collection | DOAJ |
| description | Clustering of sensor nodes is a prominent method applied to wireless sensor networks (WSNs). In a cluster-based WSN scenario, the sensor nodes are assembled to generate clusters. The sensor nodes also have limited battery power. Therefore, energy efficiency in WSNs is crucial. The load on the sensor node and its distance from the base station (BS) are the significant factors of energy consumption. Therefore, load balancing according to the transmission distance is necessary for WSNs. In this paper, we propose a hybrid routing algorithm based on Naïve Bayes and improved particle swarm optimization algorithms (HRA-NP). The cluster heads (CHs) are selected according to the CH conditional probability, which is estimated by the Naïve Bayes classifier. After the selection of the CHs, the multi-hop routing algorithm is applied to the CHs. The best routing path from each CH to the <i>BS</i> is obtained from an improved particle swarm optimization (PSO) algorithm. Simulations were conducted on evaluation factors such as energy consumption, active sensor nodes per round, the sustainability of the network, and the standard deviation of a load on the sensor node. It was observed that HRA-NP outperforms comparable algorithms, namely DUCF, ECRRS, and FC-RBAT, based on the evaluation factors. |
| first_indexed | 2024-03-09T19:54:49Z |
| format | Article |
| id | doaj.art-271bfdaa56c74f6fbb1003217924aac0 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-09T19:54:49Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-271bfdaa56c74f6fbb1003217924aac02023-11-24T01:00:36ZengMDPI AGElectronics2079-92922022-03-0111686910.3390/electronics11060869A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization AlgorithmsXun Wang0Huarui Wu1Yisheng Miao2Huaji Zhu3School of Information Science and Engineering, Southeast University, Nanjing 211189, ChinaNational Engineering Research Center for Information Technology in Agriculture, Beijing 100097, ChinaNational Engineering Research Center for Information Technology in Agriculture, Beijing 100097, ChinaNational Engineering Research Center for Information Technology in Agriculture, Beijing 100097, ChinaClustering of sensor nodes is a prominent method applied to wireless sensor networks (WSNs). In a cluster-based WSN scenario, the sensor nodes are assembled to generate clusters. The sensor nodes also have limited battery power. Therefore, energy efficiency in WSNs is crucial. The load on the sensor node and its distance from the base station (BS) are the significant factors of energy consumption. Therefore, load balancing according to the transmission distance is necessary for WSNs. In this paper, we propose a hybrid routing algorithm based on Naïve Bayes and improved particle swarm optimization algorithms (HRA-NP). The cluster heads (CHs) are selected according to the CH conditional probability, which is estimated by the Naïve Bayes classifier. After the selection of the CHs, the multi-hop routing algorithm is applied to the CHs. The best routing path from each CH to the <i>BS</i> is obtained from an improved particle swarm optimization (PSO) algorithm. Simulations were conducted on evaluation factors such as energy consumption, active sensor nodes per round, the sustainability of the network, and the standard deviation of a load on the sensor node. It was observed that HRA-NP outperforms comparable algorithms, namely DUCF, ECRRS, and FC-RBAT, based on the evaluation factors.https://www.mdpi.com/2079-9292/11/6/869wireless sensor networkrouting protocolclusteringenergy consumption optimizationchannel modelnaïve Bayes |
| spellingShingle | Xun Wang Huarui Wu Yisheng Miao Huaji Zhu A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization Algorithms Electronics wireless sensor network routing protocol clustering energy consumption optimization channel model naïve Bayes |
| title | A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization Algorithms |
| title_full | A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization Algorithms |
| title_fullStr | A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization Algorithms |
| title_full_unstemmed | A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization Algorithms |
| title_short | A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization Algorithms |
| title_sort | hybrid routing protocol based on naive bayes and improved particle swarm optimization algorithms |
| topic | wireless sensor network routing protocol clustering energy consumption optimization channel model naïve Bayes |
| url | https://www.mdpi.com/2079-9292/11/6/869 |
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