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Chimp optimization algorithm based support vector machine for congestion control in WSN-IoT |
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| รหัสดีโอไอ | |
| Creator | 1. S. Parthasarathy 2. J. A. Smitha |
| Title | Chimp optimization algorithm based support vector machine for congestion control in WSN-IoT |
| Publisher | Research and Development Office, Prince of Songkla University |
| Publication Year | 2565 |
| Journal Title | Songklanakarin Journal of Science an Technology (SJST) |
| Journal Vol. | 44 |
| Journal No. | 4 |
| Page no. | 907-913 |
| Keyword | WSN, IoT, congestion control, SVM, chimp optimization algorithm (ChOA) |
| URL Website | https://rdo.psu.ac.th/sjst/index.php |
| ISSN | 0125-3395 |
| Abstract | The Wireless sensor network (WSN) has huge part in Internet of Things (IoT), as it is used in different applications, forexample, detecting climate and sending information by means of the Internet. In any case, the issue of heavy congestion, mayaffect the performance of WSN-IoT. Despite the fact that machine learning calculations have been introduced by analysts fordistinguishing the congested data, accuracy of detection needs to be further enhanced. To control the congestion, ChimpOptimization Algorithm (ChOA) based Support Vector Machine (SVM) is proposed in this paper. To enhance on the executionof SVM, the tuning parameters of SVM are improved utilizing ChOA algorithm. Simulation results indicate that the SVM-ChOAoutranks other models, for example, SVM with Genetic Algorithm (SVM-GA), SVM and TCP, based on throughput, energyutilization, delivery ratio, and overhead. Also, the detection accuracy of SVM-CHOA has increased to 92%. |
