A fuzzy based chicken swarm optimization algorithm for efficient fault node detection in Wireless Sensor Networks
Abstract Wireless Sensor Networks (WSN) are built with miniature sensor nodes (SN), which are deployed into the geographical location being sensed to monitor environmental conditions, which transfer the sensed physical information to the base station for further processing. The sensor nodes frequent...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-024-78646-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849699584776863744 |
|---|---|
| author | B Nagarajan Santhosh Kumar SVN M Selvi K Thangaramya |
| author_facet | B Nagarajan Santhosh Kumar SVN M Selvi K Thangaramya |
| author_sort | B Nagarajan |
| collection | DOAJ |
| description | Abstract Wireless Sensor Networks (WSN) are built with miniature sensor nodes (SN), which are deployed into the geographical location being sensed to monitor environmental conditions, which transfer the sensed physical information to the base station for further processing. The sensor nodes frequently experience node failure as a result of their hostile deployment and resource limitations. In WSN, node failure can cause a number of issues, namely Wireless Sensor Networks topology changes, broken communications links, disconnected portions of the network, and data transmission errors. An important concern of WSN is the detecting, diagnosing and recovering of sensor node failures. In the course of this effort, an effective strategy for sensor node failure detection algorithm using the Poisson Hidden Markov Model (PHMM) and the Fuzzy-based Chicken Swarm Optimization (F-CSO) is proposed for efficient detection of sensor node faults in the WSN. The proposed work offers optimal false alarm, false positive, energy consumption, detection accuracy, network lifetime, and least delay rates. Moreover, the F-CSO provides improved localization to locate the defective sensor nodes that are present in the WSN. The proposed work is implemented in the NS2 simulator with realistic simulation parameters, and the simulation results demonstrate that the proposed work is more effective in terms of 89.5% fault detection accuracy, 19.53% throughput, 8.43% energy consumption with minimum delay and less false positive rate when it is compared with other existing state-of-art systems. |
| format | Article |
| id | doaj-art-80c31c3adf9c4f1b9ee433f21caa51e1 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-80c31c3adf9c4f1b9ee433f21caa51e12025-08-20T03:18:32ZengNature PortfolioScientific Reports2045-23222024-11-0114112110.1038/s41598-024-78646-2A fuzzy based chicken swarm optimization algorithm for efficient fault node detection in Wireless Sensor NetworksB Nagarajan0Santhosh Kumar SVN1M Selvi2K Thangaramya3School of computer Science Engineering and Information Systems, Vellore Institute of TechnologySchool of computer Science Engineering and Information Systems, Vellore Institute of TechnologySchool of Computer Science and Engineering, Vellore Institute of TechnologySchool of Computer Science and Engineering, Vellore Institute of TechnologyAbstract Wireless Sensor Networks (WSN) are built with miniature sensor nodes (SN), which are deployed into the geographical location being sensed to monitor environmental conditions, which transfer the sensed physical information to the base station for further processing. The sensor nodes frequently experience node failure as a result of their hostile deployment and resource limitations. In WSN, node failure can cause a number of issues, namely Wireless Sensor Networks topology changes, broken communications links, disconnected portions of the network, and data transmission errors. An important concern of WSN is the detecting, diagnosing and recovering of sensor node failures. In the course of this effort, an effective strategy for sensor node failure detection algorithm using the Poisson Hidden Markov Model (PHMM) and the Fuzzy-based Chicken Swarm Optimization (F-CSO) is proposed for efficient detection of sensor node faults in the WSN. The proposed work offers optimal false alarm, false positive, energy consumption, detection accuracy, network lifetime, and least delay rates. Moreover, the F-CSO provides improved localization to locate the defective sensor nodes that are present in the WSN. The proposed work is implemented in the NS2 simulator with realistic simulation parameters, and the simulation results demonstrate that the proposed work is more effective in terms of 89.5% fault detection accuracy, 19.53% throughput, 8.43% energy consumption with minimum delay and less false positive rate when it is compared with other existing state-of-art systems.https://doi.org/10.1038/s41598-024-78646-2Node faultPoisson Hidden Markov modelOptimizationFault detectionSensor node |
| spellingShingle | B Nagarajan Santhosh Kumar SVN M Selvi K Thangaramya A fuzzy based chicken swarm optimization algorithm for efficient fault node detection in Wireless Sensor Networks Scientific Reports Node fault Poisson Hidden Markov model Optimization Fault detection Sensor node |
| title | A fuzzy based chicken swarm optimization algorithm for efficient fault node detection in Wireless Sensor Networks |
| title_full | A fuzzy based chicken swarm optimization algorithm for efficient fault node detection in Wireless Sensor Networks |
| title_fullStr | A fuzzy based chicken swarm optimization algorithm for efficient fault node detection in Wireless Sensor Networks |
| title_full_unstemmed | A fuzzy based chicken swarm optimization algorithm for efficient fault node detection in Wireless Sensor Networks |
| title_short | A fuzzy based chicken swarm optimization algorithm for efficient fault node detection in Wireless Sensor Networks |
| title_sort | fuzzy based chicken swarm optimization algorithm for efficient fault node detection in wireless sensor networks |
| topic | Node fault Poisson Hidden Markov model Optimization Fault detection Sensor node |
| url | https://doi.org/10.1038/s41598-024-78646-2 |
| work_keys_str_mv | AT bnagarajan afuzzybasedchickenswarmoptimizationalgorithmforefficientfaultnodedetectioninwirelesssensornetworks AT santhoshkumarsvn afuzzybasedchickenswarmoptimizationalgorithmforefficientfaultnodedetectioninwirelesssensornetworks AT mselvi afuzzybasedchickenswarmoptimizationalgorithmforefficientfaultnodedetectioninwirelesssensornetworks AT kthangaramya afuzzybasedchickenswarmoptimizationalgorithmforefficientfaultnodedetectioninwirelesssensornetworks AT bnagarajan fuzzybasedchickenswarmoptimizationalgorithmforefficientfaultnodedetectioninwirelesssensornetworks AT santhoshkumarsvn fuzzybasedchickenswarmoptimizationalgorithmforefficientfaultnodedetectioninwirelesssensornetworks AT mselvi fuzzybasedchickenswarmoptimizationalgorithmforefficientfaultnodedetectioninwirelesssensornetworks AT kthangaramya fuzzybasedchickenswarmoptimizationalgorithmforefficientfaultnodedetectioninwirelesssensornetworks |