Coyote Optimization Using Fuzzy System for Energy Efficiency in WSN
Source abstract
Abstract
In recent days, internet of things is widely implemented in Wireless Sensor Network (WSN). It comprises of sensor hubs associated together through the WSNs. The WSN is generally affected by the power in battery due to the linked sensor nodes. In order to extend the lifespan of WSN, clustering techniques are used for the improvement of energy consumption. Clustering methods divide the nodes in WSN and form a cluster. Moreover, it consists of unique Cluster Head (CH) in each cluster. In the existing system, Soft-K means clustering techniques are used in energy consumption in WSN. The soft-k means algorithm does not work with the large –scale wireless sensor networks, therefore it causes reliability and energy consumption problems. To overcome this, the proposed Load-Balanced Clustering conjunction with Coyote Optimization with Fuzzy Logic (LBC-COFL) algorithm is used. The main objective is to perform the lifespan by balancing the gateways with the load of less energy. The proposed algorithm is evaluated using the metrics such as energy consumption, throughput, central tendency, network lifespan, and total energy utilization.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Energy Efficient Wireless Sensor Networks · IoT-based Smart Home Systems · Energy Harvesting in Wireless Networks
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (27)
Show source-provided references
1. Improved soft-K-means clustering algorithm for balancing energy consumption in wireless sensor networks10.1109/JIOT.2020.3031272 ↗
2. Coyote optimization based on a fuzzy logic algorithm for energy-efficiency in wireless sensor networks10.1109/ACCESS.2020.3029683 ↗
3. LBCM: Energy-efficient clustering method in wireless sensor networks
4. I-SEP: An improved routing protocol for heterogeneous WSN for IoT-based environmental monitoring10.1109/JIOT.2019.2940988 ↗
5. Multisource energy harvesting system for a wireless sensor network node in the field environment10.1109/JIOT.2018.2865431 ↗
6. Refractive index sensor using dual core photonic crystal fiber–glucose detection applications10.1016/j.rinp.2018.09.055 ↗
7. A survey of clustering techniques in WSNs and consideration of the challenges of applying such to 5G IoT scenarios10.1109/JIOT.2017.2726014 ↗
8. Cluster head selection for energy efficient and delay-less routing in wireless sensor network10.1007/s11276-017-1558-2 ↗
9. An energy-efficient compressive sensing-based clustering routing protocol for WSNs
10. A wearable embedded device for chronic low back patients to track lumbar spine position
11. Fuzzy-based cluster head selection and cluster formation in wireless sensor networks10.1049/iet-net.2018.5102 ↗
12. An enhanced energy-efficient routing protocol for wireless sensor network
13. Hybrid meta-heuristic optimization based energy efficient protocol for wireless sensor networks10.1016/j.eij.2018.01.002 ↗
14. Novel bacteria foraging optimization for energy-efficient communication in wireless sensor network
15. Increasing the lifetime of sensor networks by a data dissemination model based on a new approximation algorithm10.1016/j.adhoc.2020.102084 ↗
16. Solving the load balanced clustering and routing problems in WSNs with an fpt-approximation algorithm and a grid structure10.1016/j.pmcj.2019.101033 ↗
17. Mobile data gathering with load balanced clustering and dual data uploading in wireless sensor networks10.1109/TMC.2014.2338315 ↗
18. An application-specific protocol architecture for wireless microsensor networks10.1109/TWC.2002.804190 ↗
19. A hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks
20. Teen: A routing protocol for enhanced efficiency in wireless sensor networks. in null
21. Load-balanced clustering of wireless sensor networks
22. Energyefficient multilevel heterogeneous routing protocol for wireless sensor networks10.1109/ACCESS.2019.2900742 ↗
23. Energy consumption reduction for asynchronous message-passing applications10.1007/s11227-016-1926-1 ↗
24. ECH: An enhanced clustering hierarchy approach to maximize lifetime of wireless sensor networks10.1109/ACCESS.2019.2933052 ↗
25. An efficient load balancing scheme of energy gauge nodes to maximize the lifespan of constraint oriented networks10.1109/ACCESS.2020.3015941 ↗
26. A novel cluster head selection algorithm based on fuzzy clustering and particle swarm optimization10.1109/TCBB.2015.2446475 ↗
27. Energy efficient routing protocol for wireless sensor network