CH Selection via Adaptive Threshold Design Aligned on Network Energy
Energy consumption in Wireless Sensor Networks (WSN) involving multiple sensor nodes is a crucial parameter in many applications like smart healthcare systems, home automation, environmental monitoring, and industrial use. Hence, an energy-efficient cluster-head (CH) selection strategy is imperative in a WSN to improve network performance. So to balance the harsh conditions in the network with fast changes in the energy dynamics, a novel energy-efficient adaptive fuzzy-based CH selection approach is projected. Extensive simulations exploited various real-time scenarios, such as varying the optimal position of the location of the base station and network energy. Additionally, the results showed an improved performance in the throughput (46%) and energy consumption (66%), which demonstrated the robustness and efficacy of the proposed model for the future designs of WSN applications.
Behera, Trupti M.; Nanda, Sarita; Mohapatra, Sushanta K.; Samal, Umesh C.; Khan, Mohammad S.; and Gandomi, Amir H.. 2021. CH Selection via Adaptive Threshold Design Aligned on Network Energy. IEEE Sensors Journal. Vol.21(6). 8491-8500. https://doi.org/10.1109/JSEN.2021.3051451 ISSN: 1530-437X