A Novel Cuckoo Search Structure Optimized Neural Network for Efficient Data Aggregation in Wireless Sensor Network

• Published in: 2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS) pp. 941 - 947
• Main Authors: Vimal Kumar Stephen, K., Mathivanan, V., Kumar, K.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2020
• Subjects: and Cuckoo Search Structure Optimized Neural Network; Artificial neural networks; Cuckoo Search (CS); Data aggregation; Energy consumption; Energy resolution; Metaheuristics; mobile sink; Scalability; Sensor phenomena and characterization; Wireless Sensor Network (WSN); Wireless sensor networks
• DOI: 10.1109/ICICCS48265.2020.9121070

Mobile Wireless Sensor Network (WSN) can be used to solve various issues confronted by static WSN. A mobile sink adheres to diverse mobility patterns in the region of sensors such as controlled mobility, fixed/predictable mobility, and random mobility. Backbone construction can help decrease energy usage. The functioning of sensor nodes needs high levels of energy which are later optimized for the WSN's effective performance. Optimizers are algorithms utilized to modify the attributes of the neural network, such as weights and learning rates, to decrease the losses. Cuckoo Search (CS), a fairly new metaheuristic, is presently used extensively to resolve various kinds of issues related to optimization. The work examines the new cuckoo search structure optimized neural network Energy-Aware Secure Tree-based Virtual Backbone Network (EAST_VBN) and its ability to minimize the adjustment of energy usage in nodes to improve the WSN's network lifetime.