CUCKOO-ANN Based Novel Energy-Efficient Optimization Technique for IoT Sensor Node Modelling

Wireless sensor networks (WSNs) based on the Internet of Things (IoT) are now one of the most prominent wireless sensor communication technologies. WSNs are often developed for particular applications such as monitoring or tracking in either indoor or outdoor environments, where battery power is a critical consideration. To overcome this issue, several routing approaches have been presented in recent years. Nonetheless, the extension of the network lifetime in light of the sensor capabilities remains an open subject. In this research, a CUCKOO-ANN based optimization technique is applied to obtain a more e ffi cient and dependable energy e ffi cient solution in IoT-WSN. The proposed method uses time constraints to minimize the distance between sources and sink with the objective of a low-cost path. Using the property of CUCKOO method for solving nonlinear problem and utilizing the ANN parallel handling capability, this method is formulated. The resented model holds signi fi cant promise since it reduces average execution time, has a high potential for enhancing data centre energy e ffi ciency, and can e ff ectively meet customer service level agreements. By considering the mobility of the nodes, the technique outperformed with an e ffi ciency of 98% compared with other methods. The MATLAB software is used to simulate the proposed model.

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