(untitled) (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Background: Energy is one of the main factors forcommunication in the Internet of Things based on sensors. Sensors are a low and non-rechargeable energy source because sensors are commonly used in places and applications where they cannot be recharged. Purpose: The most important goal of this study is to reduce the energy consumption of sensors and increase the lifetime of the Internet of Things network using genetic algorithm while selecting a clusterhead and routing between clusterheads. Methods: In this paper, after distributing nodes in the network, the genetic algorithm is used to select the cluster heads and also to create a route between the cluster heads to the base station. After selecting the cluster head by the genetic algorithm, the normal nodes join thecluster head and send their data to it. After collecting the data and processing them, the data is transferred to the base station from the route specified by the genetic algorithm. Results: The proposed algorithm is implemented with MATLAB simulator and compared with LEACH, MB-CBCCP and DCABGA protocols. The simulation results show that the proposed algorithm works better than the mentioned algorithms in different environments. Conclusion: Due to energy constrained and the fact that in most applications the batteries can not be recharged, the use of optimization algorithms in designing and implementation of routing and clustering algorithms has a significant impact on expanding the lifetime of these networks.