A MULTI-CRITERIA APPROACH BASED ON GENETIC EVOLUTION FOR FINDING THE OPTIMAL DATA TRANSMISSION ROUTE IN WIRELESS SENSOR NETWORKS

Abstract

In wireless sensor networks (WSNs), data routing is critical to ensure their efficient operation. Traditional single-criteria routing algorithms do not take into account all aspects of the dynamically changing data transmission environment, which leads to a decrease in overall network performance. The choice between single-criteria and multi-criteria routing algorithms depends on the specific conditions and requirements of the BSM. Single-criteria algorithms are suitable for simpler and more stable environments where a single parameter is critical. Multi-criteria algorithms, although more difficult to implement, provide significant advantages in adaptability and performance optimization in complex and dynamic networks.

This paper is devoted to the application of modern evolutionary computing to solve complex and multi-criteria route finding problems in modern wireless sensor networks. Genetic algorithms provide high flexibility and adaptability, which allows taking into account various criteria, which is especially important for sensor nodes with limited resources. The paper presents a multicriteria method for routing data in wireless sensor networks based on the principles of genetic evolution, taking into account the dynamically changing topology and range of nodes. A block diagram of the genetic algorithm is presented, which allows finding the optimal route based on a set of criteria, the use of which allows taking into account the specifics of wireless sensor networks. The proposed method can be applied to the implementation of both single- and multi-path routing protocols. To verify the effectiveness of the developed genetic algorithm, it is compared with the greedy one using simulation modelling. Based on the obtained results, the efficiency of the proposed solution for sensor nodes with different ranges is shown. A set of alternative routes is obtained, which is advisable to use in case of failure of the optimal route, which increases the reliability of wireless sensor networks under dynamically changing conditions.