Improved leach routing method for wireless sensor networks based on chaotic genetics

Abstract

The present invention relates to an improved LEACH clustering routing method CGA-LEACH (an improved LEACH algorithm for wireless sensor network based on chaotic genetic algorithm) based on chaotic genetic wireless sensor network, the method includes system model, population initialization, fitness function construction And four parts of chaotic genetic operation. Construct a fitness function by considering energy consumption and load, use conditional chaotic mapping to generate real coded chromosomes, and use chaotic genetic selection, crossover and mutation operations to improve the convergence speed and find the optimal cluster head, thus forming a uniform distribution and energy consumption and load-balanced cluster structure. Ultimately, the network life cycle is effectively extended, the network load is balanced, and the energy efficiency of the network is improved.

Description

technical field [0001] The present invention relates to a wireless sensor network routing method, in particular to an improved LEACH routing method CGA-LEACH (an improved LEACH algorithm for wireless sensor network based on chaotic genetic algorithm) based on chaotic genetics. By constructing a new fitness function, and use chaotic genetic selection, crossover and mutation operations to form a cluster structure with uniform distribution, energy consumption and load balance, thereby prolonging the network life cycle. Background technique [0002] As one of the most important and basic information collection technologies in the real world, wireless sensor networks (WSNs) measure thermal, infrared, sonar, and seismic signals in the surrounding environment through nodes with built-in sensors. . Due to the limited resources of wireless sensor network nodes such as energy, how to save energy to prolong the network life cycle is the most important challenge for wireless sensor net...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to solve the problem of uneven clustering and high energy consumption caused by the existing LEACH clustering routing method ignoring node energy and random election of cluster heads, and constructing a system that considers energy and load by performing global optimization through chaotic genetics The fitness function, based on the function value, performs chaotic genetic selection, crossover and mutation operations, finds the optimal cluster head and its corresponding cluster members to form an optimized cluster structure, thereby improving the energy efficiency of the network and prolonging the network life cycle

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