Multi-population coevolution method for optimizing wireless sensor network topology

Abstract

The invention relates to the field of robustness optimization of network topology and provides a multi-population coevolution method for optimizing wireless sensor network topology. The method comprises the following steps: (S100) generating initial individuals of each population based on source topology; (S200) selecting parent individuals from each population, and carrying out crossover operator operation, so as to generate new filial generations; (S300) randomly selecting a certain number of individuals from the individuals of the populations, and carrying out mutation operator operation; (S400) after crossover mutation of each population is finished, carrying out fitness function screening, and selecting outstanding individuals for the next generation; (S500) carrying out immigration among the populations, so as to generate gene exchange among the populations; and (S600) circularly carrying out the steps (200) to (500), storing the most individual topology in each generation, judging the number of evolution generations, and exiting the circulation after reaching a set number of evolution generations.

Description

technical field [0001] The invention relates to the field of network topology optimization, in particular to a multi-population co-evolution method for optimizing wireless sensor network topology. Background technique [0002] The Internet of Things technology is a huge complex that integrates multiple disciplines, including WSNs, embedded systems, topology query, intelligent control, data processing, and task scheduling. The Internet of Things has become more and more demanding in recent years. It usually deploys a large number of sensor nodes in a certain geographical area. These nodes communicate with each other to form a network system to monitor and control physical variables in the environment, such as temperature. , sound, light, etc., and can independently complete specified tasks according to environmental needs. In recent years, due to the advantages of wireless sensor networks such as wireless connection and self-organization, the application environment has not ...

AI Technical Summary

Problems solved by technology

[0005] The present invention mainly solves the technical problem that the wireless sensor network in the prior art has poor robustness against malicious attacks, and proposes a multi-population cooperative evolution method for optimizing the topology of the wireless sensor network, based on complex network theory, combined with scale-free The relevant technical characteristics of the network make the network topology have high robustness in the face of random attacks and malicious attacks

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