A low-energy coverage optimization method for wireless sensor networks

Abstract

The invention discloses wireless sensor network low energy-consumption coverage optimization algorithm. On the premise of lowest energy consumption of round clusters, backbone node optimal value which can satisfy coverage capacity can be obtained. By using PSO (particle swarm optimization) to dynamically adjust flying direction and speed of nodes and a backbone node deployment scheme which uses step-by-step iteration to obtain optimal coverage, data information in a sensing area can be collected effectively, sensor network resources can be fully managed, the problems that uneven backbone node distribution, optimal backbone node number cannot be achieved, network energy consumption is unbalanced, network coverage capacity is low and the like are solved effectively, technical support is provided for reasonably effectively deploying backbone nodes to reach high network coverage uniformity and network coverage rate on the premise of low energy consumption of sensor networks, and a novel solution is provided for improving area coverage capacity of networks on the premise of network low energy consumption.

Description

technical field [0001] The invention relates to a wireless sensor network low energy consumption coverage optimization algorithm, belonging to the technical field of wireless sensor networks. Background technique [0002] A wireless sensor network is a wireless, multi-hop, self-organizing network composed of a large number of miniature wireless sensor nodes. National defense, industry, agriculture, environment, medical care, logistics, anti-terrorism, remote monitoring of dangerous areas, protection of key areas and many other fields. [0003] The problem of power supply is a major bottleneck restricting the development of wireless sensor network technology. Its system design must follow the principle of energy saving to improve energy efficiency and prolong the service life of the network. On the premise of ensuring low energy consumption of the network, at the same time, it is necessary to satisfy the perception ability of nodes in the network to the physical world, that...

AI Technical Summary

Problems solved by technology

However, there are still some problems: the randomness of the backbone node election may cause the backbone nodes to be too dense in the same area or too close to the edge of the network, the number of backbone nodes is difficult to reach the optimal value, and the network coverage cannot be effectively guaranteed, etc.

[0005] Although the above-mentioned protocols can improve the hierarchical routing protocols to a certain extent, they all face the same core problem, which is the selection of backbone nodes.

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