Wireless sensor network coverage optimization algorithm for gray wolf search of virtual force embedded Laivei flight and application

Abstract

The invention discloses a wireless sensor network coverage optimization algorithm for gray wolf search of virtual force embedded Laivei flight. The method comprises the following steps: step 1, randomly determining N node positions in wireless sensor network coverage nodes as initial positions of real nodes; step 2, initializing a solution of an initial position into a virtual node position through a modified grey wolf search algorithm embedded in the Laivie flight; step 3, searching and updating the position through the modified grey wolf search algorithm embedded in the Laivie flight; 4, calculating a virtual force through an improved virtual force algorithm; the position of each group of solution nodes is adjusted through calculation; and step 5, through the superiority and disadvantageselection rule, reserving a better solution obtained by the improved virtual force algorithm, and judging whether to update the optimal solution wolf and the optimal solution wolf through the t-th generation of the better solution until the specified update frequency is reached. 6, outputting an optimal solution wolf as an optimal node position; and step 7, completing wireless sensor node deployment through a node matching algorithm.

Description

technical field [0001] The invention relates to the field of wireless sensor coverage optimization, in particular to a wireless sensor network coverage optimization algorithm and application of gray wolf search with virtual force embedded in Levi's flight. Background technique [0002] Although the Wireless sensor network (WSN) was originally designed for military applications, WSN is currently widely used in civilian applications, including vehicle tracking, forest monitoring, earthquake observation, building monitoring, and water resource monitoring. Coverage is an important measure of WSN performance. How to use a limited number of sensor nodes to monitor the coverage target area to the greatest extent has always been one of the hot spots of WSN technology. Wireless sensors are usually randomly scattered in the monitored area, which will cause uneven distribution of nodes and lead to low coverage in the monitored area. Therefore, it is of great significance to improve the...

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Problems solved by technology

[0005] The present invention designs and develops a wireless sensor network coverage optimization algorithm for gray wolf search with virtual force embedded in Levi's flight. The coverage rate of the monitored area is low. At the same time, the present invention will use the VFLGWO algorithm to optimize the WSN node coverage problem, thereby expanding the application field of the LGWO algorithm

[0006] The present invention also designs and develops an application for wireless sensor network coverage optimization. The purpose of the invention is to solve the problem of uneven distribution of nodes when the LGWO algorithm is deployed and applied to WSN nodes, resulting in low coverage of the monitoring area.

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