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Energy source minimization arrangement method of radio-frequency energy capturing wireless sensor network based on particle swarm optimization

A particle swarm optimization and wireless sensor network technology, applied in wireless communication, network planning, network topology, etc., can solve the problems of high cost and many layout methods, and achieve the effect of reducing the number and saving economic costs.

Active Publication Date: 2016-06-29
ZHEJIANG UNIV OF TECH
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AI Technical Summary

Benefits of technology

This technology helps optimize placement of wireless sensors by optimizing their performance with specific frequencies used during operation. By repeatedly testing different combinations of these frequencies until they achieve maximum efficiency or reduce cost-effectiveness compared to traditional methods like placing multiple batteries at various locations within an area where monitoring occurs over time.

Problems solved by technology

Technological Problem: In order to optimize the deployment of sensors at different locations within a specific area while reducing interference between signals transmitted over multiple paths, we propose placing certain types of energy transducers close enough together along their pathways without causing them being too much affected on one another's performance.

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  • Energy source minimization arrangement method of radio-frequency energy capturing wireless sensor network based on particle swarm optimization
  • Energy source minimization arrangement method of radio-frequency energy capturing wireless sensor network based on particle swarm optimization
  • Energy source minimization arrangement method of radio-frequency energy capturing wireless sensor network based on particle swarm optimization

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Embodiment Construction

[0029] The present invention will be further described below.

[0030] A particle swarm optimization-based radio frequency energy harvesting wireless sensor network energy source minimization arrangement method, comprising the following steps:

[0031] (1.1) Firstly, according to the coordinates of sensor nodes capable of capturing radio frequency energy in N given positions in the wireless sensor network, calculate the minimum coverage circle center of the N nodes; where N is the total number of sensor nodes, N The minimum covering circle of a node refers to the circle that covers all N nodes and has the smallest radius;

[0032] (1.2) Initialize the number K=1 of radio frequency energy transmission sources;

[0033] (1.3) For i=1,2,...,M, do the following: Initialize the initial position of the i-th particle For any j=1,2,…,K, and Initialize the initial velocity vector v of the i-th particle as the abscissa and ordinate of a point randomly selected in the minimum cove...

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Abstract

The invention relates to an energy source minimization arrangement method of a radio-frequency energy capturing wireless sensor network based on particle swarm optimization. From the beginning of an initial state that the wireless sensor network does not have a radio-frequency energy source, the following two steps are executed repetitively: a new radio-frequency energy sending source is additionally deployed; and improvement of K energy source positions based on particle swarm optimization is carried out; when a new energy source is additionally deployed every time, the initial position, the initial speed and the optimal position of each particle are necessary to initialize; then, the energy source position optimal operation based on particle swarm optimization is executed; and, for each K value, if the optimal deployment of K energy positions satisfies capturing power requirements of all sensor nodes after improvement of the energy source positions based on particle swarm optimization is executed, the energy source minimization arrangement method is ended. The energy source minimization arrangement method of the radio-frequency energy capturing wireless sensor network based on particle swarm optimization provided by the invention is capable of effectively reducing the arrangement number of energy sources and saving the economical cost.

Description

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Claims

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Application Information

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Owner ZHEJIANG UNIV OF TECH
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