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Sensor network node optimal deployment method based on improved differential evolution algorithm

A technology of sensor network and evolutionary algorithm, which is applied in the field of improved differential evolutionary algorithm, can solve the problems of high algorithm complexity and insufficient stability, and achieve the effect of meeting coverage requirements, strong adaptability, and accelerating convergence speed

Active Publication Date: 2019-07-26
JIANGXI UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

However, the algorithm complexity in the prior art is high and not stable enough

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  • Sensor network node optimal deployment method based on improved differential evolution algorithm
  • Sensor network node optimal deployment method based on improved differential evolution algorithm
  • Sensor network node optimal deployment method based on improved differential evolution algorithm

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Embodiment Construction

[0037] Combine below Figure 1-12 The present invention is further described, but the protection scope of the present invention is not limited to the content.

[0038] For the sake of clarity, not all features of an actual embodiment are described. In the following description, well-known functions and constructions are not described in detail since they would obscure the invention with unnecessary detail and should be considered in the development of any actual embodiment. , a great deal of implementation detail must be worked out to achieve the developer's specific goals, such as changing from one embodiment to another in accordance with system-related or business-related constraints, and it should also be recognized that such development work may be complex and time-consuming Yes, but just routine work for those skilled in the art.

[0039] The sensor network node optimal deployment method based on the improved differential evolution algorithm is characterized in that: it ...

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Abstract

The invention discloses a sensor network node optimal deployment method based on an improved differential evolution algorithm, which is successfully applied to node optimal deployment of a wireless sensor network, and improves the diversity of initial populations by setting chaos mapping group initialization. An elite group is used to realize the guidance of a variation vector, and the global optimization speed of the group is accelerated. A parameter adaptive adjustment mechanism is used to enhance the adaptive capacity of the algorithm to the node. The method has the advantages that comparedwith a basic differential evolution algorithm, the node coverage rate and the convergence rate of the improved algorithm are greatly improved, meanwhile, possible emergencies of the nodes can be effectively coped with, and the adaptive capacity of the algorithm is enhanced. The improved differential evolution algorithm effectively prevents the population from falling into local optimum, and improves the optimization capability of the algorithm. Compared with a differential evolution algorithm before improvement, the network coverage rate is increased by about 5%, the coverage requirement of amonitoring area is met, the convergence speed is increased, and the improved algorithm has high adaptability.

Description

technical field [0001] The invention relates to a sensor network node optimization deployment method based on an improved differential evolution algorithm, in particular to an improved differential evolution algorithm for improving the effective coverage of wireless sensor nodes. Background technique [0002] Wireless sensor network is an ad hoc network formed by sensor nodes deployed in the monitoring area. It has the characteristics of small size, low cost, and low power consumption. It can assist in real-time perception, collection, and processing of monitoring object information. Environmental monitoring, disaster early warning, etc. Whether the deployment location of wireless sensor network nodes is appropriate has a direct impact on network performance and network life cycle. The deployment density of nodes will affect the network coverage. Although a high deployment density can achieve higher coverage, it will generate a large number of redundant nodes and reduce the...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W16/18H04W84/18H04W4/021
CPCH04W16/18H04W84/18H04W4/021Y02D30/70
Inventor 王振东刘燔桃胡中栋李大海温卫
Owner JIANGXI UNIV OF SCI & TECH
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