Method for optimizing coverage of nodes of wireless sensor network

A wireless sensor and coverage optimization technology, applied in wireless communication, network topology, network planning, etc., can solve problems such as slow convergence speed, affecting coverage effect, and difficulty in meeting the real-time requirements of dynamic node selection

Inactive Publication Date: 2013-08-07
JIANGNAN UNIV
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Problems solved by technology

In "Optimized Coverage Mechanism Based on Genetic Algorithm in Wireless Sensor Networks", Jia Jie et al. proposed to use genetic algorithm to achieve coverage optimization. Although genetic algorithm has strong global search ability and parallel search ability, its convergence speed is slow near the optimal solution. It is difficult to meet the real-time requirements of dynamic node selection
Wang Xu

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  • Method for optimizing coverage of nodes of wireless sensor network
  • Method for optimizing coverage of nodes of wireless sensor network
  • Method for optimizing coverage of nodes of wireless sensor network

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[0034] The method of the invention will be further described below in conjunction with the accompanying drawings.

[0035] Differential evolutionary algorithm is an evolutionary algorithm based on real number coding, and its overall structure is similar to other evolutionary algorithms. The evolutionary algorithm model for the distribution of sensing nodes in wireless sensor networks is usually established as follows: Assuming that the monitoring area A is a two-dimensional plane, the monitoring area A is divided into m×n grids, and the set of sensor nodes on the monitoring area expressed as C={c 1 ,c 2 ,...,c N}, where c i ={x i ,y i ,r} is the coverage model of node i, (x i ,y i ) is the coordinate of node i, and r is the perception radius of node i. The present invention selects a binary perception model, and considers that the coverage of a node is a circular area with the node coordinates as the center and a radius of r. For the grid point (x,y) we use the follow...

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Abstract

The invention discloses a method for optimizing the coverage of nodes of a wireless sensor network. The method is characterized in that the coverage of the nodes of the wireless sensor network is defined as a discretization plane geometry problem, wireless sensors are idealized into standard circles with radiuses within a communication range, the circles are overlapped, centers of the circles are constrained, and then the circles are optimized by an evolution mechanism of a differential evolution algorithm. Overlapped areas among the sensors need to be reduced in order to increase a regional coverage rate, and the coverage capacity of the sensors can be efficiently utilized in a non-overlapping manner. The method has the advantages that the sensors are rearranged when the quantity of the overlapped sensors is excessively high, and an experiential threshold overlapping value (for example, an optimization effect is realized when 20-40 wireless sensors are distributed in 100X100 monitored regions and the threshold overlapping value n is equal to 6) can be obtained after repeated experimental comparison.

Description

technical field [0001] The invention relates to a wireless sensor network node coverage optimization method, in particular to a wireless sensor network node coverage optimization method based on a differential evolution algorithm. technical background [0002] In recent years, the development of MEMS (Micro electro mechanical system) technology has made it possible to realize compact and low-cost mobile sensors, and more and more people have begun to pay attention to mobile sensor networks (MSN). The wireless sensor network is composed of a large number of micro-sensors with perception capabilities, computing capabilities, and communication capabilities in a self-organizing manner. The nodes in the network cooperate to complete data collection and transmission. It can be widely used in many fields such as battlefield monitoring, environmental protection, and smart home. Wireless sensor network is considered as an indispensable technology in future information transmission. ...

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Application Information

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IPC IPC(8): H04W16/18H04W24/02H04W84/18
Inventor 方伟孙俊周梦璇葛建良
Owner JIANGNAN UNIV
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