Particle-swarm-based rapid optimization deployment method for wireless network sensors
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A wireless sensor and particle swarm optimization technology, applied in network planning, network topology, wireless communication, etc., can solve problems such as limited search space, achieve the effects of simplifying calculations, improving optimization speed, and accelerating solution speed
Active Publication Date: 2014-07-23
BEIJING INSTITUTE OF TECHNOLOGYGY
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[0009] The above-mentioned traditional particle swarm optimization algorithm has a limited
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Embodiment 1
[0046] In view of the above basic ideas, the wireless sensor network targeted by this embodiment is specifically: the wireless sensor network has n wireless sensors, and the sensing radius of each wireless sensor is r, and they are all deployed in a 2-dimensional space. The wireless sensor network of the method is as follows figure 1 As shown, it can be achieved by the following steps:
[0047] Step 1. Establish the particle swarm of the wireless sensor network. There are M 2n-dimensional particles in the particle swarm; at the current time t, for the i-th 2n-dimensional particle, i=1~M, randomly generate a 2n-dimensional position x id (t) and velocity v id (t) as the initial position and initial velocity of the particle, where x id (t)=(x 1 ,y 1 ,x 2 ,y 2 ,x 3 ,y 3 ,...,x n ,y n ), (x 1 ,y 1 )~(x n ,y n ) is the coordinate value of the 1st to nth sensors, v id (t)=(v 1 ,v 2 ,...,v 2n ), v 1 ~v 2n for position x d The change speed of each dimension coordin...
Embodiment 2
[0072] In order to further illustrate the above-mentioned problems, the improved particle swarm algorithm used in the present invention and the traditional particle swarm algorithm are simulated on the wireless sensor network coverage problem. Consider 20 sensors deployed in an area of 40×40m 2 in the area. The size of the particle population is 20, the detection range of the sensor is r=5m, and for the probability detection model, the parameter is r e =0.1r,α 1 =1,α 2 =0,β 1 =1,β 2 =0. The parameter of particle swarm optimization algorithm is set as c 0 =0.4,c 1 =c 2 =1.496, the number of iterations is 1000, the number of iterations set here. The grid size is considered to be 1×1m 2 , that is, 1600 grid points are used to calculate the coverage.
[0073] Considering 50 random experiments, the algorithm performs as image 3 and shown in Table 1. The results show that the improved particle swarm optimization algorithm (d-PSO) has a faster convergence speed, and the...
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Abstract
The invention discloses a particle-swarm-based rapid optimization deployment method for wireless network sensors. The method is capable of improving a global optimization effect of a particle swarm optimization algorithm (PSO) and reducing particle resource use and greatly speeding up a solution speed. The method is as follows: using a feasible solution of each kind of deployment of the wireless network sensors as a particle to establish a particle swarm and initiating the speed and position of each particle and setting an iteration number and using the PSO to perform iterative search on the particles, wherein a disturbance term is added when the speed of the particles is updated; after the iterative search is performed for the set iteration times, obtaining a final optimization result so as to realize particle swarm optimization; the PSO using an effective coverage rate of a wireless network as a fitness; and the disturbance being the product of a disturbance amplitude and a random number selected through standard normal distribution and increasing or decreasing the proportion of the disturbance term through changing the disturbance amplitude. The particle-swarm-based rapid optimization deployment method for the wireless network sensors is suitable for the PSO to obtain a comparatively satisfactory solution under a condition that the number of particles is significantly small.
Description
technical field [0001] The invention relates to the technical field of wireless sensor networks, in particular to a method for deploying optimal coverage nodes of wireless network sensors based on improved particle swarms, and is especially suitable for situations where the number of sensors is large and rapid deployment is required. Background technique [0002] A wireless sensor network consists of some tiny, cheap and low-power sensor nodes. Wireless communication can be realized within a limited distance. It is currently a research hotspot due to its potential applicability in many fields. It is widely used in area surveillance. [0003] However, based on the characteristics of wireless sensor networks, there are some challenging issues now. Sensors have limited communication range and lifetime. Therefore, sensors must be deployed within a certain communication range. The problem of network coverage is a hot issue in regional monitoring. The coverage of wireless se...
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