Optimization Of Wireless Sensor Networks Base On Genetic Algorithms

Wireless sensor network consists of a large number of low-cost, Low power consumption, multifunctional sensor nodes. Configuration of sensor nodes can be accessibly placed in the areas of need and some special conditions, eliminating the high cost of cable network distribution and cumbersome maintainence shortage. Design of wireless network could refer to infrastructure requirement. However, in wireless sensor networks, an important but critical problem is: the energy consumption of wireless sensor nodes greatly limits the working life. The paper combining the application of genetic algorithm for wireless sensor networks in multi-objective optimization, taking into account the needs of specific application, a sensor network in the open pit slope detection example is introduced.This paper designs the slope detection network networking strategy to develop the appropriate coding scheme, combined with various important parameters, and establish a network robustness function. In the same conditions, the paper applied of the serial genetic algorithm, parallel genetic algorithm and quantum genetic algorithm for network energy optimization. Simulation results show that: network design based on genetic algorithm optimization of energy management, achieve the longest life cycle of the network, genetic algorithm parameters by comparing the three reached the final quantum genetic algorithm is better than the other two genetic algorithm is more superior.