Study on the Application of Genetic Algorithms in the Optimization of Wireless Network

Wireless sensor network can eliminate the high cost of wired network. However, in wireless sensor networks, an important but critical problem is the energy consumption of 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. Fitness function is designed according to the application of open-pit mine slope detection system. In the same conditions, using serial genetic algorithm, parallel genetic algorithm and quantum genetic algorithm for network energy optimization. Simulation results show that: genetic algorithm optimize the energy consumption, achieve the longest life cycle of the network. By comparing these three kinds of genetic algorithms, the quantum genetic algorithm is much better than the other two genetic algorithms in optimizing the energy consumption.