一种自适应神经元无线传感器网络功率控制技术

An adaptive power control algorithm for wireless sensor networks using neural node

针对传感器网络成簇过程难以建立数学模型的特点,利用人工智能技术提出了一种采用自适应神经元控制算法调整簇头功率,进而改变网络拓扑结构的方案.本算法能够根据实时系统误差,动态调整系统的控制参数,克服了在拓扑功率控制中仅仅依靠经验选择或分级调节的局限性.仿真结果显示,通过分簇拓扑控制后,网络的生存时间和通信总量有显著的增加.

Due to the difficulty of constructing the mathematical model for wireless sensor networks, an adaptive algorithm is proposed to adjust the power of cluster heads by intelligent technology so as to change the framework of topology. This method adjusts the system parameters dynamically according to real-time error without the limitation of scalability and dependence on experiences. Simulation results show that the lifetime and throughput capacity have been increased by employing this method.