摘要
在大多数无线传感网络的应用场景中,网络节点通常由不可充电的电池供电。因此,最大限度降低无线传感器网络的电池能耗是提高其性能的关键。本文针对无线传感器网络数据通信的能耗问题,提出了一种基于能耗模型的遗传优化方法,并研究了3组不同能量模型对遗传算法性能的影响。此外,在MATLAB平台上进行了60次蒙特卡洛实验,选择了提出的算法中最小能耗的最优参数集。
In most application scenarios of wireless sensor networks, the network nodes are usually powered by non-rechargeable batteries. Therefore, minimizing the battery energy consumption of wireless sensor networks is the key to improve their performance. In this paper, a genetic optimization method based on energy consumption model is proposed for the energy consumption problem of data communication in wireless sensor networks, and the effect of three different sets of energy models on the performance of the genetic algorithm is investigated. In addition, 60 Monte Carlo experiments were performed on the MATLAB platform to present the optimal parameter set selection for the minimum energy consumption in the proposed algorithm.
作者
杨丹
YANG Dan(Shaanxi Institute of Mechatronic Technology,Baoji Shaanxi 721001,China)
出处
《信息与电脑》
2022年第24期103-105,共3页
Information & Computer
关键词
无线传感网络
遗传算法
能量优化
能耗模型
wireless sensing networks
genetic algorithm
energy optimization
energy consumption model
作者简介
杨丹(1990—),女,陕西宝鸡人,硕士研究生,讲师。研究方向:最优化理论。
