无线传感器节点能量自主预测算法研究  

Research on Self-prediction Algorithm of Residual Energy for WSN

作　　者：杜永文[1] 冯珂[1] 练云翔 

机构地区：[1]兰州交通大学电子与信息工程学院,甘肃兰州730070

出　　处：《微电子学与计算机》2016年第12期113-116,120,共5页Microelectronics & Computer

基　　金：甘肃省科技计划资助项目(144NKCA040)

摘　　要：结合节点能耗模型,提出了传感器节点能量自主预测算法.算法考虑了不同工作状态对能耗的影响以及电池放电对传感器节点的影响.在TinyOS平台上实现了算法和仿真,同时在硬件上进行了实测,并对得到的仿真数据和实测数据进行分析.实验数据表明算法能比较准确地预测节点的工作时间和剩余能量.为能量感知算法提供准确的能量依据,提高节点能量使用效率和网络生命期.A self-estimation algorithm of residual energy is proposed, according to discharging process of battery and energy consumption model. The algorithm is improved to take into consideration the influence of different working conditions and the discharging time of battery. It is implemented and simulated on TinyOS, and also tested on real node device. Comparing the simulation data and measured data, the result indicates that the algorithm can more precisely predict work time and residual energy. For energy aware algorithm provide accurate energy Basis, and improve the energy efficiency and life.

关 键 词：无线传感器网络 能耗算法 能耗模型 TINYOS 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]