传感器网络自主划分时段的预测采样机制  

An Sampling Mechanism with Autonomous Portioned of the Interval in Sensor Networks

作　　者：陈天笑[1] 周四望[1] 林亚平[1] 伍振兴[1] 

机构地区：[1]湖南大学软件学院,长沙410082

出　　处：《微计算机信息》2010年第7期89-91,共3页Control & Automation

摘　　要：在无线传感器网络中,调整节点的采样频率是减少冗余数据传输的一种有效方法。基于一元线性回归模型,提出了一种自主划分时段的自适应采样机制,在采样周期内根据数据波动的情况自主划分时段,同时为各个时段分配相应的采样频率。模拟实验表明,对存在一定周期性的环境监测数据,该机制使能源得到合理利用,延长传感器节点的工作时间。The sampling mechanism is a kind of efficient method for decreasing the redundancy of data flow in wireless sensor networks.Based on linear regression model,a sampling mechanism of sensors network using the autonomous partition of the interval is proposed.In our proposed scheme,the interval can be partitioned independently based on the fluctuation of data flow,and then assigns appropriate sampling rate for each interval.Simulation shows that our scheme can make reasonable utilization of energy.And the sampling mechanism of sensors network can extend the life span of node as long as possible on the premise of accuracy for peri-odic environment data.

关 键 词：传感器网络 预测 采样 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]