传感器网络异常时间同步数据过滤算法  

Abnormal time synchronization data filter algorithm in sensor networks

作　　者：孙纪敏[1] 沈玉龙[2] 裴庆祺[2] 马建峰[2] 

机构地区：[1]北京交通大学电子信息工程学院 [2]西安电子科技大学计算机学院,陕西西安710071

出　　处：《西安电子科技大学学报》2008年第5期910-915,共6页Journal of Xidian University

基　　金：国家自然科学基金资助(60633020,60573036,60702059,60503012);863项目资助(2007AA01Z429,2007AA01Z405);陕西省自然科学基金资助(2007F37);航空科学基金资助(2007ZD31003)

摘　　要：利用节点时间偏移的分布特性和时间同步数据的线性特征,使用概率统计中的样本空间估计理论和方法,设计时间同步数据过滤预测区间,提出基于线性回归的无线传感器网络数据过滤算法.该算法利用预测空间过滤异常时间同步数据,解决了因传感器网络数据错误率高且容易受到攻击而影响网络时间同步的难题.算法判定过程简单,避免针对异常数据而运行复杂的线性回归算法,有效降低节点的计算开销.仿真结果表明,该算法有效消除了异常数据对线性回归估计值的影响,提高了基于线性回归的传感器网络时间同步精度.The time synchronization data filter estimative region is designed and a data filter algorithm based on linear regress is presented by using the distribution feature of the time bias and the linear feature of the time synchronization of node and the theory and the method of sample space estimation in probability statistics. This algorithm uses the estimative region to filter abnormal data and solves the problem that sensor networks are so easily attacked that the time synchronization is affected due to the high error rates of sensor networks. The algorithm is simple in decision process. The algorithm is avoided on the abnormal data. The computation costs are greatly reduced. The simulation result shows that this algorithm eliminates effectively the effect of the abnormal data on the estimated values of linear regresg and increases the time synchronization accuracy.

关 键 词：无线传感器网络 时间同步 线性回归 数据过滤 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]