基于时空冗余数据清除的数据备份算法  

A data backup algorithm based on spatiotemporal correlation redundancy data clearance

作　　者：潘燕燕 陈冬隐 程红举[1,2] Pan Yanyan;Chen Dongyin;Cheng nongju(College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108,China;Fujian Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou University, Fuzhou 350108, China)

机构地区：[1]福州大学数学与计算机科学学院,福建福州350108 [2]福州大学福建省网络计算与智能信息处理重点实验室,福建福州350108

出　　处：《微型机与应用》2017年第24期54-57,61,共5页Microcomputer & Its Applications

基　　金：国家自然科学基金(61370210);福建省教育厅A类科技项目(2013JA12027);福州大学科技发展基金(2013-XQ-35)资助

摘　　要：传感器节点易受环境影响,会出现节点失效的现象,导致感知数据丢失。然而无线传感器网络是以数据为中心,因此对感知数据进行备份问题的研究显得尤为重要。针对无线传感器网络中数据备份问题,提出基于时空冗余数据清除的数据备份算法(TS_DB),该算法首先用k-means算法对网络分簇,然后挖掘出节点间的关联模式消除空间冗余数据,同时在传感节点建立一元线性回归模型消除时间冗余数据,最后根据簇头的能量进行数据备份。仿真实验表明,TS_DB算法能有效节省节点的能量,对延长网络的寿命具有重要的意义。Sensor nodes are subject to environmental impact and appear the phenomenon of node failure, leading to loss of sensing data. However, the wireless sensor network is data-centric, so it is very important to study the backup of the sensing data. In this paper, a data backup algorithm （TS_DB） based on spatiotemporal redundancy data clearance is proposed for the data backup problem in WSNs. The algorithm firstly uses the k-means algorithm to cluster the networks and then digs out the association patterns between nodes to eliminate spatial redundancy data. Meanwhile, at sensor nodes a linear regression model is established to eliminate time redundant data, and finally according to the energy of cluster head data backup is realized. Simulation results show that TS_DB algorithm can effectively save the node＇ s energy, which is of great significance to extend the life of network.

关 键 词：无线传感器网络 时空冗余数据 分簇 数据备份 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]