[1]王昌达,徐芹宝,宋泽,等.WSN中基于逐级重建的Provenance增量压缩[J].哈尔滨工程大学学报,2018,39(04):736-743,777.[doi:10.11990/jheu.201609086]
 WANG Changda,XU Qinbao,SONG Ze,et al.Provenance increment compression based on gradual reconstruction in WSNs[J].hebgcdxxb,2018,39(04):736-743,777.[doi:10.11990/jheu.201609086]
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
39
期数:
2018年04期
页码:
736-743,777
栏目:
出版日期:
2018-04-05

文章信息/Info

Title:
Provenance increment compression based on gradual reconstruction in WSNs
作者:
王昌达 徐芹宝 宋泽 毛健
江苏大学 计算机科学与通信工程学院, 江苏 镇江 212013
Author(s):
WANG Changda XU Qinbao SONG Ze MAO Jian
School of Computer Science and Telecommunication Engineering, Jiangsu University, Zhenjiang 212013, China
关键词:
无线传感网络多级分簇溯源增量传输逐级重建分段传输
分类号:
TP393
DOI:
10.11990/jheu.201609086
文献标志码:
A
摘要:
在无线传感器网络(WSN)中,一般使用溯源(Provenance)对基站(BS)接收的数据进行可信性评估。针对当前的Provenance分段传输方法平均压缩比较低,并且只有当获取所有Provenance分段后才可以解码Provenance等问题,提出了一种基于逐级重建的Provenance增量传输方法,即在WSN多级分簇基础上,运用整数素因子分解具有唯一性这一性质,首次传输最粗粒度的Provenance,其余每次只传输各个粒度之间的增量信息,实现了在解码Provenance时BS能够按粒度从高到低逐级重建Provenance,因此有效克服了上述现有Provenance分段传输方法平均压缩比低、在未获得全部Provenance分段前不能解密等问题。理论分析与实验数据显示,与传统的Provenance分段传输方法相比,本方法在Provenance压缩比、鲁棒性以及能耗方面均优于当前存在的Provenance分段传输方法。

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备注/Memo

备注/Memo:
收稿日期:2016-09-28。
基金项目:国家自然科学基金项目(61672269);江苏省科技成果转化项目(BA2015161);江苏大学拔尖人才计划(1213000013).
作者简介:王昌达(1971-),男,教授,博士生导师.
通讯作者:王昌达,E-mail:changda@ujs.edu.cn
更新日期/Last Update: 2018-04-11