摘要
近些年来,将优化算法应用到节点定位问题当中成为了一个研究热点.本文假设下一次定位结果为准确坐标,对前后两次定位结果邻居节点之间距离关系进行深度分析和推导,得到一个邻域函数.在此基础上根据贪婪思想,提出了贪婪定位算法.为了达到更精确的定位结果,本文将贪婪定位算法分成两个阶段:第一阶段,根据贪婪迭代优化得到一组初始定位结果;第二阶段将满足一定条件的未知节点升级为锚节点,重新执行第一阶段的过程,重复第二阶段,直到没有未知节点可以升级为锚节点为止.实验结果表明,无论是定位精确度还是算法执行时间,本文所提算法都比当前的一些优化定位算法要好.
Using optimization algorithm to solve the node localization problem has become a research focus .This paper makes deep analysis on the distance relationship between two successive localization results and designs a neighborhood function , and then proposes the greedy localization algorithm based on greedy idea .The proposed algorithm is divided into two phases .In the first phase ,a set of estimated positions is generated based on the greedy iterative optimization .In the second phase ,some unknown nodes will be elevated to anchor nodes ,and the first phase is executed again .The second phase is repeated until there is no node that can be elevated to an anchor node .Finally ,the experimental results show the proposed algorithm achieves more accurate result and take less time than the existing optimization localization algorithms .
出处
《电子学报》
EI
CAS
CSCD
北大核心
2014年第2期328-334,共7页
Acta Electronica Sinica
基金
国家自然科学基金(No.60903159
No.61173153)
中央高校基本科研业务费(No.110818001
No.100218001
No.110404014
No.110318001)
沈阳市科技计划项目(No.1091176-1-00)
中国博士后科学基金(No.20110491508
No.2012T50248)
关键词
节点定位
优化算法
邻域函数
贪婪思想
迭代优化
node localization
optimization algorithm
neighborhood function
greedy idea
iterative optimization
