摘要
为实现容延网络(DTN)长期运行的高网络可达率,提高DTN的传输性能,提出了1种网络场景与路由度量映射模型。以DTN标准数据集为样本,研究分析DTN特征参数,提出了运用k-means聚类算法对动态DTN场景分类的方法。利用时间图结合Floyd算法的方法统计信息时效期内的网络可达率。采用破坏性方法建立网络场景与路由度量的映射模型。仿真结果验证了该模型的有效性。
Aiming to accelerate the long-term network delivery rate and improve network transmission performance of delay tolerant networks （DTN）,a mapping model of network scenarios and routing metrics is proposed here .A network scenarios classification method based on k-means clustering algorithm is proposed by taking real standard trace datasets as samples and analyzing DTN network characteristics .The network delivery rate in time to live （ TTL） is computed using the temporal graph and Floyd algorithm .A mapping model of network scenarios and routing metrics is constructed using the destructive analysis method .The simulation results verify the validity of the model proposed here .
出处
《南京理工大学学报》
EI
CAS
CSCD
北大核心
2016年第3期290-296,共7页
Journal of Nanjing University of Science and Technology
基金
中国博士后科学基金(2012M521291)
关键词
容延网络
网络场景分类
路由度量
K-MEANS聚类算法
时间图
FLOYD算法
网络可达率
delay tolerant networks
network scenarios classifications
routing metrics
k-means clustering algorithm
temporal graph
Floyd algorithm
network delivery rate
