摘要
针对传统的基于分簇的无线传感器网络(WSNs)信任评价模型中,簇头节点因负担大量的计算工作而降低网络生存时间的问题,提出一种通过人工免疫评估WSNs中节点信任值的方法。该方法运用阴性选择算法产生检测器,由基站根据检测器进行节点的信任检测,不需要簇头节点聚合成员节点的信任值,只要求簇头节点将成员节点的信任属性发送给基站,降低了簇头节点的负担,延长了WSNs的生存时间。仿真实验结果表明,该方法在延长网络生存时间的同时,与已有方法相比具有较高的检测率,在非信任节点数不超过40%时,检测率高于90%。
Aiming at the problem that the network lifetimes of cluster head nodes are reduced because of a large number of computations to do in traditional trust evaluation models of wireless sensor networks（WSNs） based on clustering,an artificial immune method is proposed to evaluate the trust values of nodes in WSNs. Base stations use detectors generated by the negative selection algorithm for trust detection of nodes. Cluster head nodes send the trust properties of member nodes to base stations instead of aggregating the trust values of member nodes. The burdens on the cluster head nodes are cut and the lifetimes of WSNs are extended. The simulation results show that the method proposed here extends network lifetimes and has higher detection rates compared with＆nbsp;existing methods. When the percentages of non-confidence nodes are not more than 40% , the detection rates are above 90% .
出处
《南京理工大学学报》
EI
CAS
CSCD
北大核心
2014年第3期318-324,共7页
Journal of Nanjing University of Science and Technology
基金
国家自然科学基金(60903027
61272419)
江苏省973项目(BK2011023)
关键词
人工免疫
无线传感器网络
信任检测
分簇
簇头节点
信任值
阴性选择算法
检测器
基站
成员节点
artificial immunity
wireless sensor networks
trust detection
clustering
cluster head nodes
trust values
negative selection algorithm
detectors
base stations
member nodes
