.png){kind=icon}
返回
Trust Evaluation Sensing for Wireless Sensor Networks
.png){kind=icon}
PRE
AI
DOI：10.1109/TIM.2009.2036483.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Sensing reliability is an important issue in wireless sensor networks due to generally existing failures in sensor nodes. In this paper, we focus on the issue of sensing reliability in an acoustic target localization application, and a reputation-based algorithm is proposed to assure sensing reliability. Similar to the random sampling consensus (RANSAC), we select multiple subsets of nodes to roughly estimate target locations each time and choose the best subset receiving the most support from all nodes to compute the final target locations. The effectiveness and the efficiency of the algorithm are ensured by accurate estimation of the contamination ratio of node data. We define a node's reputation to indicate its sensing reliability, and the contamination ratio of the node can be represented by the reputation. As time passed, a node's reputation will gradually be evolved to the true value by exerting the Dirichlet process. In the experiments, we investigate several common failures in the sensor network. The results verify that the method can effectively detect unreliable measurements and improve the localization performance.
Keyword:
Acoustic target localization
random sampling consensus (RANSAC)
reputation system
sensing reliability
trust evaluation
wireless sensor networks (WSNs)
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.9
论文数:
2.0W
被引数:
5.8W
机构
引用论文
分享收藏Agent collaborative target localization and classification in wireless sensor networks.png)
SENSORS
OAAI
SENSORSIF3.5
OAAI分享收藏Living isomerization polymerizations of alkenylcyclohexane with camphyl α-diimine nickel catalystsPolymer
PolymerIF0
PREAI
分享收藏
查看更多内容