文献类型：期刊文献

英文题名：A Novel Cluster-Based Wireless Sensor Network Reliability Model Using the Expectation Maximization Algorithm

作者：Yang, Jianfeng Chen, Jing Huo, Yujia Liu, Yanyu

第一作者：杨剑锋

通信作者：Yang, JF[1]

机构：[1]Guizhou Inst Technol, Sch Data Sci, Guiyang 550003, Peoples R China;[2]Guizhou Univ Tradit Chinese Med, Coll Informat Engn, Guiyang 550025, Peoples R China;[3]Tongren Univ, Sch Data Sci, Tongren 554300, Peoples R China

第一机构：贵州理工学院

通信机构：corresponding author), Guizhou Inst Technol, Sch Data Sci, Guiyang 550003, Peoples R China.|贵州理工学院;

年份：2021

卷号：2021

外文期刊名：JOURNAL OF SENSORS

收录：;EI(收录号：20211410182408);Scopus(收录号：2-s2.0-85103550935);WOS:【SCI-EXPANDED(收录号:WOS:000636387500001)】；

基金：This work was supported by the National Natural Science Foundation of China (No. 71901078), Science and Technology Foundation of Guizhou (QianKeHeJZi[2015]2064, QianKeHeLHZi[2015]7249, and QianKeHeLHZi[2016]7108), Advanced Talents Project (XJGC20150106), and Special Key Laboratory of Artificial Intelligence and Intelligent Control of Guizhou Province (QianJiaoHeKY[2020]001).

语种：英文

外文关键词：Geographical regions - Image segmentation - Maximum likelihood estimation - Maximum principle - Reliability

摘要：Wireless sensor networks (WSNs) have been used widely across various industries and business fields that require the coverage of large geographical regions that are difficult for humans to reach. It is therefore important to be able to model, assess, and predict the reliability of WSNs. Masked data is a type of missing data used to represent system failure when the exact cause of the failure is unknown. This paper proposed a novel additive reliability model for a cluster-based WSN system using general masked data and uses the expectation maximization (EM) algorithm to solve the problem of the maximum likelihood estimation (MLE). Moreover, the proposed model assumes that a WSN comprises several clusters, and the failure processes of these clusters are independent. The probability characteristics of the system are determined according to the topology of the WSN system to evaluate the system reliability. Finally, the proposed model is demonstrated to be powerful for estimating WSN system reliability using a simulated dataset.