基于局部决策融合的无线传感器网络诊断方法研究

项目名称： 基于局部决策融合的无线传感器网络诊断方法研究

项目编号： No.61202369

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 计算机科学学科

项目作者： 杨俊杰

作者单位： 上海电力学院

项目金额： 25万元

中文摘要： 开展无线传感器网络故障诊断技术研究对提高传感器网络的可用性具有重要的意义。在大规模的无线传感器网络中，传统的集中式故障诊断方法存在诊断开销大、局部故障区域状态获取不准确等不足。本课题致力于研究一种基于局部决策融合机制的传感器网络诊断方法，课题拟通过研究局部节点状态信息与网络故障之间的关联性，通过采用高效的决策融合模型来检测和推理网络中出现的异常和导致故障的原因。研究围绕以下几方面展开：1）研究基于统计关联排序机制的节点状态特征提取方法，并建立状态信息与网络故障的关联模型；2）研究基于改进D-S理论的节点诊断证据融合模型，实现一致性的局部故障诊断；3）研究局部诊断的故障发现机制，通过设计基于融合树的决策融合算法，提高故障诊断的效率。与传统的传感器网络诊断技术相比，基于局部决策融合的故障诊断方法仅需要局部节点的状态信息，不仅可以有效降低故障诊断的开销，还能够在局部得到一致而又准确的诊断结果。

中文关键词： 局部决策融合；无线传感器网络；故障诊断；；

英文摘要： Fault diagnosis is an important factor to improve the robustness of wireless sensor networks. In large scale sensor networks,the sink-based diagnosis methods cause large overhead and always have difficulty in getting the network status from the problematic area.To overcome these disadvantages,a local evidence fusion diagnosis scheme for wireless sensor network is proposed in this project.The diagnosis scheme tries to study the relationship between the network status and the fault causes.Then,it focuses on an evidence fusion model which is used to detect the network faults and to infer the root-cause of faults.The research include three parts. In the first part, a data feature extraction method based on statistic correlation sequence is first to be studied, then the correlaton models between the network status and the faluts are to be proposed. In the second part, to achieve consistent diagnosis results, an improved D-S theory is to be used to conduct evidence fusion.Finally, in the third part, the fault dection scheme for the local evidence fusion diagnosis is to be studied in detail. In order to improve the diagnoses efficiency, appropriate fusion algorithms based on fusion-tree should also be proposed. Compared with sink-based diagnoses,the local evidence fusion diagnosis needs only information from local nod

英文关键词： local evidence fusion；wireless sensor network；fault diagnoses；；