【作者】 谌业滨；

【导师】 孙利民； 舒坚；

【作者基本信息】 南昌航空大学 ， 计算机应用技术， 2010， 硕士

【摘要】 由大量随机部署于监测区域的传感器节点通过无线自组织所形成的网络能够协作地完成各种监测任务,如:战场信息收集、有毒气体监测、煤矿安全监测、海洋生态监控等,这些环境十分复杂,可能导致节点工作不稳定,甚至失效,不能完成正常监测任务。通过对无线传感器网络的自身健康状态进行监视,可及时了解网络的故障区域并采取相应措施,使得网络能够迅速从故障中恢复从而保证网络能够提供正常服务。然而,无线传感器网络是资源受限的网络,如果将每个节点所收集的健康状态消息不加处理发送给sink节点将导致网络节点特别是靠近sink的节点转发大量消息,将使节点因能耗过大而过早死亡。因此有必要对其自身健康状态进行融合。本课题来源于国家自然科学基金,对无线传感器网络自身健康状态的融合机制进行研究。论文介绍了无线传感器网络中数据融合方法的研究现状,针对无线传感器网络自身健康状态消息的整网汇报、周期性汇报特点,提出一种基于网格划分的融合树构建方法。该方法根据节点的地理位置信息将整个网络划分为网格,每个网格形成一个簇,根据节点的剩余能量及其所处的地理位置选取簇头节点,簇头节点因负责自身健康状态消息的融合、与成员节点和其他簇之间的通信,能量消耗较其他成员节点更快。为了避免簇头节点过早死亡和周期性成簇造成的不必要能量消耗,本文采取局部替换簇头节点的方法,即当簇头节点的能量低于其当选簇头时能量的一半时,则重新选取该簇的簇头。在网格簇中,论文假设多节点覆盖区域中的信息只要被一个节点感知并成功上报,那么该区域中的信息都能被感知并上报,设计了对簇内感知覆盖与簇成员节点到簇头节点的链路状态进行融合的算法。仿真实验表明,通过构建融合树,降低了平均能耗,从而延长了网络的寿命;在网格簇中,本文提出的自身健康状态融合算法能够较准确地反映网络中簇区域的节点健康状态。更多还原

【Abstract】 The network constituted by a large number of sensor nodes which deployed randomly in the monitored area by means of wireless self-organization can be used for various of monitoring tasks cooperatively, such as battle field information collection, toxic gas monitoring, coal mine safety monitoring, and marine ecological monitoring. These environments are very complex, which may lead to instable work of the sensor nodes or even failure, so that can’t competent for the monitoring task. By monitoring the self health information in wireless sensor network, the failure area can be known in time and corresponding actions can be taken, which assures the network recover from failure quickly to provide the monitoring task normally. However, wireless sensor networks are resource-constrained. If each node sends the monitored health information to the sink without any processing, the nodes, especially the nodes near the sink will forward a large number of packets, which will lead premature death of the node due to a large amount of energy consumption. So the aggregating of the self health status becomes necessary. This study comes from National Nature Science Foundation and focus on self health status aggregation.The thesis introduces the current state of the art of data fusion in wireless sensor network. For the characteristic of the self health information which is reported periodically by all the nodes, the thesis constructs an aggregation tree based on grid. The aggregation tree divides the network into grids according to the position information of the node, each grid forms a cluster. The cluster head is elected not only considers the residual energy, but also considers the position information. The cluster head will consume more energy due to take responsibility of data fusion and communicating with cluster members and other clusters. In order to avoid premature death of the cluster head and unnecessary energy consumption in reconstructing aggregation tree, the cluster head is replaced locally. Namely, the new cluster head will be reelected if the residual energy of the cluster head is less than half of the energy when it becomes cluster head.In the grid cluster, the thesis designs an aggregation algorithm that aggregates the coverage in the cluster and the link quality of the member nodes to cluster head based on the assumption that the information in a multi-node covered area can be detected and reported only if at least one of the nodes detects and reports it successfully,Simulation experiments indicate that the network consumes lesser energy and enjoys longer network lifetime through the aggregation tree. The self health status aggregation algorithm proposed in the thesis can accurately reflect the health information of the nodes in the cluster area.更多还原