【作者】 刘炎艳；

【导师】 李仁发；

【作者基本信息】 湖南大学 ， 计算机应用技术， 2005， 硕士

【摘要】 无线传感器网络能实时监测、感知、采集和处理各种监测对象的信息,具有十分广阔的应用前景,是当前国际上备受关注的、多学科高度交叉的新兴前沿研究热点之一。为了有效促成无线传感器网络的应用,出现了很多急需解决的问题和必须面对的挑战。其中,如何利用无线传感器网络极其有限的能量资源,对监测范围内的分布式数据进行采集和处理,即适用于无线传感器网络的数据发布算法的研究,是无线传感器网络研究的难点之一。 本文基于分组转发下一跳节点的选择方式,将适用于无线传感器网络中的路由算法分为四类(洪泛/受限洪泛路由算法、层次式路由算法、以数据为中心的路由算法和基于位置信息的路由算法),同时按照数据存储的方式,将目前常用的适用于无线传感器网络的数据发布方案分为三类(基于外部存储的数据发布方案、基于局部存储的数据发布方案以及以数据为中心存储的数据发布方案),并采用数学分析的方法对其性能进行了初步评估。对基于局部存储数据发布方案的TTDD算法和基于以数据为中心存储数据发布方案的GHT算法进行了仿真分析,仿真结果表明,GHT算法比TTDD算法能更有效的降低网络的总通信量,而TTDD算法比GHT算法具有更好的终端节点移动支持性和网络负载均衡性。根据对这两种算法及其代表的数据发布方案的分析,针对于其中存在的问题,提出一种基于局部存储的位置制导数据发布方案,并根据该方案的核心思想提出一种具体算法——基于位置索引的数据发布算法(GBI)。该算法采用数据本地存储机制和位置索引机制,来均衡网络中节点的资源消耗,提供对终端节点移动的支持。在NS-2网络模拟器上添加了GBI算法模块,实现了对GBI算法的仿真实验,并根据实验结果将其与GHT和TTDD算法进行对比、分析、评价。实验结果表明,GBI算法能更好的均衡网络中节点的资源消耗,提高对终端节点移动的支持,并能较好支持网络的能源有效性。更多还原

【Abstract】 Wireless sensor network is a new hot research area, which is interdisciplinary and can widely be used for civil and military applications, for monitoring, sensing, collecting and processing information of interested objects. Although there are many invaluable applications for wireless sensor networks, there are a lot of problems which must be handled and challenges that must be solved. It is the hottest and most difficult problem among research on sensor networks that how to efficiently use the stringent energy to collect and process distributed data of objects in monitored area. And the research on data dissemination algorithms for wireless sensor network are designed to tackle this problem.Based on the election of next hop in packet forwarding, this thesis classified currently popular routing protocols for wireless sensor network (WSN) into four categories which are flooding/limited flooding routing, hierarchical routing, data-centric routing and location-based routing. And the paper also classified currently popular data dissemination schemes for WSN into three categories by the means of data storage, which are external storage-based (ES), local storage-based (LS) and data-centric storage-based (DCS). Through mathematical analysis, we have made a basic performance evaluation on the algorithms. We also make simulations for the two typical algorithms, TTDD and GHT. By the way, TTDD is an algorithm based on the idea of LS, and GHT is an algorithm based on the idea of DCS. The simulation results show that GHT can more efficiently decrease entropy amount among a network than TTDD does, but TTDD can support nodes’ mobility and network load balance better than GHT. Based on the analysis of the two algorithms and their data dissemination schemes, to solve some problems of them, this thesis proposes a new data dissemination scheme which is based on local storage with location guidance (LSLG), and according to the new idea, we then proposes a specific algorithm, data dissemination with geographic-based index (GBI). The GBI uses the idea of data local-storage and geographic-based index to balance the resource consumption of the nodes in network and to provide support for sink mobility. Finally, we add the GBI module into NS-2 network simulator and evaluate the performance of GBI in ns-2 simulations with GBI module. The simulation results show that compared with GHT and TTDD, GBI can better balance the resource consumption of nodes in a network, improve support for sink mobility and it can satisfy the energy-efficient requests of wireless sensor network too.更多还原