对WSN中基于地理哈希表分布式数据存储与查询算法的改进

发布时间：2018-01-19 16:22

本文关键词： 无线传感器网络数据存储与查询改进GHT算法网络负载均衡通讯能耗　出处：《天津工业大学》2017年硕士论文　论文类型：学位论文

【摘要】：在无线传感器网络中实现数据的高效存储和查询是提高整体网络运行效率的关键技术,目前以数据为中心的分布式存储策略逐渐成为主流,而其中的基于地理位置哈希表(GHT)算法更是应用最广泛的一种算法。本文深入分析和研究了影响无线传感器网络中数据存储和查询的关键因素以及传统GHT算法存在的问题,进而提出了改进的GHT算法。在进行数据存储时,数据采集点将采集到的信息存储到利用Hash函数(在不同环境下可根据实际情况设定)计算出位于Hash映射位置距离最近的节点上。此时,存储节点检查自身通讯量,当超出自身通信阂值(阈值根据具体情况设置)时,此存储节点将通过Hash函数计算出另一个位于此函数位置距离最近的一个节点上,其余采集节点将会按照贪心搜索最短路径方式寻找存储点。以此类推,每个存储点都将实时计算其通讯量,在其通信量超出其自身通信阈值时做出相同策略;在进行数据查询时,数据查询节点将按照Dijkstra算法最搜索离自己最近的数据存储点。最后,本文通过仿真实验验证了改进GHT算法在地里位置感知、均衡网络负载、通讯能耗方面优于传统GHT算法以及另一种广泛使用的分布式存储的double Rulings算法。本文利用MATLAB搭建了仿真环境并编写了仿真程序,实验分别对GHT算法、double Rulings算法和改进的GHT算法在数据存储空间、数据通信量及通信负载均衡等因素上进行了仿真分析。实验结果表明改进GHT算法在均衡网络负载、通讯能耗方面优于传统GHT算法以及另一种广泛使用的分布式存储的double Rulings 算法。
[Abstract]:The efficient storage and query of data in wireless sensor networks is the key technology to improve the efficiency of the whole network. At present, the distributed storage strategy with data as the center is becoming the mainstream. And the geographical location based hash table (GHT). The algorithm is one of the most widely used algorithms. This paper deeply analyzes and studies the key factors that affect the data storage and query in wireless sensor networks and the problems of traditional GHT algorithm. Furthermore, an improved GHT algorithm is proposed, which is used for data storage. The data acquisition point stores the collected information to the node that is closest to the Hash mapping position by using the Hash function (which can be set according to the actual situation in different environments). The storage node checks its own traffic when it exceeds its own communication threshold (the threshold is set according to the circumstances). The storage node will calculate another node located in the nearest location of this function through the Hash function, and the rest of the collection nodes will search for the storage point according to the greedy search for the shortest path. And so on. Each storage point will calculate its traffic in real time and make the same strategy when its traffic exceeds its own communication threshold. When conducting data query, the data query node will search for the nearest data storage point according to Dijkstra algorithm. Finally. This paper verifies the improved GHT algorithm in the field location sensing and balancing network load through simulation experiments. Communication energy consumption is superior to traditional GHT algorithm and another widely used distributed storage double. Rulings algorithm. This paper uses MATLAB to build a simulation environment and write a simulation program. The experimental results show that the GHT algorithm double Rulings algorithm and the improved GHT algorithm are used in the data storage space. The simulation results show that the improved GHT algorithm can balance the network load. Communication energy consumption is superior to the traditional GHT algorithm and another widely used distributed storage double Rulings algorithm.
【学位授予单位】：天津工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP212.9;TN929.5

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