摘要
无线传感器网络集成了传感器技术、嵌入式计算技术、分布式信息处理技术、现代网络及无线通信技术，将数字化的信息世界与自然存在的物理世界融合在一起，改变了人类与客观世界的交互方式，是未来物联网的重要组成技术之一。在无线传感器网络中，节点通过无线通信的方式自组织形成网络系统，以实现对监测区域中对象的信息感知和处理。本文研究了无线传感器网络的自组织技术，较好地解决了无线传感器网络中随机分布节点的组网、网络边界的生成和网络配置的定量等问题。论文的主要工作如下：
介绍了无线传感器网络研究的发展历程，总结了无线传感器网络应用领域，概述了无线传感器网络自组织技术目前的研究现状。
在与其它传统无线网络拓扑控制机制比较的基础上，归纳了无线传感器网络分簇算法和路由算法应具有的特性，并对近年来针对无线传感器网络提出的代表性的算法进行了研究，总结了各种算法的特点和适合的应用场合，重点分析了它们的不足之处，最后指出了无线传感器网络分簇和路由算法未来发展的趋势。
分析了节点均匀分布下的重叠分簇算法的性能，克服了以往的分簇算法的不足，提出了一种节点非均匀分布下自组织重叠分簇算法Nu-SOAC；通过改进簇头选举机制，减少簇内通信能耗，提出了改进的自组织重叠分簇算法SOAC，该算法能较好的应用于多种节点分布情况。仿真实验验证了算法在节点均匀和非均匀分布情况下均能取得较好的性能。
考虑了节点的连接密度、剩余能量以及节点相对基站的位置，提出了针对基站位置固定的无线传感器网络的一种基于节点位置和分布密度的多跳自组织分簇算法SACN；在此基础上进行优化了成簇方式，减少了簇内广播通信，针对基站位置已知的情况，提出了一种性能更优的分布式自组织平衡分簇算法DSBCA，通过仿真分析验证其能够有效生成结构更为均衡的分簇结构，延长网络的生存周期。
分析了无线传感器网络的边界搜索算法的的研究现状，指出了先前研究的不足，从更可靠的分簇结构的角度出发，提出了基于分簇结构，对分簇边界进行融合的边界搜索算法，并通过仿真分析验证了基于分簇的边界搜索的可行性和可靠性。
讨论了无线传感器网络配置的相关研究情况，针对节点的均匀分布的情况，建立了分析模型，分别就簇内单跳通信和多跳通信进行了讨论，得出了节点能量的基本要求和最优的节点通信半径；针对节点随机分布的情况，进行定量分析，将单分簇的分析的结论推广到一般情况下，给出了实现最小的全网络能耗的最优分簇半径的定量分析。
Integrated with sensor, embedded computer, distributed information processing,modern network and wireless communication technology, Wireless Sensor Networks(WSNs) merge information world and the physical world to change the interactionsbetween human being and nature. WSNs are important component technology of theInternet of things. In WSNs, the wireless sensor nodes construct network system in theform of self-organization to process information of monitored objects. This paper studiesthe self-organization technology of WSNs，and solves the networking of random nodes,formation of network boundary and quantity of network configuration commendably.
The main content can be outlined as follows:
Firstly, the brief history of WSNs is introduced, and then the application fields ofWSNs are summarized. This paper outlines the present situation of self-organizationtechnology of WSNs.
Secondly, this paper induces specialities which the clustering and routing algorithmsof wireless sensor networks should have, basing on WSNs with other traditional wirelessnetworks, and then studies recent representative algorithms for the wireless sensornetworks. After that, it sums up the characteristics and the appropriate application, pointingout the limitation of them emphatically. The future trends of the algorithms are put forward.
Thirdly, the performance of the overlapping clustering in uniform distribution of nodesis analysed, and then we overcome the shortage of the previous clustering algorithms to putforward the Self-organization Overlapping Algorithm for Clustering in Non-uniformdistribution (Nu-SOAC). By improving electing mechanism of cluster head and reducingenergy consumption of communication in the cluster, this paper proposes the improvedSelf-organization Overlapping Algorithm for Clustering (SOAC), which can deal withmany kinds of distribution. The results of simulations indicate that the algorithms achieveideal performance in uniform distribution and random distribution.
Fourthly, essentially different from the previous clustering algorithms, whenconsidering residual energy of nodes in WSNs with random distribution, we propose aSelf-Organization Algorithm for Clustering Basing on Node Position and Connection Density (SACN) to generate clusters. On the basis of SACN, the Balancing ClusteringAlgorithm with Distributed Self-Organization (DSBCA) is come up with, with optimizingelecting mechanism of cluster head and decreasing energy consumption of communicationin the cluster. The performance of the novel algorithm is illustrated with a series ofsimulated tests, which indicate that the new algorithm can establish more balanceableclustering structure effectively and enhance the network life cycle obviously.
Fifthly，the paper discusses the present situation of boundary search algorithm ofWSNs and points out the deficiency of previous studies. Different from former boundarysearch algorithm basing on single node, we carry out fusing clusters borderline to formboundary of WSNs based on overlapping clusters, then Moreover, the results ofsimulations points out that the algorithm generates the network boundary feasibly andreliably.
Sixthly, basing on the wireless sensor network related research of the configuratingWSNs, in view of the node uniform distribution, we establishes the analysis model ofsingle hop and multiple hops communication respectively to calculate the basic demand ofnode energy and the optimal node communication radius. In the situation of the noderandom distribution, with the conclusion of quantitative analysis in single cluster expandedto the general case, the minimum of the network energy and optimal clustering radius arefigured out.
Finally, the entire research is summarized, following with the future work discussions.
引文
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