无线传感器网络中高效能分簇路由算法研究

发布时间：2018-07-03 15:13

本文选题：无线传感器网络 + 分簇路由　；参考：《山东师范大学》2014年硕士论文

【摘要】：无线传感器网络是由大量具有特定功能的传感器节点通过自组织的无线通信方式，相互传递信息，协同完成特定功能的智能专用网络。由于其自身特点，无线传感器网络已在众多的领域中得到应用，具有巨大的应用价值。而正是由于其广阔的应用前景和巨大的应用价值，近年来在国际上引起了广泛的关注，并且越来越多的人投身于无线传感器网络技术的研究。但是，由于无线传感器网络中节点间传输、处理数据等均需要依靠电池供电，而无线传感器网络特殊的工作环境又致使更换电池很困难甚至是不可能的。因此，设计高效能路由算法以尽可能降低平均能耗，延长网络生命周期是无线传感器网络中的关键问题。针对无线传感器网络能量有限且负载不均衡问题，为提高能量利用率进而延长网络生命周期，提出一种基于分簇的节能路由策略。首先，通过经线和纬线对网络进行动态分区。利用非均匀分簇的思想将网络划分为大小不等的区域，离汇聚节点较近的区域形成的簇规模较小，数量较多，这样簇首消耗在簇内通信和数据聚合上的能量就少，从而能够补偿由于转发外层区域簇首数据包而所需的能量，进而实现能耗均衡。分区完成后再根据节点的地理位置和剩余能量为每个分区选出最优簇首。然后，，非簇首节点选择与自身距离较小且剩余能量较大的簇首加入，从而构建成簇。最后，完成数据的传输过程。由于在组织成簇和选择中继转发节点时均考虑距离和剩余能量的因素，从而在一定程度上进一步均衡了网络中的能耗。另外，又对数据融合算法进行了研究。在利用LEACH算法划分网络的基础上，首先通过阈值的设置来减少非簇首节点的数据发送量，降低非簇首节点因发送相似数据而消耗的能量。然后通过延迟时间的设置让簇首能够在接收到足够多的数据后再进行数据融合，以此来保证数据的准确性。最后对簇首收集的数据取平均值，大大减少了簇首与基站间的通信量，降低了簇首节点的能耗。仿真结果表明:两种算法均能优化网络能耗，延长网络生命周期。
[Abstract]:Wireless sensor network (WSN) is a special intelligent network which is composed of a large number of sensor nodes with specific functions. Because of its own characteristics, wireless sensor networks have been applied in many fields and have great application value. Because of its wide application prospect and great application value, it has attracted wide attention in the world in recent years, and more people devote themselves to the research of wireless sensor network technology. However, due to the transmission between nodes in wireless sensor networks, data processing needs to rely on battery power supply, and the special working environment of wireless sensor networks makes it difficult or even impossible to replace batteries. Therefore, designing a high performance routing algorithm to minimize the average energy consumption and prolong the network life cycle is a key problem in wireless sensor networks. Aiming at the problem of limited energy and unbalanced load in wireless sensor networks, an energy saving routing strategy based on clustering is proposed to improve energy utilization and prolong network life cycle. First, the network is dynamically partitioned by longitude and weft. Using the idea of non-uniform clustering, the network is divided into regions of different sizes. The cluster size is smaller and the number of clusters is larger in the region near the convergence node, so the cluster head consumes less energy in the communication and data aggregation within the cluster. It can compensate for the energy needed by forwarding the cluster head packets in the outer region, and then realize the energy balance. After the partition is completed, the optimal cluster head is selected for each partition according to the location of the node and the residual energy. Then, the non-cluster head nodes are selected to join the cluster heads with small distance and large residual energy, so as to form clusters. Finally, the data transmission process is completed. Because the factors of distance and residual energy are taken into account in organizing clusters and selecting relay forwarding nodes, the energy consumption in the network is further balanced to a certain extent. In addition, the data fusion algorithm is studied. On the basis of the Leach algorithm to divide the network, the threshold is set to reduce the amount of data transmission and the energy consumption of the non-cluster head node due to the transmission of similar data. Then the delay time is set so that the cluster head can fuse the data after receiving enough data to ensure the accuracy of the data. Finally, the data collected by cluster head are averaged, which greatly reduces the communication between cluster head and base station, and reduces the energy consumption of cluster head node. The simulation results show that both algorithms can optimize the network energy consumption and prolong the network life cycle.
【学位授予单位】：山东师范大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP212.9;TN929.5

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