基于随机几何的大规模无线传感器网络性能分析

发布时间：2018-06-19 22:53

本文选题：无线传感器网络 + 能耗　；参考：《昆明理工大学》2016年硕士论文

【摘要】：随着无线传感器网络(Wireless Sensor Networks, WSN)急剧快速地发展,其规模和应用领域、应用范围日渐扩大,而撒播节点分布的多样化,对网络拓扑结构的研究日趋复杂。因此,对大规模随机播撒的无线传感器网络性能进行研究具有深切意义。能耗问题和网络传输容量是无线传感器网络关键性能指标,同时又是其研究热点及难点。本文环绕无线传感器网络能耗和传输容量问题,针对正六边形覆盖的随机播撒大规模网络,采用随机几何理论开展了以下研究：首先,介绍了随机几何理论的概念与主要作用,针对节点分布情况,利用随机几何理论推导、计算在正六边形覆盖监测区域内,节点随机播撒分布且任意两节点通信的模型以及星型通信模型下的累积分布函数(Cumulative Distribution Function, CDF)和概率密度函数(Probability Density Function, PDF),并运用蒙特卡洛法对概率密度函数在MATLAB软件上数值仿真。其次,本文根据任意节点通信模型的概率密度函数,求得节点距离期望,进而研究距离期望下的网络点平均统计能耗。同时,为更好的体现网络能量消耗,提出节点通信概率,并利用该通信概率来研究加权网络点平均统计能耗。然后对距离期望下的网络点平均统计能耗和加权网络点平均统计能耗进行比较分析。进一步地,考虑到稀疏型网络和密集型网络,又分别对最近邻网络点平均统计能耗以及最远邻网络点平均统计能耗展开研究。通过MATLAB仿真结果表明：网络能耗受到节点分布状况较大的影响；同时,正六边形覆盖监测区域内的网络能耗相对于圆形、矩形覆盖监测区域内的网络能耗要低,寿命则相对较高。最后,考虑星型通讯模型,研究分析在CSMA协议下的网络传输容量。考虑CSMA下的节点空间分组密度、退避概率以及重传概率,将其联合得到CSMA下的网络中断概率。同时,结合编码策略,考虑在系统最大分组错误概率的情况下,研究不同的编码效率对网络传输容量的影响。通过4ATLAB数值仿真结果可以得到：网络干扰一定程度上受到空间分组密度的影响；网络传输容量则受到编码效率的制约；空间分组密度的增加会导致网络传输容量呈先增后减的趋势。而且,相同条件下,与圆形、矩形覆盖监测区域相比,正六边形覆盖监测区域内系统中断概率相对较低,而网络传输容量则相对较高。以上对无线传感器网络关键性能的研究,可为大规模随机播撒无线传感器网络减少网络能耗、增加网络寿命和传输容量提供了理论依据及参考价值。
[Abstract]:With the rapid development of Wireless Sensor Networks (WSNs) in wireless sensor networks (WSNs), the scale and application field of WSNs are expanding day by day, and the research on network topology is becoming more and more complicated with the diversification of the distribution of broadcast nodes. Therefore, it is of great significance to study the performance of large-scale random broadcast wireless sensor networks. Energy consumption and network transmission capacity are key performance indicators of wireless sensor networks. This paper focuses on the problem of energy consumption and transmission capacity of wireless sensor networks. The random geometry theory is used to study the random seeding large-scale networks with hexagonal coverage. Firstly, the concept and main functions of random geometry theory are introduced. According to the distribution of nodes, the random geometry theory is used to calculate the coverage monitoring area of hexagon. The model of random distribution and arbitrary two-node communication, the cumulative distribution function (CDFF) and the probability density function (PDFN) under the star communication model are distributed randomly, and the probability density function (PDFN) is simulated by Monte Carlo method on the MATLAB software. Secondly, based on the probability density function of any node communication model, the node distance expectation is obtained, and the network point average statistical energy consumption under distance expectation is studied. At the same time, in order to better reflect the network energy consumption, the node communication probability is proposed, and the weighted network point average statistical energy consumption is studied by using the communication probability. Then the network point average statistical energy consumption and the weighted network point average statistical energy consumption under the expectation of distance are compared and analyzed. Furthermore, considering sparse network and intensive network, the point average statistical energy consumption of nearest neighbor network and the farthest neighbor network point average energy consumption are studied respectively. The results of MATLAB simulation show that the network energy consumption is greatly affected by the distribution of nodes, and the network energy consumption in the regular hexagonal coverage monitoring area is lower than that in the circular coverage area, and the network energy consumption in the rectangular coverage monitoring area is lower than that in the rectangular coverage monitoring area. The life span is relatively high. Finally, considering star communication model, the network transmission capacity under CSMA protocol is studied and analyzed. Considering the node spatial packet density, Backoff probability and retransmission probability under CSMA, the outage probability of CSMA can be obtained by combining them. At the same time, considering the maximum packet error probability of the system, the influence of different coding efficiency on the network transmission capacity is studied. The results of 4MATLAB numerical simulation show that the network interference is affected by the spatial packet density to some extent, and the transmission capacity of the network is restricted by the coding efficiency. The increase of spatial packet density will lead to the increase of network transmission capacity first and then decrease. Moreover, under the same conditions, the outage probability of the system in the hexagonal coverage monitoring area is relatively lower than that in the circular and rectangular coverage area, and the transmission capacity of the network is relatively high. The above research on the key performance of wireless sensor networks can provide theoretical basis and reference value for large-scale random broadcast wireless sensor networks to reduce network energy consumption and increase network life and transmission capacity.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP212.9;TN929.5

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