无线传感器网络基站位置优化算法研究

发布时间：2018-09-13 08:04

【摘要】：无线传感器网络是由大量无线传感器节点组成的自组织分布式网络,现在已经被广泛地应用在各个领域。它的主要特点是资源严格受限,尤其是能量受限,这直接影响了整个网络的生存时间。为了使网络能够长时间工作,节能问题显得特别重要。本文从基站位置优化的角度出发研究了延长无线传感器网络生存时间的方法,主要工作如下:(1)介绍了无线传感器网络的发展前景、研究现状以及与网络生存时间相关的技术,包括无线传感器网络生存时间的定义、覆盖控制、路由协议、基站位置优化技术等。(2)使用最优化理论对无线传感器网络的系统模型进行数学建模,分析了优化无线传感器网络生存时间的方法;针对Greedy算法不能均衡网络能量分布的缺点,通过引入潜能值的概念,提出了基于能量感知的无线传感器网络基站位置的优化算法。仿真结果表明,新算法可以很好地均衡网络能量分布,进一步延长了无线传感器网络生存时间。(3)提出了基于遗传算法的无线传感器网络基站移动算法。首先,结合潜能值的概念对无线传感器网络的最优基站位置进行建模;其次,使用标准遗传算法来求解此模型,针对标准遗传算法“早熟”的问题,使用分层遗传算法重新求解该数学模型,遗传算法求解的结果即为基站在下一轮数据收集时最优位置。仿真结果表明,遗传算法可以快速求解基站的移动路径,使用基站移动算法可以更进一步延长无线传感器网络的生存时间。
[Abstract]:Wireless sensor network (WSN) is a self-organized distributed network composed of a large number of wireless sensor nodes, which has been widely used in various fields. Its main feature is that the resource is strictly limited, especially the energy limitation, which directly affects the lifetime of the whole network. In order to make the network can work for a long time, energy-saving is particularly important. In this paper, the methods of prolonging the lifetime of wireless sensor networks are studied from the point of view of base station location optimization. The main work is as follows: (1) introduce the development prospects of wireless sensor networks, the current research situation and the technologies related to the lifetime of wireless sensor networks. Including the definition of the lifetime of wireless sensor networks, coverage control, routing protocols, base station location optimization technology. (2) the use of optimization theory to model the system model of wireless sensor networks, This paper analyzes the method of optimizing the lifetime of wireless sensor networks, and aiming at the disadvantage of Greedy algorithm which can not balance the energy distribution of wireless sensor networks, by introducing the concept of potential value, puts forward an optimization algorithm of base station location based on energy perception in wireless sensor networks. Simulation results show that the new algorithm can balance the network energy distribution well and further prolong the lifetime of wireless sensor networks. (3) A base station mobility algorithm based on genetic algorithm is proposed. Firstly, the optimal base station location of wireless sensor networks is modeled with the concept of potential. Secondly, the standard genetic algorithm is used to solve this model, aiming at the problem of "precocity" of standard genetic algorithm. The hierarchical genetic algorithm is used to solve the mathematical model again. The result of the genetic algorithm is the optimal position of the base station in the next round of data collection. The simulation results show that the genetic algorithm can solve the mobile path of the base station quickly, and the survival time of the wireless sensor network can be further extended by using the base station mobility algorithm.
【学位授予单位】：南京邮电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN929.5;TP212.9

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