蚁群算法在无线传感器网络路由协议中的应用研究

发布时间：2018-10-14 16:51

【摘要】：随着当代信息科技的不断发展,无线传感器网络在人们的日常生活中越来越受到重视,其应用范围现已涉及军事、医疗、环境等诸多领域。无线传感器网络的三大主要功能包括数据采集,数据处理以及数据传输,它是由众多静止的传感器节点以自行组织和多跳的方式构成的网络。其核心技术是如何选取一条合理并且高效的通信路由,这也是决定网络整体性能的重要依据。近年来,低功耗自适应集簇分层型协议、能量有效的阈值敏感路由协议、定向扩散协议、洪泛法,以及以数据为中心的自适应通信路由协议等传统的路由协议往往无法满足无线传感器网络的实际需求,因此文章提出了基于改进后的蚁群算法的无线传感器网络路由协议。本文的核心工作如下 1、文章介绍了基本蚁群算法的原理和适用范围,总结出了基本蚁群算法在求解最优路径问题时,虽然具有很强的发现较优解的能力,但是存在容易陷入局部最优解和收敛时间过长等问题。考虑到基本蚁群算法在无线传感器网络路由上应用的不足,文章提出了一种改进后的蚁群算法,并将其应用到传感器网络路由中。该算法不仅在状态转移概率公式中引入罚函数以及动态权重因子,而且采用局部信息素更新和全局信息素更新结合的方式更新路径信息,可以更加高效、全面地进行寻优。防止基本蚁群算法较早的陷入局部最优解。 2、该算法模型充分考虑到传感器节点与节点间的传输距离,并且充分考虑传感器节点的剩余能量,提出了一种智能、动态、扩充性良好的路由选择传输方式来获取有效且节能的通信路由。最后通过仿真实验,得到了基本蚁群算法以及焦斌等人改进后的蚁群算法和本文改进后的蚁群算法在传感器节点剩余能量和传输数据包时网络延迟的不同曲线,验证了本文改进后的蚁群算法在无线传感器网络路由选择上的高效性,实验结果表明本文改进后的蚁群算法能有效的降低传感器网络中节点与节点之间的传输能耗,最大程度上延长了整个网络的生存周期。该算法具有很强的扩展性,因此特别适合大规模的网络结构。
[Abstract]:With the development of modern information technology, wireless sensor networks (WSN) have been paid more and more attention in people's daily life. The application of WSN has been involved in military, medical, environmental and other fields. The three main functions of wireless sensor networks (WSN) include data acquisition, data processing and data transmission. It is a network composed of many static sensor nodes organized by themselves and multi-hop. Its core technology is how to select a reasonable and efficient communication route, which is also an important basis to determine the overall performance of the network. In recent years, low power adaptive clustering protocols, energy-efficient threshold sensitive routing protocols, directional diffusion protocols, flooding methods, Traditional routing protocols, such as data-centric adaptive communication routing protocols, are often unable to meet the actual needs of wireless sensor networks. Therefore, an improved ant colony algorithm based routing protocol for wireless sensor networks is proposed in this paper. The core work of this paper is as follows: 1. This paper introduces the principle and application scope of basic ant colony algorithm, and concludes that the basic ant colony algorithm has a strong ability to find a better solution in solving the optimal path problem. However, there are some problems such as easy to fall into local optimal solution and long convergence time. Considering the deficiency of basic ant colony algorithm in wireless sensor network routing, this paper proposes an improved ant colony algorithm and applies it to sensor network routing. The algorithm not only introduces penalty function and dynamic weight factor into the formula of state transition probability, but also updates path information by combining local pheromone update with global pheromone update. In order to prevent the basic ant colony algorithm from falling into the local optimal solution earlier. 2, this algorithm model fully considers the transmission distance between sensor nodes and nodes, and fully considers the residual energy of sensor nodes, and proposes an intelligent and dynamic algorithm. The extended route choice transmission mode to obtain the effective and energy-efficient communication route. Finally, through the simulation experiments, the different curves of the network delay between the sensor node residual energy and the transmission packet are obtained by the basic ant colony algorithm, the improved ant colony algorithm of Jiao Bin and the improved ant colony algorithm in this paper. The experimental results show that the improved ant colony algorithm can effectively reduce the transmission energy consumption between nodes in wireless sensor networks. The life cycle of the whole network is extended to the maximum extent. This algorithm has strong expansibility, so it is especially suitable for large scale network structure.
【学位授予单位】：陕西师范大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP212.9;TN915.04;TP18

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