无线传感网中基于移动汇聚节点的节能路由算法研究

发布时间：2018-07-20 21:36

【摘要】：近年来,云计算技术越来越受研究者欢迎。利用云计算技术,无线传感网可以支持从底层到上层应用。无线传感网一旦部署到目标区域,就能够对目标区域进行实时感知,这都得益于网络中节点之间能够相互协作。现实生活中的诸多领域都涉及到了无线传感网,例如军事领域、农业领域、智能医疗领域等等。由于节点的能量一般由电池供电,再加上应用环境的约束,很难进行节点能量的更换或者补给。因此,实现节点能量的高效利用成为了设计无线传感网路由协议中的重点也是难点。在传统路由协议中,最为常见的是节点与汇聚节点之间采取多跳通信。然而由于汇聚节点是固定不动的,越靠近汇聚节点的传感器需要转发大量的数据包,这些节点的能量将会快速消耗并过早死亡,也就产生所谓的“热节点”,这种现象被称为“能量空洞”。近年来,研究者们提出了移动汇聚节点的思想,在延长网络生命周期上有着显著的表现。相比较于基于固定汇聚节点的传感网,该方法能够缓解热节点问题并平衡网络的能量消耗。本文针对基于移动汇聚节点的无线传感网中的节能路由算法进行研究,从而提高网络的生命周期,主要工作如下:(1)本文综述了基于移动汇聚节点的无线传感网路由协议具有的特点以及引入移动汇聚节点所带来的挑战,根据移动汇聚节点的移动特点将路由协议分为了三类并进行了比较分析。分析MECA算法和PEGASIS算法所存在的缺点,并结合这两种算法的优点,改进它们存在的不足之处。(2)针对由于汇聚节点移动导致的频繁路由重构问题,提出一种基于移动汇聚节点的动态路由调整节能算法,通过设置了一些通信规则来管理簇头节点的路由调整,实现了每当汇聚节点移动后,不会出现整个网络路由重构的现象。簇头轮换机制有效缓解了热节点的问题,同时也避免了频繁的簇头选择和簇内路由重建。(3)本文结合了分簇算法、蚁群算法和移动汇聚节点策略,进一步提高了网络的整体性能。考虑了簇头节点之间的距离,从而改进蚁群算法中的距离启发因子,提高了算法的全局搜索能力并应用到无线传感器网络中,用于规划出汇聚节点访问所有簇头的最佳移动轨迹。
[Abstract]:In recent years, cloud computing technology is becoming more and more popular. With cloud computing technology, wireless sensor networks can support applications from the bottom to the top. Once deployed to the target area, the wireless sensor network can perceive the target area in real time, which is due to the cooperation between nodes in the network. Many fields in real life involve wireless sensor network, such as military field, agriculture field, intelligent medical field and so on. It is difficult to replace or recharge the node energy because of the battery power supply and the constraints of the application environment. Therefore, the efficient use of node energy has become the key point in the design of wireless sensor network routing protocol. In traditional routing protocols, multi-hop communication between nodes and convergent nodes is the most common. However, because the convergent nodes are stationary, the sensors near the convergent nodes need to forward a large number of packets, and the energy of these nodes will be consumed quickly and die prematurely, thus creating so-called "hot nodes". This phenomenon is called an energy hole. In recent years, researchers have proposed the idea of mobile convergence node, which has a remarkable performance in prolonging the network life cycle. Compared with the sensor networks based on fixed convergent nodes, the proposed method can alleviate the problem of thermal nodes and balance the energy consumption of the networks. In this paper, the energy-saving routing algorithm in wireless sensor networks based on mobile convergence nodes is studied to improve the network life cycle. The main work is as follows: (1) this paper summarizes the characteristics of wireless sensor network routing protocols based on mobile convergence nodes and the challenges brought by the introduction of mobile convergence nodes. The routing protocols are divided into three categories according to the mobile characteristics of mobile convergence nodes and are compared and analyzed. The shortcomings of MECA algorithm and PEGASIS algorithm are analyzed, and their shortcomings are improved by combining the advantages of these two algorithms. (2) aiming at the problem of frequent routing reconfiguration caused by converging node movement, MECA algorithm and PEGASIS algorithm are analyzed. This paper proposes a dynamic routing adjustment and energy-saving algorithm based on mobile convergence node. By setting some communication rules to manage the routing adjustment of cluster head nodes, it can realize that the whole network route reconfiguration will not occur every time the convergent node moves. The cluster head rotation mechanism can effectively alleviate the hot node problem and avoid frequent cluster head selection and intra-cluster routing reconstruction. (3) this paper combines clustering algorithm ant colony algorithm and mobile convergence node strategy to further improve the overall performance of the network. Considering the distance between cluster head nodes, the distance heuristic factor in ant colony algorithm is improved, and the global searching ability of the algorithm is improved and applied to wireless sensor networks. It is used to plan the optimal trajectory for convergent nodes to access all cluster heads.
【学位授予单位】：扬州大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN929.5;TP212.9

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