基于非均匀成簇的双sink环境下无线传感器网络能量空洞避免策略

发布时间：2018-03-02 10:28

本文关键词： 非均匀成簇大规模网络能量空洞负载均衡数据分流　出处：《四川师范大学》2017年硕士论文　论文类型：学位论文

【摘要】：近年来,随着微机电系统、片上系统、无线通信技术和低功耗嵌入式等技术的飞速发展,无线传感器网络被广泛应用于军事,医疗,环境监测,智能家居等领域,作为连接人类生活与物理世界的桥梁,无线传感器网络成为了国内外学者的一个研究热点。无线传感器网络中,通常以随机部署的方式将大量传感器节点部署于特定的监控区域内,传感器节点多是由自身所携带的锂电池供电,节点的能量非常有限,因此,如何有效地利用节点的能量是延长网络生命周期的关键。能量空洞问题作为影响网络能量利用效率的关键问题,广泛存在于层次式无线传感器网路中。能量空洞问题是指网络中某些区域内节点由于负载过大而提前死亡,节点死亡后,死亡节点周围的节点将承担更多的负载,从而加快这部分节点的死亡,网络出现“热区”,当死亡节点达到一定数量时,网络中剩余节点的数据将无法传输至数据汇聚点,网络生命周期结束。本文在现有能量空洞避免策略基础上,创新性地对配置了双sink的大规模无线传感器网络中的能量空洞避免问题进行了研究,提出了一种基于非均匀成簇的双sink环境下能量空洞避免策略(DEAS,double-sinks energy hole avoidance strategy)。本文的主要工作包括:(1)对簇结构与计时广播机制进行优化,以分流的方式对数据进行转发,并引入数据分流度的概念。DEAS策略假设在矩形网络两侧固定位置部署两个数据汇聚点(sink),以负责对网络相应区域内节点数据的收集。网络中,传感器节点采用非均匀成簇的方式组织,以候选簇头节点簇内普通节点的密度为依据对候选簇头的竞选半径进行优化,候选簇头采用计时广播机制竞选成为最终簇头,候选簇头广播胜选消息的时间取决于候选簇头的剩余能量和簇内的节点密度。在数据路由过程中,为使得节点间的负载更加均衡,采用拆分数据包的方式,以使得更多的节点参与到数据的转发中。并引入节点分流度的概念,以更合理地确定分发给每个中继节点的数据量。(2)为均衡双sink间节点的负载,提出一种双sink监控区域面积动态调整策略。在本文所讨论的网络环境中,节点随机非均匀部署于网络,节点不装配位置感知设备。由于网络中部署了两个sink,每个sink监控区域内节点的负载很难一致。本文提出负载差异度的概念以量化双sink间节点的负载差异。随着网络的运行,双sink间节点的负载差异度将进一步拉大,负载较大区域内的节点将更快耗尽能量,网络出现能量空洞。为使得双sink间节点的负载趋于均衡,本文采用动态调整双sink监控区域面积的方式,以实现双sink间节点负载的均衡。(3)为使得双sink监控区域面积的调整更加高效,提出一种面积调整阈值训练策略。DEAS算法中,当双sink间节点的负载差异度大于某一个临界值时,则需要调整双sink监控区域的监控面积。反之,则保持双sink监控区域的监控面积不变。本文将决定双sink监控区域面积是否需要进行调整的临界值定义为区域调整阈值。区域调整阈值的设置决定了双sink监控区域面积调整的效率,为使得双sink监控区域面积的调整过程更加高效,提出一种区域调整阈值训练机制,以获得更加合理的区域调整阈值。(4)对多sink环境下的能量空洞问题进行分析,提出启发式算法本文最后对多sink环境下的能量空洞问题进行简单分析,为解决多个sink的部署问题,本文在网络初始时根据sink的数量将网络进行分区,每个sink位于子区域的中心。并将多sink环境下的能量空洞问题划归为多个双sink环境下的能量空洞问题,提出启发式算法。本文最后将DEAS算法与LEACH,EEUC,DEBUC三种算法进行对比。证明了DEAS算法在网络生命周期与节点的能量利用率等方面具有更优的性能,证明了DEAS算法的高效性。
[Abstract]:In recent years, with the development of microelectromechanical system, system on chip, the rapid development of wireless communication technology and Low-Power Embedded Technology, wireless sensor network has been widely used in military, medical, environmental monitoring, intelligent Home Furnishing and other fields, as a bridge between human life and physical world, wireless sensor network has become a hot research topic in China foreign scholars. The wireless sensor network, usually by way of randomly deployed a large number of sensor nodes deployed in the monitoring area within a specific sensor node is a lithium battery power supply carried by itself, the energy of the node is very limited, therefore, how to effectively use the energy of the node is the key to extend the network life cycle energy. Empty problems as the key issues affecting the network energy efficiency, widely exists in hierarchical wireless sensor networks. The energy hole problem refers to a network Some nodes within the region because the load is too large and premature death, the node after the death of nodes around the dead node will bear more load, thus speeding up the part of the node's death, the network appears "hotspots", when the death node reaches a certain quantity, the remaining nodes in the network data will not be transmitted to the data sink, end the network life cycle. Based on the existing energy hole avoidance strategy based on the innovation of large-scale wireless sensor network configuration of double sink in avoiding the energy hole problem is studied, this paper proposed an energy unequal clustering based on sink double hole avoidance strategy (DEAS, double-sinks energy hole avoidance strategy). The main work of this paper includes: (1) the cluster structure and timing broadcast mechanism to optimize the data forwarding to shunt, and introduce the concept of.D data flow EAS strategy hypothesis in the rectangular network on both sides of the deployment of two fixed position data sink (sink), which is responsible for the corresponding network nodes within the region to collect data. In the network, sensor nodes with non uniform clustering approach to candidate cluster head nodes of ordinary nodes within the cluster density as the radius of the candidate cluster head election on the basis of optimization, candidate cluster head by timing broadcast mechanism campaign to become the final cluster head node density, candidate cluster head election news broadcast time depends on the candidate cluster head's residual energy and intra cluster data. In the routing process, as the load between nodes is more balanced, the resolution of data packets, in order to make more nodes to participate in forwarding data. And divided into the concept of node mobility, with more reasonable distribution to each relay node (2). The amount of data for load balancing between two sink nodes, is proposed A double sink monitoring area dynamic adjustment strategy are discussed in this paper in the network environment, non-uniform nodes are randomly deployed in the network, node assembly position sensing devices. Due to the network deployment of two sink, each sink load monitoring area node is difficult to consistent. This paper proposed a concept of load difference in order to quantify the load difference between dual sink nodes. With the operation of the network between dual sink node load difference will further widen the node load larger area will be faster to run out of energy. The energy hole network node between the double sink load balanced, the method of dynamic adjustment of double sink monitoring the area, in order to achieve load balancing between two sink nodes. (3) to make the double sink monitoring area adjustment more efficient, we propose an area to adjust the threshold training strategy of.DEAS algorithm, when the double sink The difference between the node load is greater than a critical value, the monitoring area should adjust the double sink monitoring area. On the other hand, keep monitoring area double sink monitoring area unchanged. This paper will decide whether to double sink monitoring area needs to be adjusted and the critical value is defined as the region to adjust the threshold to adjust the threshold region. Setting determines the efficiency of double sink monitoring area adjustment, to make the adjustment process of double sink monitoring area more efficiently, the paper proposes a kind of region to adjust the threshold training mechanism, to achieve regional adjustment threshold more reasonable. (4) the empty problem of multi sink environment energy analysis, put forward the question at the end of this paper, heuristic algorithm the multi sink environment energy hole analysis, problem solving for the deployment of multiple sink, based on the initial network according to sink the number of partition the network, each sink At the regional center. And the problem of sink under the environment of energy hole into multiple double sink under the environment of energy hole, heuristic algorithm is proposed. Finally, the DEAS algorithm with LEACH, EEUC, DEBUC three kinds of algorithms are compared. It is proved that the DEAS algorithm has better performance in utilization of network the life cycle and the energy of the node, proves the efficiency of DEAS algorithm.

【学位授予单位】：四川师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP212.9;TN929.5

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