无线传感器网络中节点部署优化算法研究
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摘要
节点的优化部署是无线传感器网络研究中的重要领域。通过网络节点的优化部署方案不但可以满足网络的覆盖性和连通性,还可以提高路由协议和MAC协议的效率。本论文研究的一个问题是如何通过节点的部署策略来平衡网络负载,提高网络生存期;另一个研究问题是通过对移动锚节点的路径规划设计来更好的实现目标定位。论文的主要研究内容包括:
     1、研究了在无线传感器网络中部署超能节点对网络负载和生存期的作用,并提出了最小化最大瓶颈负载算法。该算法可以确定在静态网络中超能节点的最佳的部署位置和在动态网络中部署超能节点的优化移动轨迹,论文同时给出了相应的路由算法。经理论分析、仿真和实验,表明最小化最大瓶颈负载算法可有效提高网络的生存期。
     2、通过调整不同位置节点的传递半径进行能量平衡,即增大负载轻节点的传递半径,减小负载重节点的传递半径,从而达到能量平衡的目的,并根据不同节点的传递半径来进行部署。论文中给出了线性网络节点间距离与负载的关系,同时给出了提高网络生存期的最优节点密度。与均匀部署策略想比,这种基于能量平衡的部署算法显著提高了网络的生存期。
     3、提出了根据不同位置节点的能耗来分配节点的初始能量的能量分配算法,也就是耗能高的节点分配的初始能量高,耗能低的节点分配较少的初始能量,从而达到延长网络生存期的目的。
     4、对相对定位方法在减少能耗方面进行了改进。波图定位算法是一种相对定位方法,而已有的文献中没有对波距大小进行讨论,论文根据最小能耗的距离计算波距,对每个节点进行相对定位,并在定位的基础上给出了基于最小能耗的路由算法,对后继节点的确定和选择给出了详细的算法。
     5、提出了一种基于移动信标的双圆定位算法,即在一个静态的待定位的网络中部署一个动态的信标节点或者锚节点,这个锚节点分别围绕两个圆心绕圆环运动,通过这种环绕完成对整个网络的双重覆盖,最后利用正弦定理计算每个节点的位置。本文没有采用以往的根据接收信号强度(RSSI)计算距离的方法,而只是根据信号强度决定节点在不同的圆心坐标系下的角度,这种算法在RSSI与距离的关系成反比的情况下,可以达到较高的定位精度,并且移动路径和定位方法简单,可实现性强。
Optimal node placement is a very challenging problem in wireless sensor networks (WSNs). The optimized deployment strategy can be helpful for various layers of the communication protocol stack. In this paper, research works studied include: 1) How to design optimization deployment strategy for balancing the energy consumption and improving the network lifetime. 2) How to optimize the path planning of the mobile beacon for the sensor network location.
     The benefits of a heterogeneous architectures composed of a resource rich mobile node and a large number of simple static nodes are investigated in this paper. The mobile node can either act as mobile relay or mobile sink. The strategy of minimizing traffic of bottleneck nodes is proposed to find the optimal location of the mobile resource rich node. We first consider a line network, and compute the lifetime for different deployment algorithms for four cases 1) when the resource rich node is placed close to the sink 2) when the resource rich node is placed on the middle of the line network 3) when the resource rich node is placed on the optimal place of the line network 4) when the resource rich node and sink are jointly deployed. We find that when the resource rich node and sink are jointly deployed it will result in the maximum improvement in lifetime of line network. We then investigate the performance of a circular dense network with one mobile relay, and results show the improvement in network lifetime over an all static network. The mobility and routing algorithms are jointly considered in this strategy to balance the network traffic and prolong the network lifetime.
     A distance-based energy efficient sensor placement (DBEEP) strategy is proposed for lifetime maximization. The relations of adjusted distance, communication range, network radius and the number of nodes are studied in this paper, on which the network can be jointly optimized to satisfy different demands. In simulations, we demonstrate that the energy consumption on DBEEP strategy is much less than that on the other strategies.
     Initial energy assignment (IEA) strategy is another static deployment strategy. The IEA strategy is proposed according to their energy consumption for lifetime maximization. In the two-tier sensor network architecture, the IEA strategy can be used for the second-tier of relay nodes. The location and energy level of the sensors are given to optimize the load balance and prolong the network lifetime.
     An efficient routing algorithm based on hop distance without location information is investigated in this study. The wave mapping coordinate (WMC) system is considered to address the localization problem, and the wave distance of WMC is optimized according to the optimal hop distance. The simulation results confirm the high routing performance of WMC systems.
     A double-circle localization algorithm based on a single mobile beacon aware of its position is presented in this paper. The mobile beacon rotates around two central points. The whole area will be covered two times in this strategy by the mobile beacon. And the location of every sensor can be obtained by the sine theorem. The RSSI is not used to calculate the distance of sensors and the mobile beacon; it is only used to estimate their polar angle of two coordinate systems. And the path that mobile beacon should travel along has been optimized. In this case, a fundamental research issue is the planning of the path that the mobile beacon should travel along in order to minimize the localization error as well as the time required to localize the whole network. The experimental results show that the accuracy of the localization is good for most applications.
引文
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