【作者】 赵亮；

【导师】 瞿少成；

【作者基本信息】 华中师范大学 ， 无线电物理， 2021， 博士

【摘要】 进入21世纪以来,随着传感器技术、嵌入式系统、分布式计算和无线通信技术的迅猛发展和日趋成熟,一项集感知、计算和通信能力于一体的跨学科、多元技术融合领域——无线传感器网络(Wireless SensorNetworks,WSNs)应运而生。无线传感器节点通常采用电池供电,有限的电量存储制约着其使用寿命。因此,如何对WSNs中的路由算法进行优化,以选择最短的路由进行数据传输并降低网络能耗,是WSNs中一个亟待解决的问题。另一方面,当WSNs的不同层同时出现拥塞现象时,会导致传输时延大、丢包率高以及吞吐量低等问题。因此,如何对WSNs进行合理的跨层拥塞控制,以提高其服务质量,是WSNs中的另一个研究重点。本文以WSNs中的跨层拥塞控制为研究对象,分别研究了离散滑模控制算法、自适应离散滑模控制算法和模糊滑模控制算法。然后,以ZigBee无线传感器网络中的路由算法为研究对象,研究了一种基于能量感知的快捷树路由算法,并将该算法应用到基于ZigBee技术的无线环境监测系统中。本文的主要贡献包括以下几个方面:(1)针对WSNs中传统拥塞控制方法调节时间长、稳态误差大等问题,研究了基于水槽模型和离散滑模的WSNs跨层拥塞控制。首先,通过将单容水槽、双容水槽和三容水槽的液位控制类比到WSNs中单节点、双节点和三节点的缓冲区列队长度控制,提出了一种跨越WSNs链路层和网络层的逐跳拥塞控制模型。然后,提出了一种基于指数趋近律的离散滑模控制算法(Discrete Sliding Mode Control Algorithm,DSMC),并以此作为上述模型的控制器,来合理调控拥塞节点帧缓冲区的流入、流出数据。最后,MATLAB仿真结果表明,与传统的拥塞控制策略相比,所提出的DSMC算法具有调节速度快、超调量小、稳态误差接近零等优点,从而有效缓解了 WSNs的拥塞现象。(2)针对WSNs中拥塞现象导致的能量浪费、丢包和寿命短等问题,研究了基于流体模型和自适应离散滑模的WSNs跨层拥塞控制。首先,通过在某一特定节点上对其输入和输出的数据包进行调控,提出了一种适用于WSNs传输层节点级拥塞和数据链路层链路级拥塞的跨层拥塞控制模型。然后,在此模型上,设计了一种基于指数趋近律的自适应离散时间滑模拥塞控制器(Adaptive Discrete-time Sliding Mode Congestion Controller,ADSMC),以调节瓶颈节点的列队长度到达期望值。大量NS-2.35仿真结果证明,所提出的ADSMC算法优于传统的模糊控制、PID控制以及模糊PID控制等算法,它能够较好地控制队列长度并避免拥塞,同时具有收敛快速、稳定性强、网络寿命长等优点。(3)针对WSNs跨层拥塞控制中传统滑模控制算法队列抖振较大、抗干扰能力弱等缺点,研究了基于模糊滑模控制的WSNs跨层拥塞控制。首先,通过将无线信道中的信噪比应用于TCP模型,提出了一种新的传输层与MAC层之间的跨层拥塞控制模型。然后,通过将模糊控制与滑模控制相结合,设计了一种模糊滑模控制器(Fuzzy Sliding Mode Controller,FSMC),该控制器可以自适应地调节拥塞节点缓冲区的队列长度,并显著减弱外部不确定扰动的影响。最后,在MATLAB/Simulink和NS-2.35中进行了大量的仿真,并与传统的RED、DropTail、Fuzzy、PID、SMC等拥塞控制策略进行了比较。仿真结果表明,所提出的FSMC算法可以有效地适应队列长度的变化,并且具有良好的网络性能,例如:收敛速度快、平均时延短、丢包率低和吞吐量高。(4)针对ZigBee无线传感器网络中路由选择不佳和能耗负载不均等问题,研究了一种基于能量感知的快捷树路由算法——EASTR。首先,通过在一跳范围内的邻居表中引入邻居节点的剩余能量信息,EASTR算法能够感知ZigBee节点的剩余能量。然后,在所有剩余能量大于动态能量阈值Eth的邻居节点中,选择到目的节点跳数最少的作为下一跳节点。大量NS-2.35仿真结果表明,与现有的Cluster-Tree、AODV、ZBR、STR和ESTR等路由算法相比,所提出的EASTR算法明显提升了星状、树状、网状等中小型ZigBee网络在平均时延、丢包率、吞吐量、总剩余能量等方面的性能,为改善中小型ZigBee网络的服务质量和网络寿命提供了一定的理论指导。(5)开展了 EASTR算法在ZigBee无线环境感知系统中的应用研究。首先,设计并实现了一种“小型ZigBee无线环境感知系统”。然后,将所提出的EASTR算法应用到该系统,以优化传统的ZigBee路由策略。实验结果表明,在保证传输质量和系统稳定性的前提下,EASTR算法能够有效降低ZigBee网络的能耗和丢包率,为ZigBee技术应用到无线环境实时监测领域提供了良好的理论意义与实用价值,同时也为物联网技术的广阔发展带来了新的契机。最后,对全文作出了总结,并讨论了下一步研究的方向。更多还原

【Abstract】 Since the beginning of the 21 st century,with the rapid development and gradual maturity of sensor technology,embedded systems,distributed computing and wireless communication technology,Wireless Sensor Network(WSNs),an interdisciplinary and multi-technology fusion field that integrates sensing,computing and communication capabilities,has emerged.Wireless sensor nodes are usually powered by batteries,and their service life is restricted by limited power storage.Therefore,how to optimize the routing algorithm in WSNs to select the shortest route for data transmission and reduce network energy consumption is an urgent problem in WSNs.On the other hand,when congestion phenomenon simultaneously occurs in different layers of WSNs,it will result in large transmission delay,high packet loss rate and low throughput.Hence,how to carry out reasonable cross-layer congestion control in WSNs to improve its quality of service is another research focus in WSNs.This dissertation regards cross-layer congestion control in WSNs as the research object,and studies discrete sliding mode control algorithm,adaptive discrete sliding mode control algorithm and fuzzy sliding mode control algorithm respectively.Then,this dissertation also takes routing algorithms in ZigBee wireless sensor network as the research object,and investigates a shortcut tree routing algorithm based on energy perception,and applies this algorithm to a wireless environment monitoring system based on ZigBee technology.The main contributions of this dissertation are as follows:(1)In order to solve the problems of long adjustment time and large steady-state error of traditional congestion control methods in WSNs,this paper investigates the cross-layer congestion control of WSNs based on the sink model and discrete sliding mode.Firstly,by applying water-level control of single-,double-and triple-tank to queue length control of single-,double-and triple-node,a hop-to-hop congestion control model across the link-layer and network-layer of WSNs is presented.Subsequently,a reaching-law-based discrete sliding mode control algorithm(DSMC)is proposed to regulate the inflows and outflows of node’s frame buffer.Finally,simulation results in MATLAB show that compared with conventional congestion control strategies,the proposed DSMC algorithm has advantages such as faster adjustment speed,smaller overshoot and near-zero steady-state error,thus effectively alleviating the congestion phenomenon of WSNs.(2)Aiming at the problems of energy waste,packet loss and short lifespan caused by congestion in WSNs,this paper studies the cross-layer congestion control of WSNs based on fluid model and adaptive discrete sliding mode.Firstly,by regulating incoming and outgoing packets at a particular node,this paper proposes a cross-layer congestion control model which is suitable for node-level congestion in the transport layer and link-level congestion in the data link layer of WSNs.Then,based on this model,an exponential-reaching-law-based adaptive discrete-time sliding mode congestion controller(ADSMC)is designed,which effectively adjusts bottleneck nodes’ queue length to desired value.Extensive NS-2.35 simulation results demonstrate that the proposed ADSMC outperforms conventional algorithms such as Fuzzy control,PID control and Fuzzy-PID control,it controls queue length and avoids congestion well,and has good qualities such as fast convergence,strong stability and long network lifetime.(3)In order to address the shortcomings of traditional sliding mode control algorithms such as large queue chattering and weak anti-interference ability in cross-layer congestion control of WSNs,this paper researches the cross-layer congestion control of WSNs based on fuzzy sliding mode control.Firstly,by applying the signal-to-noise ratio of wireless channel to TCP model,a new cross-layer congestion control model between transmission layer and MAC layer is proposed.Then,by combining fuzzy control with sliding mode control,a fuzzy sliding mode controller(FSMC)is designed,which adaptively regulates the queue length of buffer in congested nodes and significantly reduces the impact of external uncertain disturbance.Finally,numerous simulations are implemented in MATLAB/Simulink and NS-2.35 by comparing with traditional congestion control strategies such as RED,DropTail,Fuzzy,PID and SMC,which show that the proposed FSMC effectively adapts to the change of queue length and has good network performance,such as rapid convergence,lower average delay,less packet loss ratio and higher throughput.(4)Aiming at the drawbacks of poor routing and unequal energy load in ZigBee wireless sensor networks,this paper studies an energy-aware shortcut tree routing algorithm—EASTR.First,by introducing the remaining energy information of neighbor nodes into the neighbor table within one hop,EASTR can perceive the remaining energy of ZigBee nodes.Then,among all neighbor nodes whose remaining energy is greater than the dynamic energy threshold Eth,the one with the least number of hops to the destination node is selected as the next hop node.Many NS-2.35 simulation results show that compared with the existing routing algorithms such as Cluster-Tree,AODV,ZBR,STR,and ETR,the proposed EASTR algorithm significantly enhances the performance of star-shaped,tree-shaped,mesh-shaped and other small-and medium-sized ZigBee networks in terms of average delay,packet loss rate,throughput,total remaining energy,etc.,which provides certain theoretical guidance for improving the quality of service and network lifetime of those ZigBee networks.(5)This paper carries out the application research of EASTR algorithm in ZigBee wireless environment sensing system.First,a small-scale ZigBee wireless environment perception system is designed and implemented.Then,the proposed EASTR algorithm is applied to the system to optimize conventional ZigBee routing strategy.Experimental results show that under the premise of ensuring transmission quality and system stability,EASTR algorithm can effectively reduce the energy consumption and packet loss rate of ZigBee networks,which provides good theoretical significance and practical value for the application of ZigBee technology in the field of wireless environment real-time monitoring,and also brings a new opportunity for the broad development of Internet of Things technology.In the end,the whole thesis is concluded and some future research directions are discussed.更多还原