无线传感器网络中一种改进的DV-Hop定位算法

针对DV-Hop算法在无线传感器网络节点分布不均匀时定位误差比较大的问题,提出了一种针对DV-Hop的改进定位算法。该改进算法主要是利用RSSI测量技术增加锚节点;在给定约束下引入“可能存在区域”这一概念,并以该可能存在区域的面积作为目标函数,对未知节点的位置利用非线性共轭梯度法进行逼近,从而使节点定位误差达到最小。通过仿真验证了节点通信半径和锚节点比例对定位误差的影响,结果表明,该改进算法将节点定位精度提高了5%~10%。     

传感器网络同步态的节点故障诊断算法

首先介绍了复杂网络同步态的概念,以传感器量测数据为节点,定义了随时间动态变化的传感器网络,采用数学分析方法定量描述了传感器网络的动力学机制,给出了传感器网络同步态的数学定义、计算方法及其实际的物理含义。理论推导表明,同步态从全局角度评价传感器网络的健康程度,以量测数据距离关联性定义复杂网络的耦合矩阵A=（a_ij）_N×N,并以该耦合矩阵零特征值对应的左特征向量（ξ₁,ξ₂,...,ξ_N）来刻画传感器网络节点的局部细节信息,进而衍生出基于传感器网络同步态的节点故障诊断算法,实现传感器网络的故障诊断。实验仿真了由100个传感器组成的复杂网络,采集了在稳定运动60 s期间的的量测数据,每个量测数据长度为5 000,其中有3个传感器处于间歇增益故障状态,以此来验证基于传感器网络同步态的节点故障诊断算法的有效性。结果表明,该算法不仅可以很好地跟踪整个传感器网络的工作状态,实时监测每个传感器网络节点的故障,而且可以利用传感器网络节点故障之间的相关性有效地识别出传感器量测数据的异常是由外界量测对象的改变还是由传感器本身故障引起的。该算法为全局评估传感器网络的工作状态和监测网络节点的局部故障提供了一个新颖可行的研究思路,期望为相关领域的研究学者提供有益的参考。     

向环境采集能量的WSN中的自适应周期机会路由算法

如何让可以采集能量的节点充分利用环境能量,从而提高整个网络持续高效工作的能力是在能量采集无线传感网中的关键问题。目前的研究主要集中在如何均衡分配可进行能量采集的节点的能量,从而在提高节点寿命的基础上,实现网络寿命延长,但是仍然存在环境能量变化的不确定性导致的风险。笔者提出了自适应周期机会路由算法,首先对节点进行地理分区,再分配优先级,最后进行优化后路由处理。仿真结果表明,该算法能实现对环境能量更加高效的利用,并能有效提升网络的吞吐量和网络效率。     

遗传算法的DV-Hop算法改进

DV-Hop算法中,平均每跳距离是影响定位精度的因素之一。针对平均每跳距离带来的定位误差,对锚节点和未知节点的平均每跳距离进行了改进和优化。首先引入遗传算法计算锚节点的平均每跳距离;然后利用跳数小于等于3的锚节点的平均每跳距离加权处理未知节点的平均每跳距离,减少平均每跳距离带来的误差。仿真结果表明,在不增加硬件开销的基础上,改进算法能够有效提高算法的定位精度,并且具有较好的稳定性。     

蔬菜温室WSN路由算法研究

以无线传感器网络在蔬菜温室环境监控中的应用为目的,研究几种常用自组网路由算法原理。通过对ABR、TORA、DSR、DSDV、AODV等不同路由算法的分类归纳和各自优缺点对比,得出AODV算法因在降低开销的同时还能减小通信延时而最适用于无线传感器网络的结论,因此以实际应用为目的对AODV算法的工作原理进行研究和梳理。使用NS2和NAM网络仿真工具对使用AODV算法的无线传感器网络进行模拟场景仿真,使用gwark和gnuplot工具对仿真数据进行分析,重点研究一定区域面积下节点数量增加时网络传输延时和丢包率的变化,得出应用场景确定时节点数量对通信质量的影响关系,为今后WSN在蔬菜温室中的实际应用提供理论依据。     

移动Ad Hoc网络AODV路由协议的研究与优化

无线移动自组网是仅由移动节点所组成的网络,具有分布式控制、自组织、多跳等特点,由于该网络具有抗毁性能高、易铺设等性质,越来越受到业界的广泛关注。原始的路由协议已经满足不了现有网络不可预测、频繁变化的拓扑结构的需要,因此,在之前研究的基础上,对现有Ad Hoc网络AODV路由协议进行了研究,并设计出一种基于AODV协议的改进路由协议——基于认知的AODV协议(Cognitive-based AODV,CAODV)。通过NS2进行试验仿真,结果表明,CAODV协议具有比AODV协议更加优良的性质,可以有效降低重启路由发现频率,增加断裂链路的修复成功率,降低协议的控制负载,对现有网络的动态变化具有很强的适应能力。     

无线网络接入点TCP流时间公平性

对无线网络接入点上下行TCP流存在的时间不公平性现象进行了研究,报告了无线网络接入有线网络存在的拥塞控制问题现状,提出了一种的无线网络TCP流公平调度算法。采用快速的TCP流优先发送方法,既保证了各流吞吐率公平性,又解决了慢速的TCP占用信道时间过多的问题,实现了各流占用信道的时间公平性。通过网络仿真实验证明,新的公平调度算法比传统的算法在性能上有较大的改进,达到了提高网络整体效率的目的。     

模糊控制系统的垂直切换判决算法分析

针对模糊控制系统中切换时延较长和切换次数较多的问题,研究了一种基于模糊控制系统的垂直切换判决算法。在基于信号强度判决时将RSS作为门限值,提高系统判决能力;同时,将网络参数和服务类型作为判决因素,结合层次分析法引入并行的模糊控制系统,缩短了切换判决的时间、选择适合用户的最佳网络,做出垂直切换。仿真结果表明,该算法减少了切换次数,降低了切换时延,增强了系统的性能。与传统的切换算法相比较,该算法对切换的判决因素考虑的更全面,兼顾了用户终端的使用环境及成本问题,有效地保证了网络的服务质量。     

基于ZigBee技术的物流仓库温湿度监控系统设计

针对电商快速发展导致物流交易量增加,从而给仓库存储带来较高成本的问题,提出了一种基于ZigBee技术的物流仓库温湿度监控系统设计。本文结合快速发展的无线传感器网络技术,对物流仓库的温度和湿度状态进行监测,并通过ZigBee技术将传感器数据传输至汇聚节点和嵌入式网关设备,并由嵌入式网关设备将数据转发至监控中心,同时监控中心可以根据仓库状态自动开启相关控温和控湿设备。经实际运行验证,本系统可以实现数据自动化采集、传输和显示温湿度,所设计的系统可以有效提升物流企业的仓库状态监控效率,达到智能化管理要求。     

基于WSN的果蔬冷链物流实时监测系统研究

为降低果蔬运输过程的损耗,提高果蔬冷链物流信息化程度,提出以ZigBee协议为基础的无线传感网络(WSN)的果蔬冷链物流实时监测系统。该系统采用CC2530F256片上系统构建ZigBee网络,实现对冷链物流运输及仓储的温湿度实时监测。冷链环境下测试结果表明,传感器节点在恒温0℃环境下工作可靠,能准确地监测环境温度及相对湿度等参数的变化,协调器将汇总的温湿度数据通过GPRS模块上传到远程监控软件,并由监控软件实时向数据库存储数据,监测过程中未发生丢包现象。     

An improved HEED clustering algorithm for Wireless Sensor Network

In wireless sensor network, routing protocols which based on clustering have the advantages of energy consumption, topology management and data fusion. The HEED protocol, which generates cluster heads based on distributed algorithm, drives up the rate of clustering and creates well distributed cluster heads. However, it does not consider the mobility of nodes in the network. When the distance between neighbor nodes has changed, the AMRP method which decides the node belongs to different cluster heads would cause problems such as high energy consumption, short lifetime of network and so on. Responding to these problems, the paper proposes the S HEED, a clustering algorithm based on stability, which chooses the stability as a parameter of nodes when choosing a cluster head. With S HEED algorithm, the high energy consumption problem among cluster nodes and cluster heads caused by the mobility is tackled. The simulation experiment demonstrates that the S HEED algorithm lower the energy consumption of cluster heads and prolongs the network lifetime.     

On-demand routing algorithm based on load balancing and mobility prediction in wireless mobile Ad hoc network

The traditional routing protocol for wireless mobile ad hoc networks is unable to achieve balanced energy consumption and could not adapt to the dynamic topology changes well.A novel on-demand rooting algorithm is proposed based on load balancing and mobility prediction.The proposed rooting algorithm excludes the unstable links in routing discovery,and allows the node with more energy forward the routing request packet preferentially.In addition,it adopts the active local routing recovery strategy by predicting the link connection time,and finishes the repair work before the link being actually failure.The simulation experiments demonstrate that,comparing with the traditional AODV protocol,with slight increase of the rooting control overhead,the proposed algorithm increases the average packet delivery ratio,decreases the average end-to-end delay of the data packets,and achieves load balancing in the network and prolong the life-span of the network,which shows the proposed algorithm is highly practical.     

A fuzzy logic multicasting algorithm for ad hoc networks

To increase the multicasting efficiency of Ad hoc networks, a fuzzy logic multicasting algorithm (FLMA) is proposed. FLMA adopts the fuzzy logic to tolerate the imprecise information caused by dynamic network topology. The two input variables of the fuzzy logic system are the relative degree of the additional coverage node number and the relative degree of the residual energy. The deferring time of rebroadcast is the output variable of the fuzzy logic system, which is used to optimize the priority of the nodes to rebroadcast. FLMA reduces the redundant retransmission and the chance of the contention and collision, while balances the energy consumption of the nodes. Simulation results reveal that the FLMA achieves better performance than BCAST in terms of the network lifetime, average end-to-end delay, the average number of drops per node and the throughput.     

Multi-target tracking algorithm based on adaptive sampling interval in wireless sensor networks

Multi-target tracking is a hot topic of current research on wireless sensor networks (WSN). Based on adaptive sampling interval, we propose a multi-target tracking algorithm in order to save energy consumption and prevent tracking lost for WSN. We contrast the targets moving model by using the position metadata, and predicte the targets moving status based on extended Kalman filter (EKF).we adopt the probability density function (PDF) of the estimated targets to establish the tracking cluster. By defining the tracking center, we use Markov distance to quantify the election process of the main node (MN). We comput targets impact strength through the targets importance and the distance to MN node, and then use it to build tracking algorithm. We do the simulation experiment based on MATLAB, and the experiment results show that the proposed algorithm can accurate predict the trajectory of the targets, and adjust the sampling interval while the targets were moving. By analyzing the experiments data, we know that the proposed algorithm can improve the tracking precision and save the energy consumption of WSN obviously.     

A new pattern recognition method of gas sensor array detection

BP neural network based gas sensor array detection pattern recognition has some disadvantages, such as slow convergence and local minimum problem. A modified immune neural network model which combines BP algorithm and immune algorithm is proposed to enhance global search capability and improve the performance of the neural network model. Orthogonal test is adopted to design the study samples of neural network. This ensures the accuracy of neural network while reducing the number of samples. The simulation results show that the proposed pattern recognition method solves the cross sensitivity of gas sensor effectively, overcomes the disadvantages of traditional BP neural network and improves the learning speed and detection accuracy.     

Optimal sensor deployment scheme for heterogeneous wireless sensor networks

For the high density of distributed heterogeneity nodes in wireless sensor networks (WSNs), the optimal sensor deployment is studied. A cost optimal heterogeneous sensor deployment scheme based on genetic algorithm is proposed. The cost of sensor node deployment is used as objective function for optimization computation subjected to network coverage and fault tolerance to obtain the suitable types and positions of the sensors. The algorithm can be used for boolean sensing model as well as probabilistic sensing model. The simulation results demonstrate that the proposed algorithm converges fast toward the optimal solutions and reduces the cost of sensor deployment, which is feasible for heterogenous nodes deployment in WSNs.     

Restoration algorithm with wavelength reservation collision avoidance in ASON

Aiming at the problem of link fault restoration in ASON, an improved equalizing routing algorithm (ERA) is introduced to proportion the load at the routing phase. In order to solve the easy blocking problem for the network without wavelength converter because of the wavelength continuity constraint, the algorithm WRCA is proposed at the wavelength assignment phase. This algorithm is realized by adding collision detection object (CDO) in the path message of the resource reservation protocol with traffic engineering extension (RSVP TE). Depending on the value of the CD flag, different wavelength selection strategies are applied at the destination node, and the blocks resulting from wavelength reservation collision are reduced. The simulation experiments compare four wavelength assignment algorithms with the same routing algorithm ERA. The results show that compared with the traditional first fit algorithm (FF) and random fit algorithm (RD), the FF and RD employing CD scheme can effectively reduce the blocking ratio of the whole network, and enhance the practical applicability of the restoration algorithms.     

基于FM信号的外辐射源雷达组网系统多传感器选择算法

提出一种基于调频广播（FM）信号的外辐射源雷达组网系统多传感器快速启发式算法,目的是使系统能够动态地协调各部FM信号接收机的使用,进而在资源有限的条件下达到更好的目标参数估计性能。该算法采用相干克拉美罗界（CRLB）作为代价函数,并通过贪婪快速启发式算法对优化问题进行了求解。仿真结果表明,所提算法不仅可以在系统资源有限的情况下提升目标的参数估计性能,而且可以大大减小计算量,具有很强的实用性。     

SEEIP核心企业局域智慧能源网络框架及优化配置方法

智慧节能工业园区（SEEIP）的核心企业能源配置对产业集群的循环经济节能降耗具有重要作用。针对SEEIP建设与既有工业园区核心企业能源系统的智慧化改造,提出一种基于信息和通信技术（ICT）的局域智慧能源网络框架,并给出了能源生产模块、能源转换模块与能源蓄存模块中各种能源介质及品位的能量计算数学模型。以经济成本与环境影响为目标的函数,给出了SEEIP企业能源网络系统配置的优化模型,并采用改进的差异演化算法（DE）结合数据库查询技术求解该混合整数非线性规划（MINLP）优化问题,给出企业能源系统最佳配置方案,以满足用户冷、热、电需求。