基于能耗量化传导的WSN路由探测算法

为了降低无线传感器网络(WSN)路由节点的能量损耗,提高网络的寿命周期,需要进行路由节点的优化分布设计。传统方法采用CSMA/CA有限竞争的信道分配模型进行WSN的路由探测算法设计,实现能量均衡,在节点规模较大和干扰较强时,节能的能耗开销较大。提出一种基于能耗量化传导的WSN路由探测算法,首先建立WSN的分簇能耗调度模型,以能量控制开销、丢包率、传输时延等为约束参量指标进行路由探测的控制目标函数的构建,然后采用路由冲突协调机制进行能耗量化分配,结合WSN传输信道的能量传导均衡模型实现WSN路由的优化探测和WSN节点的优化部署。仿真结果表明,采用该方法进行WSN路由探测设计时网络的能效较高,传输时延和误码率等参量指标的表现优于传统方法。     

一种能耗均衡的WSN分布式拓扑博弈算法

无线传感器网络（wireless sensor network,WSN）中通常节点能量受限,节点间能耗不均衡会导致网络生命周期缩短.针对该问题,综合考虑节点的能量效率和能耗均衡,通过引入阿特金森指数设计了一种改进优化的综合效用函数;基于此,建立了一种能耗均衡的拓扑博弈模型,并证明了该拓扑博弈模型是序数势博弈且存在帕累托最优;提出了一种能耗均衡的WSN分布式拓扑博弈算法（DTCG）.通过仿真实验及对比分析表明,相较于其它基于博弈理论的拓扑控制算法,DTCG算法能在保证网络连通性和鲁棒性的前提下,降低节点发射功率,拥有更好的能量均衡性和能量效率,可以有效延长网络生命周期.     

一种缓解能量空洞的数据聚合算法

针对影响无线传感器网络(WSN)生命周期的能量空洞(EH)问题,以实际测量的数据为依据,综合考虑在数据传输过程中最大传输单元的影响因素,提出一种解决能量空洞的数学模型。该模型通过数据聚合的方式使每个节点发送数据时以最大的分片数进行传送,采用节能的方式对WSN能耗进行优化,以减小EH的区域,使全网能耗最低。仿真实验结果表明,与EHMS方案相比,该模型能够最大程度地优化WSN的能量,缓解能量空洞的形成,延长无线传感器网络的生命周期。     

无线传感网中改进的节能分级数据汇聚机制

考虑WSN中节点的能耗分布情况,提出了一种改进的多级汇聚协议。首先建立分析模型评估了在WSN中采用多级汇聚机制时的能耗情况,证明在SINK附近的汇聚节点的能量增加很快,从而会耗尽能量,缩短整个网络的生存期。然后提出了一个改进的多级汇聚协议,通过改变通过减少离SINK附近的汇聚节点选择概率,可以均衡网络性能。仿真结果证明,该方法可以有效地降低能量,从而延长网络生存期。     

一种新型能耗优化的无线传感器网络成簇算法

能量消耗一直是限制WSN广泛应用的热门问题之一,能源容量的大小对各个传感器节点产生重要的影响.针对WSN中能耗过快,以及网络区域内能量消耗不均衡而导致的网络生命周期缩短的问题,同时为了提高WSN的能量利用率,提出了一种新型能耗优化的无线传感器网络非均匀成簇算法(UCNE).该算法首先根据节点的历史能耗来竞选簇头节点,将整个网络划分为不均匀的簇群从而平衡簇内节点通信与簇间节点通信的能耗.其次设立新的能量阈值作为网络重新分簇的标准,减少了频繁分簇造成的不必要的控制消息能耗.最后为了降低簇头节点的负担,竞选副簇头节点作为中继转发节点转发主簇头加工的数据并根据权值选择向前向簇头节点传递数据.通过对比相关协议,UCNE协议在平衡网络能耗,延长网络寿命方面表现更优.     

无线传感器网络覆盖控制算法研究

无线传感器网络(Wireless sensor network, WSN)覆盖控制通常采用基于二元感知模型的几何计算方法休眠冗余节点, 其算法在实际应用中受到局限, 不够精确. 针对此问题, 本文采用概率感知模型, 提出新的覆盖控制算法, 将提高能量利用效率作为重要指标, 采用节点轮换周期工作机制, 每个周期逐个唤醒部分节点, 组成满足网络覆盖要求的覆盖集, 实现降低能耗、均衡节点能量的目的. 概率感知模型描述网络的覆盖能力更精确, 算法不受感知模型的限制, 原理简单, 易实现, 仿真结果验证了本算法的有效性.     

一种基于LEACH的改进无线传感器网络路由协议

为了在无线传感器网络(WSN)中降低能耗和提高网络生存期,针对LEACH协议中簇头选举不合理和随机分簇的不足,提出了一种LEACH的改进协议.该协议首先计算无线传感器网络的最佳分簇数量,然后与遗传算法相结合对网络进行分簇,再根据簇中节点的剩余能量等情况选出簇头节点.仿真结果表明,与经典的LEACH协议相比,改进后的协议减少了网络的能量消耗,延长了网络生命周期.     

WSN中基于最大最小化的优化路由算法

无线传感器网络(WSN)由能量受限的节点组成,需要设计路由算法优化节点的能耗。文章以最大化网络生存时间为目标,基于最大最小化模型提出了优化路由算法,定义了数据发送矩阵,设计了转发节点选择机制,以避免路由回路;基于节点收发数据的能耗及剩余能量,设计了求解优化路由的数学规划模型,优化了传感器节点的数据发送路径和发送量,均衡了节点的能量消耗。仿真结果表明,该算法能有效地均衡节点的能耗,延长网络生存时间。     

基于环的节点非均匀分布分簇算法

针对无线传感器网络（WSN）中基于环的节点非均匀分布网络模型下的能量空洞问题,提出了一种基于环的节点非均匀分布分簇算法（RCANND）。该算法在节点非均匀分布的网络模型下,通过每环的能耗最小化,计算每一环的最优簇首数;通过节点剩余能量、距基站距离以及与邻居节点的平均距离计算簇首选择度。在簇内以簇首选择度序列表进行簇首轮转,降低分簇次数,提高网络能量的利用效率。对提出的算法进行仿真对比实验,仿真结果表明,相同半径、不同分布模型下节点的平均能耗波动很小;相同分布模型、不同半径下节点的平均能耗波动也不明显。以网络中50%节点存活作为网络生命周期,在节点非均匀分布情况下,所提算法的网络生命周期比混合能量高效分布式不等分簇算法（UHEED）和轮转的混合能量高效分布式不等分簇算法（RUHEED）分别提高约18.1%和11.5%;在节点均匀分布模型下,所提算法的网络生命周期比基于分环的能量高效无线传感器网络分簇路由（RECR）协议提高约6.4%。所提算法有效均衡了不同分布模型下的能耗,有效延长了网络生命周期。     

基于能量最小路径的WSN分簇算法

为延长无线传感器网络(WSN)的生存时间,提出一种基于能量最小路径的WSN分簇算法。参照节点的剩余能量与全网动态平均能量的比例关系,决定节点是否成为簇头,并结合簇头间的能量最小路径,实现全网的能耗均衡。仿真结果显示,该算法在网络生存时间、数据吞吐量和网络能耗等指标上性能较优。     

Layout Optimization for Greenhouse WSN Based on Path Loss Analysis

When wireless sensor networks (WSN) are deployed in the vegetable greenhouse with dynamic connectivity and interference environment, it is necessary to increase the node transmit power to ensure the communication quality, which leads to serious network interference. To offset the negative impact, the transmit power of other nodes must also be increased. The result is that the network becomes worse and worse, and node energy is wasted a lot. Taking into account the irregular connection range in the cucumber greenhouse WSN, we measured the transmission characteristics of wireless signals under the 2.4 Ghz operating frequency. For improving network layout in the greenhouse, a semi-empirical prediction model of signal loss is then studied based on the measured data. Compared with other models, the average relative error of this semi-empirical signal loss model is only 2.3%. Finally, by combining the improved network topology algorithm and tabu search, this paper studies a greenhouse WSN layout that can reduce path loss, save energy, and ensure communication quality. Given the limitation of node-degree constraint in traditional network layout algorithms, the improved algorithm applies the forwarding constraint to balance network energy consumption and constructs asymmetric network communication links. Experimental results show that this research can realize the energy consumption optimization of WSN layout in the greenhouse.     

Energy-efficient multipath routing in wireless sensor network considering wireless interference

Due to the energy and resource constraints of a wireless sensor node in a wireless sensor network (WSN), design of energy-efficient multipath routing protocols is a crucial concern for WSN applications. To provide high-quality monitoring information, many WSN applications require high-rate data transmission. Multipath routing protocols are often used to increase the network transmission rate and throughput. Although large-scale WSN can be supported by high bandwidth backbone network, the WSN remains the bottleneck due to resource constraints of wireless sensors and the effects of wireless interference. In this paper, we propose a multipath energy-efficient routing protocol for WSN that considers wireless interference. In the proposed routing protocol, nodes in the interference zone of the discovered path are marked and not allowed to take part in the subsequent routing process. In this way, the quality of wireless communication is improved because the effects of wireless interference can be reduced as much as possible. The network load is distributed on multiple paths instead of concentrating on only one path, and node energy cost is more balanced for the entire wireless network. The routing protocol is simulated in NS2 software. Simulation result shows that the proposed routing protocol achieves lower energy cost and longer network lifetime than that in the literature.     

基于线性回归的无线传感器网络分布式数据采集优化策略

事件监测是无线传感器网络中最重要的应用之一,部署在监测区域内的传感器节点通过对感知数据信息的采集、处理和传输等基本操作完成具体的监测任务,在各种操作中,节点之间的数据传输是最消耗能量的.为了减少节点之间的通信数据量,达到降低网络能耗和延长网络生命周期的目的,该文提出了一种能量高效的基于线性回归的无线传感器网络分布式数据采集优化策略,通过应用线性回归分析方法构建感知数据模型,保持感知数据的特征,使节点仅传输回归模型的参数信息,代替传输实际监测的感知数据信息.仿真实验结果表明,文中提出的数据采集优化策略能通过较小的通信量有效地实现事件监测区域感知数据的预测和估计,降低网络的总能量消耗,延长网络的生命周期.     

A Methodology for Reliability of WSN Based on Software Defined Network in Adaptive Industrial Environment

As communication technology and smart manufacturing have developed, the industrial internet of things (IIoT) has gained considerable attention from academia and industry. Wireless sensor networks (WSNs) have many advantages with broad applications in many areas including environmental monitoring, which makes it a very important part of IIoT. However, energy depletion and hardware malfunctions can lead to node failures in WSNs. The industrial environment can also impact the wireless channel transmission, leading to network reliability problems, even with tightly coupled control and data planes in traditional networks, which obviously also enhances network management cost and complexity. In this paper, we introduce a new software defined network (SDN), and modify this network to propose a framework called the improved software defined wireless sensor network (improved SD-WSN). This proposed framework can address the following issues. 1) For a large scale heterogeneous network, it solves the problem of network management and smooth merging of a WSN into IIoT. 2) The network coverage problem is solved which improves the network reliability. 3) The framework addresses node failure due to various problems, particularly related to energy consumption. Therefore, it is necessary to improve the reliability of wireless sensor networks, by developing certain schemes to reduce energy consumption and the delay time of network nodes under IIoT conditions. Experiments have shown that the improved approach significantly reduces the energy consumption of nodes and the delay time, thus improving the reliability of WSN.      

基于贪婪算法无线传感器网络中继节点布局的研究

为实现远距离的无线通信, 在网络中添加中继节点, 采用多跳路由传输数据。对于中继节点的布局问题, 依据线性结构使网络整体能量消耗最小的特征, 提出一种中继节点贪婪布局算法。该算法通过最近贪婪策略、中继节点通信容量、传感器节点数据转发跳数等约束方法限制中继节点的布局位置。理论分析和实验验证了该算法能够有效减少能量消耗, 延长网络寿命。     

一种分布式无线传感器网络跨层移动通信技术研究

针对无线多媒体传感器网络对带宽和实时性等的高要求,建立了一种基于能量优化和跨层协同交互的分布式多路径路由技术,并应用于移动通信领域。该技术采用了遗传算法优化节点传输多媒体数据能耗,建立节点剩余能量预测模型,根据感知能量建立跨层协同工作体系,以较小代价在动态无线网络拓扑中选择最优路径。仿真实验和数学分析表明,该技术能够高效地支持实时移动视频通信,适合于计算能力、存储能力和能量等受限的无线多媒体传感器网络。     

一种基于改进粒子群的无线传感器网络层次化聚类协议

延长网络的生存周期是无线传感器网络路由设计的主要目标之一。簇头的高能耗是网络快速死亡的一个重要原因。提出一种基于改进粒子群PSO( Particle Swarm Optimation)的无线传感器网络聚类路由协议IPSOCH。利用中继节点来分担簇头数据转发的任务,减轻簇头节点的负载,并利用改进的粒子群算法通过节点的剩余能量信息和位置信息来选择簇头和中继节点。仿真实验表明,IPSOCH协议比起现有的几种路由协议,能有效提高能量使用率,延长网络生存周期。     

Editorial

Wireless sensor network(WSN)is characterized by the dense deployment of sensor nodes that continuously observe physical phenomenon.The main advantages of WSN include its low cost,rapid deployment,self-organization,and fault tolerance.WSN has received tremendous interests of various research communities,and significant progresses have been made in various aspects including sensor platform development,wireless communication and networking,signal and information processing,as well as network performance eva...     

基于小世界模型的WSN簇间拓扑优化方法

针对无线传感器网络节点因能量消耗、硬件故障、通信因素等导致的链路失效问题,提出一种基于复杂网络小世界模型Kleinberg的无线传感器网络簇间拓扑优化方法,该方法依据簇头节点的局部视图ViewList信息中的长链与短链构建WSN簇间拓扑.实验分析表明,利用该方法演化的无线传感器网络拓扑在节点失效概率为0.2时,网络寿命比DECDC提高25%,并具有良好的能量均衡性和较低的消耗代价.该方法构建的拓扑具有较好的容错性和较强的鲁棒性.     

移动式脉冲耦合振荡器实现动态WSN时间同步

针对无线传感器网络WSN（Wireless Sensor Network）中移动式传感器的广泛应用,考虑到传统时间同步模型受运动方向、速度和通信距离等因素的限制,提出将移动式脉冲耦合振荡器（MPCOs）模型应用到二维动态的相互交互平面WSN当中,研究一种动态WSN的时间同步方法。为提高时间同步方法的收敛速度,分析传感器节点数、耦合强度、速度、通信半径对所提时间同步方法收敛速度的影响,得出收敛速度与传感器节点数、耦合强度、速度、通信半径成正比的结论。通过得到最优参数实现网络最优化使同步收敛时间最快,达到降低能耗和信息损耗。通过数值仿真验证了所提方法的有效性。