限制链路数量对无线传感器网络寿命的影响

由于传感器节点能量受限,如何优化无线传感器网络(WSN)寿命是一项重要任务。借助混合二元线性规划(MBLP)框架,对限制传入/传出链路数量的WSN寿命影响进行了研究。利用MBLP最大化WSN寿命,并给出对应约束条件;通过线性网络拓扑结构,分析了节点数量、节点面积对WSN寿命的影响。性能分析表明,如果传入/传出链路数量至少为3时,网络寿命降低小于1.0%,从而进一步证明了分割流量为三部分足以平衡传感器节点间的能耗。     

基于ZigBee的低功耗无线传感器网络改进协议

如何降低无线传感器网络(WSNs)节点的能耗来延长网络寿命是非常重要的,无线网路的性能主要取决于MAC协议,若要降低节点能耗,合理的设计与改进MAC协议就成为一个关键性问题.主要介绍了无线传感器网络中的ZigBee技术发展与应用,针对相关能耗问题,将延迟测量时间同步(DMTS)算法融入到ZigBee网络中,同时引入了基于S-MAC协议机制的周期性侦听/睡眠、碰撞避免等措施对协议进行改进,通过仿真与基本协议进行比较.仿真结果表明:改进的协议能够有效降低网络节点能耗.     

基于梯度的无线传感器网络能耗分析及能量空洞避免机制

在基于"梯度汇聚"模型的无线传感器网络 (Wireless sensor networks, WSNs)中, 因节点间能量消耗不平衡而引发的能量空洞一直是影响网络生存周期的重要原因. 本文分别分析了无通信干扰的自由空间环境和瑞利衰落环境下网络中节点的能量消耗,提出了一种基于节点能量非均匀分布的能量空洞避免机制,即根据节点的能耗水平为每个节点储备不同的初始能量.并结合通信干扰、休眠机制等因素,研究了基于"梯度汇聚"模型的无线传感器网络生存周期的上界和下界. 模拟结果表明,该机制提高了能量的利用效率,延长了网络的生存周期.     

无线传感器网络分簇路由节能研究

在大规模传感和环境监测中,节约能源延长传感器节点生命已成为无线传感器网络最重要的研究课题之一。提供合理的能源消耗和改善无线网络生命周期的传感器网络系统,必须设计一种新的有效的节能方案和节能路由体系。方案采用一种聚类算法减少无线传感器网络的能量消耗,创建一种cluster-tree分簇路由结构的传感器网络。该方案主要目标是做一个理想的分簇分配,减少传感器节点之间的数据传输距离,降低传感器节点能源消耗,延长寿命。实验结果表明,该方案有效地降低了能源消耗从而延长无线传感器网络生命。     

基于网络编码的WSNs数据收集方法

无线传感器网络(WSNs)监测数据的收集方式方法是目前的研究热点,而无线传输的广播特性又使得网络编码非常适合于无线网络。在介绍网络编码原理、核心思想以及在WSNs应用现状的基础上,提出了一种基于部分网络编码的自适应WSNs数据收集方法,该方法针对簇网络拓扑结构,簇成员节点把网络编码数据发送给簇头节点,簇头节点利用随机网络编码的方式把数据传输到Sink节点。实验结果表明:该机制具有能耗较低和汇报数据较准确的特点。     

改进的基于网络寿命的RPL路由协议

为提高无线传感器网络(WSN)的寿命,提出一个能量平衡路由协议的设计方案,该协议不再侧重于最小化所有节点的平均能量消耗,重点识别能量瓶颈节点,最大限度降低其能量消耗以达到网络寿命的最大化。定义一个估计的预期寿命(ELT),用该值度量这些瓶颈节点寿命,通过剩余能量和链路可靠性等约束条件,估计瓶颈节点的平均能耗,选择最优的路径,均衡能量消耗。实验结果表明,与预期发送次数(ETX)和剩余能量两种协议相比,该协议能够有效延长网络的寿命。     

移动Sink的传感器网络路径优化策略

在无线传感器网络（WSNs）中引入移动 Sink 可以避免网络拥塞和能量空洞并降低网络能耗,但由于移动速度的限制导致时延较大。针对这一问题,提出了时延约束下的移动 Sink 路径优化策略,根据时延和网络能耗之间的关系设计了可调节的节点权重,通过模拟退火遗传算法得到最优节点权重,并依据此权重通过迭代得到汇聚节点和最佳移动路径。仿真结果表明：该策略能保证在满足时延约束的前提下降低网络能耗,且收敛速度快。     

基于能耗优化的AODV路由协议

在无线传感器网络中,为了优化和平衡各节点的能量消耗从而达到延长了网络寿命的目的,提出了一种基于能耗优化的AODV(E-AODV)路由协议。E-AODV优先选择剩余能量较高的节点参与路由同时选择能耗相对较小的路径作为路由,引进了被动更新路由和动态调整发射功率两种机制。NS-2仿真结果表明:与传统AODV相比,E-AODV降低了网络的整体能耗,有效均衡使用各节点的能量,延长了网络寿命。     

单节点的无线传感器网络数据传输优化策略

为了提高无线传感器网络（WSNs）节点能量的利用率,延长WSNs的生存时间,提出了一种单节点的WSNs数据传输优化策略.首先对WSNs结构进行分析,并建立单个传感器节点数据传输优化的数学模型;然后采用惩罚函数法对数据传输过程中的传感器节点能耗进行优化;最后在Matlab 2012平台对其进行仿真分析.结果表明：该方法可以根据环境能量的变化对传感器节点能耗进行自适应优化,提高了节点的累积数据传输总量,可以较好适应环境能量不确定性.     

用于智能电网的有差别射频充电传感器网络

针对应用于智能电网中的无线传感器网络(WSNs)节点能量受限问题,分析了基于无线射频充电技术的为传感器节点充电技术,改进了可持续无线充电传感器网络(SWRSNs),提出有差别射频充电传感器网络(DRRSNs)技术,增加节点的优先级设置,建立整数线性规划模型,用CPLEX求解模型确定标志性节点位置。求解数据表明:节点获得的能量平均提高105%,高优先级节点比低优先级节点平均多获得43%的能量,提高了节点的寿命,保证了WSNs的可靠性,但是路径访问效率平均降低了14%。     

一种鲁棒性强的无线传感器网络位置隐私保护方案

传统无线传感器网络（WSNs）位置隐私保护方案难以解决安全性与网络能耗之间的均衡,为了提高网络隐私信息的安全性,提出一种鲁棒性强的无线传感器网络位置隐私保护方案.首先通过增加伪源节点和伪汇聚节点防止攻击者获得关键节点的位置信息;然后采用伪汇聚节点分组、概率丢弃冗余数据包降低网络资源消耗;最后在Matlab 2012平台下进行仿真对比实验.结果表明：该方案可以提高网络攻击事件检测率,降低网络时延,有效地保护源节点和汇聚节点的位置隐私.     

A chain-cluster based routing algorithm for wireless sensor networks

Wireless sensor networks (WSNs) are an emerging technology for monitoring physical world. Different from the traditional wireless networks and ad hoc networks, the energy constraint of WSNs makes energy saving become the most important goal of various routing algorithms. For this purpose, a cluster based routing algorithm LEACH (low energy adaptive clustering hierarchy) has been proposed to organize a sensor network into a set of clusters so that the energy consumption can be evenly distributed among all the sensor nodes. Periodical cluster head voting in LEACH, however, consumes non-negligible energy and other resources. While another chain-based algorithm PEGASIS (power- efficient gathering in sensor information systems) can reduce such energy consumption, it causes a longer delay for data transmission. In this paper, we propose a routing algorithm called CCM (Chain-Cluster based Mixed routing), which makes full use of the advantages of LEACH and PEGASIS, and provide improved performance. It divides a WSN into a few chains and runs in two stages. In the first stage, sensor nodes in each chain transmit data to their own chain head node in parallel, using an improved chain routing protocol. In the second stage, all chain head nodes group as a cluster in a self- organized manner, where they transmit fused data to a voted cluster head using the cluster based routing. Experimental results demonstrate that our CCM algorithm outperforms both LEACH and PEGASIS in terms of the product of consumed energy and delay, weighting the overall performance of both energy consumption and transmission delay.     

Dynamic cluster head for lifetime efficiency in WSN

Saving energy and increasing network lifetime are significant challenges in wireless sensor networks （WSNs）. In this paper, we propose a mechanism to distribute the responsibility of cluster-heads among the wireless sensor nodes in the same cluster based on the ZigBee standard, which is the latest WSN standard. ZigBee supports ad hoc on-demand vector （AODV） and cluster-tree routing protocols in its routing layer. However, none of these protocols considers the energy level of the nodes in the network establishing process or in the data routing process. The cluster-tree routing protocol supports single or multi-cluster networks. However, each single cluster in the multi-cluster network has only one node acting as a cluster head. These cluster-heads are fixed in each cluster during the network lifetime. Consequently, using these cluster-heads will cause them to die quickly, and the entire linked nodes to these cluster-heads will be disconnected from the main network. Therefore, the proposed technique to distribute the role of the cluster head among the wireless sensor nodes in the same cluster is vital to increase the lifetime of the network. Our proposed technique is better in terms of performance than the original structure of these protocols. It has increased the lifetime of the wireless sensor nodes, and increased the lifetime of the WSN by around 50% of the original network lifetime.     

Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

Wireless Sensor Network (WSN) consists of a group of limited energy source sensors that are installed in a particular region to collect data from the environment. Designing the energy-efficient data collection methods in large-scale wireless sensor networks is considered to be a difficult area in the research. Sensor node clustering is a popular approach for WSN. Moreover, the sensor nodes are grouped to form clusters in a cluster-based WSN environment. The battery performance of the sensor nodes is likewise constrained. As a result, the energy efficiency of WSNs is critical. In specific, the energy usage is influenced by the loads on the sensor node as well as it ranges from the Base Station (BS). Therefore, energy efficiency and load balancing are very essential in WSN. In the proposed method, a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques (GW-IPSO-TS) was used. The selection of Cluster Heads (CHs) and routing path of every CH from the base station is enhanced by the proposed method. It provides the best routing path and increases the lifetime and energy efficiency of the network. End-to-end delay and packet loss rate have also been improved. The proposed GW-IPSO-TS method enhances the evaluation of alive nodes, dead nodes, network survival index, convergence rate, and standard deviation of sensor nodes. Compared to the existing algorithms, the proposed method outperforms better and improves the lifetime of the network.     

Using a dynamic backbone for efficient data delivery in solar-powered WSNs

The periodic nature of solar power requires a different approach to energy consumption in wireless sensor networks (WSNs) from battery-based WSNs. Based on the energy model of a solar-powered node, we develop efficient energy-aware topology-control and routing schemes which utilize a backbone network consisting of energy-rich nodes within the WSN. This backbone handles most of the traffic with low latency, while reconfiguring itself dynamically in response to changes in the availability of energy at each node. Simulation results demonstrate that our schemes can achieve a balance between latency and energy consumption.     

一种能量有效的三维传感器网络覆盖控制算法

由于无线传感器网络节点部署是随机的而且数量巨大,会产生很多冗余的节点,因而对网络进行覆盖控制提高冗余节点的利用率就成为一个亟待解决的问题.针对无线传感器网络中的三维覆盖问题进行了深入的研究,提出了一种分布式能量有效的三维覆盖控制算法,并利用OPNET网络仿真软件对其性能进行了验证.     

多宿点无线传感器网络时分多址时隙优化分配算法

针对单宿点无线传感器网络的时延大、容易出现传输瓶颈等问题,提出了多宿点无线传感器网络模型以及该模型的基于遗传算法(GA)的时分多址(TDMA)时隙分配算法。该算法根据宿点的数量以及位置将整个传感器网络划分成多个小传感器网络,并采用遗传算法对时隙分配结果进行优化。仿真结果表明,基于遗传算法的多宿点无线传感器网络TDMA时隙分配算法得到的时隙分配结果在时隙分配帧长度、数据包平均时延以及节点平均能耗方面均要优于图着色算法。     

Mobility-assisted minimum connected cover in a wireless sensor network

All properties of mobile wireless sensor networks (MWSNs) are inherited from static wireless sensor networks (WSNs) and meanwhile have their own uniqueness and node mobility. Sensor nodes in these networks monitor different regions of an area of interest and collectively present a global overview of monitored activities. Since failure of a sensor node leads to loss of connectivity, it may cause a partitioning of the network. Adding mobility to WSNs can significantly increase the capability of the WSN by making it resilient to failures, reactive to events, and able to support disparate missions with a common set of sensor nodes. In this paper, we propose a new algorithm based on the divide-and-conquer approach, in which the whole region is divided into sub-regions and in each sub-region the minimum connected sensor cover set is selected through energy-aware selection method. Also, we propose a new technique for mobility assisted minimum connected sensor cover considering the network energy. We provide performance metrics to analyze the performance of our approach and the simulation results clearly indicate the benefits of our new approach in terms of energy consumption, communication complexity, and number of active nodes over existing algorithms.     

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。     

一种抗干扰半静态分簇路由算法

针对无线传感器网络( WSNs)分簇路由算法中的能量洞、热点和抗干扰问题,设计一种抗干扰半静态分簇( AlSSC)路由算法,给无线传感器网络提供能量多、距离短、链路质量好的路径来传输数据.该算法利用节点定位获取节点地理位置,综合考虑传感器节点剩余能量和干扰信噪比,通过节点距离度量、节点聚簇、簇间融合、簇头选举和簇头轮换五个步骤进行无线传感器网络节点的分簇.仿真结果表明:这种路由算法可以提高无线传感器网络通信链路质量,均衡网络能量消耗.