基于休眠和扇区的传感器网络拓扑控制算法

拓扑控制算法对节省无线传感器网络节点能量、延长网络寿命具有重要意义。无线传感器网络节省节点能量有两种方法：层次型拓扑结构控制和功率控制；但目前还没有算法将以上两种方法相结合。丈中是结合周期性休眠和拓扑控制的一种新型拓扑控制策略：基于休眠和扇区的无线传感器网络拓扑控制算法，将拓扑控制算法和节点的休眠结合起来。仿真结果表明：算法在不降低网络吞吐量条件下节省了网络能量消耗，有效延长网络寿命。     

WSN中一种混合型拓扑控制算法

拓扑控制对于延长网络寿命,减小通信干扰,提高路由协议效率等具有重要的意义。睡眠调度和功率控制是现在研究的主流方向。全文首先阐述了无线传感器拓扑控制算法的研究进展,接着提出了一个混合型拓扑控制算法HTC,叙述了HTC算法的实现过程,它融合了睡眠调度和功率控制算法的优点,克服了它们的缺点,在提高网络性能和延长网络寿命方面起到很好的作用。     

无线传感器网络中联合功率 控制和速率调整

 无线传感器网络本质上是能量受限的,而且,传感器节点扮演着数据收集和数据转发的双重角色.本文提出了怎样分配传感器节点的功率用于转发其它节点的数据.在节点的转发功率分配比确定后,研究了采用价格作为一种方法,刺激节点与它到数据采集节点路径上的所有节点合作.通过把无线传感器网络中数据收集和传输抽象为一个网络效用最大化问题,通过采用对偶分解技术,提出了一种迭代价格与联合功率控制和速率调整的分布式算法.实验表明,该算法能提高系统的性能,同时降低功率的消耗.     

一种基于最短路径树的无线Ad hoc网络拓扑维护算法

该文主要研究了无线Ad hoc网络中节点失效的情况下,如何维护网络的连通性和拓扑的性能,并且尽可能地降低拓扑维护的开销。提出了基于最短路径树的拓扑维护算法。该算法在拓扑变化时首先触发失效节点的邻节点响应(即重新运行拓扑控制算法),在不增加额外通信开销的情况下,响应的节点根据相互发送的Hello分组来判断网络是否连通;如果不能确定网络是连通的,再触发失效节点的其它可达邻近节点响应。仿真研究表明,算法显著地减少了拓扑维护的开销,维护后的拓扑结构在功率有效性和功率扩展因子等方面也取得了好的性能。     

功率控制技术在可靠连通无线传感器网络中的应用研究

 功率控制技术是容错拓扑控制中的重要手段,可以简化网络结构,获得可靠连通和高效的底层拓扑.本文提出集中式功率控制算法CTPC,证明其正确性和最小化最大通信半径的最优性质.拓展CTPC算法到分布式环境,设计基于全局信息的功率控制算法GDTPC和基于局部信息的功率控制算法LDTPC,给出算法正确性证明和关于最优性质保持的讨论.LDTPC算法只使用局部信息,适用于大规模无线传感器网络.     

无线传感器网络拓扑控制分析

无线传感器网络的拓扑控制对网络的性能有很大影响。拓扑控制的目标是用最小的能量维持网络拓扑。目前,对拓扑控制算法的研究主要分为集中式和分布式两种。文章简要介绍了无线传感器网络中拓扑控制研究的意义,总结了无线传感器网络的拓扑结构及现有的一些拓扑控制算法,最后探讨了存在的问题和今后的发展方向。     

基于簇结构超宽带无线传感器网络的传输功率优化选择算法

在簇结构超宽带无线传感器网络中,为了在可接受的实现成本范围内解决节能与功率控制问题,提出了一种传输功率优化选择算法,同时满足了预设的数据传输速度和最大限度的节能要求.然后详细地分析了该算法实现的可行性、复杂度和实现成本.仿真结果表明,本算法得出的最优传输功率大大小于传感器节点可获取的最大功率,并可以根据网络背景噪声和最大传输速度的变化而动态调整;该算法可以较为显著地延长传感器节点寿命;另外,仿真结果还表明本算法的实现成本是合理的且可接受的.     

无线传感器网络的能效分析

能量效率是衡量无线传感器网络性能最重要的指标,介绍了无线传感器网络节点结构,分析了无线传感器节点的主要能耗源.讨论动态能量管理和动态电压调整等提高传感节点能效的技术,从物理层、链路层、网络层、传输层等层次论述了无线传感器网络拓扑所采用的能效机制,最后对功率控制技术进行了分析.     

WSN中基于能量感知的最小跳数路由算法

无线传感器网络的拓扑往往由于节点死亡而发生变化。网络拓扑的重新构建加速了剩余传感器节点的死亡,缩短了网络的生存时间。针对无线传感器网络对网络生存时间的苛刻要求,提出了一种基于能量感知的最小跳数路由算法。建立路由时,该算法综合考虑了节点剩余能量和该节点潜在的转发能力。仿真结果显示,该算法在生存时间、存活节点数和吞吐量方面的性能要远优于LEACH算法和HEED算法。     

基于无线传感器网络的业务流调度算法

实时性要求是无线传感器网络调度算法性能评价的重要内容。对于实时性要求很高的应用场合,调度算法的首要标准是降低数据包的传输时延。针对无线传感器网络的业务流调度问题,结合传统的加权循环调度算法WRR,着眼于解决无线传感器网络中业务流突发引起的时延性能下降问题,提出了新的调度算法-WSWRR。新算法合理分配传感器节点的数据感知和传输时间,使节点在不需要工作时转入低功耗的休眠模式,且能在满足应用要求服务质量的前提下,高效利用节点能量,延长整个传感器网络的生命周期。通过仿真实验,验证了新算法在调度突发数据包时性能得到了很好的改善,且没有增加网络的整体能耗,证明了WSWRR算法的有效性。     

An energy‐efficient localized topology control algorithm for wireless ad hoc and sensor networks

Topology control plays an important role in the design of wireless ad hoc and sensor networks and has demonstrated its high capability in constructing networks with desirable characteristics such as sparser connectivity, lower transmission power, and smaller node degree. However, the enforcement of a topology control algorithm in a network may degrade the energy‐draining balancing capability of the network and thus reduce the network operational lifetime. For this reason, it is important to take into account energy efficiency in the design of a topology control algorithm in order to achieve prolonged network lifetime. In this paper, we propose a localized energy‐efficient topology control algorithm for wireless ad hoc and sensor networks with power control capability in network nodes. To achieve prolonged network lifetime, we introduce a concept called energy criticality avoidance and propose an energy criticality avoidance strategy in topology control and energy‐efficient routing. Through theoretical analysis and simulation results, we prove that the proposed topology control algorithm can maintain the global network connectivity with low complexity and can significantly prolong the lifetime of a multi‐hop wireless network as compared with existing topology control algorithms with little additional protocol overhead. Copyright © 2008 John Wiley & Sons, Ltd.     

一种无线传感器网络全连通群的休眠调度算法

该文针对无线传感器网络的覆盖性和连通性问题,在假设传感器节点地理位置信息已知的条件下,设计了一种包含全连通群的建立和维护以及群内节点休眠调度的全新算法。该算法采用保证群内节点彼此一跳可达的全连通群分群方法,以及分布式节能的休眠调度策略,最大程度上减少传感器网络的能量消耗,延长了网络寿命。仿真结果表明:该算法能较好地保证无线传感器网络的覆盖性和连通性,且能耗较低。     

无线Ad hoc网络中基于节点位置的功率控制算法

为了降低无线Ad hoc网络中节点的能量消耗,该文提出了一种基于节点位置的功率控制算法(PCAP)。PCAP算法通过分析节点间的位置关系,建立节点的优化邻居集合,并对路由层报文、MAC层控制报文和其它数据类报文使用不同的功率控制策略。PCAP算法在保证网络连接性的同时能降低网络能量消耗,计算机仿真表明,PCAP算法在MAC层的吞吐量、MAC层丢包、端到端时延等方面取得较好的性能表现。     

物联网感知层多路径传输策略研究

多路径数据传输是无线传感器网络亟需解决的一个关键问题.本文针对节点故障、链路失效和外界干扰影响网络稳定性和可靠性,提出一种基于混合蛙跳算法的无线传感器网络多路径传输策略.首先我们详细介绍了蛙跳算法及其原理,之后我们将其应用到无线传感器网络多路径传输策略之中,接着运用混合蛙跳算法对传感网络节点其进行更新、划分、重组以便选择出最优节点建立传输最优路径,提高网络的稳定性和可靠性.通过算法仿真与结果对比提出的算法与AODV、粒子群PSO算法相比,在网络能耗、传输时延、丢包率、连通率和可靠度等方面都具有较好的性能.其中网络能耗比AODV、PSO算法降低了62.5％和35.8％.     

无线传感器网络基于容量和传输能耗的功率与信道联合博弈算法

针对无线传感器网络(WSNs)日益增大的干扰导致网络容量下降的问题,同时考虑到网络能量有限性,该文综合网络容量和链路传输能耗,构建了高容量低传输能耗的功率控制与信道分配联合博弈模型,并通过理论分析证明该模型存在最优功率和最优信道。继而采用最佳响应策略,在该博弈模型基础上提出了一种功率控制与信道分配联合优化算法(PCOA),理论证明其能收敛到纳什均衡状态,且具有较小的信息复杂度。最后,仿真结果表明,PCOA算法能够达到降低网络干扰和链路能耗,增大网络容量的目的。     

Efficient location‐based topology control algorithms for wireless ad hoc and sensor networks

Topology control is an efficient strategy for improving the performance of wireless ad hoc and sensor networks by building network topologies with desirable features. In this process, location information of nodes can be used to improve the performance of a topology control algorithm and also ease its operations. Many location‐based topology control algorithms have been proposed. In this paper, we propose two location‐assisted grid‐based topology control (GBP) algorithms. The design objective of our algorithm is to effectively reduce the number of active nodes required to keep global network connectivity. In grid‐based topology control, a network is divided into equally spaced squares (called grids). We accordingly design cross‐sectional topology control algorithm and diagonal topology control algorithm based on different network parameter settings. The key idea is to build near‐minimal connected dominating set for the network at the grid level. Analytical and simulation results demonstrate that our designed algorithms outperform existing work. Furthermore, the diagonal algorithm outperforms the cross‐sectional algorithm. Copyright © 2016 John Wiley & Sons, Ltd.     

Weighted relay node placement for wireless sensor network connectivity

In wireless sensor networks (WSN), which are composed of unreliable sensor nodes, preserving the connectivity is a serious problem and one of the most effective solutions of this problem is to deploy powerful relay nodes (RN). The location of the RN is an important parameter for the network performance. In this paper, we investigate relay node placement (RNP) problem on a weighted terrain structure to satisfy WSN connectivity. Contrary to the existing studies, instead of minimizing the number of RN, the main objective of weighted RNP is to minimize the total weight of the points on which RN are deployed. In order to solve the weighted RNP problem, a mathematical formulation is proposed to find the optimal solution. However, because of the NP-complete nature of the problem, a polynomial time heuristic algorithm is also developed. Performance results show that the proposed heuristic algorithm can find near-optimal solutions in a reasonable time bound.     

基于Voronoi的无线传感器网络覆盖控制优化策略

针对无线传感器网络运行状态中存在覆盖空洞的问题,提出了一种基于Voronoi有效覆盖区域的空洞侦测修复策略。该策略以满足一定网络区域覆盖质量为前提,在空洞区域内合理增加工作节点以提高网络覆盖率为优化目标,采用几何图形向量方法对节点感知范围和Voronoi多边形的位置特性进行理论分析,力求较准确地计算出空洞面积,找寻最佳空洞修复位置,部署较少的工作节点保证整个网络的连通性。仿真结果表明,该策略能有效地减少网络总节点个数和感知重叠区域,控制网络中冗余节点的存在,同时其收敛速度较快,能够获得比现有算法更高的目标区域空洞修复率,实现网络覆盖控制优化.     

Power Efficient Video Multipath Transmission over Wireless Multimedia Sensor Networks

This paper proposes a power efficient multipath video packet scheduling scheme for minimum video distortion transmission (optimised Video QoS) over wireless multimedia sensor networks. The transmission of video packets over multiple paths in a wireless sensor network improves the aggregate data rate of the network and minimizes the traffic load handled by each node. However, due to the lossy behavior of the wireless channel the aggregate transmission rate cannot always support the requested video source data rate. In such cases a packet scheduling algorithm is applied that can selectively drop combinations of video packets prior to transmission to adapt the source requirements to the channel capacity. The scheduling algorithm selects the less important video packets to drop using a recursive distortion prediction model. This model predicts accurately the resulting video distortion in case of isolated errors, burst of errors and errors separated by a lag. Two scheduling algorithms are proposed in this paper. The Baseline scheme is a simplified scheduler that can only decide upon which packet can be dropped prior to transmission based on the packet’s impact on the video distortion. This algorithm is compared against the Power aware packet scheduling that is an extension of the Baseline capable of estimating the power that will be consumed by each node in every available path depending on its traffic load, during the transmission. The proposed Power aware packet scheduling is able to identify the available paths connecting the video source to the receiver and schedule the packet transmission among the selected paths according to the perceived video QoS (Peak Signal to Noise Ratio—PSNR) and the energy efficiency of the participating wireless video sensor nodes, by dropping packets if necessary based on the distortion prediction model. The simulation results indicate that the proposed Power aware video packet scheduling can achieve energy efficiency in the wireless multimedia sensor network by minimizing the power dissipation across all nodes, while the perceived video quality is kept to very high levels even at extreme network conditions (many sensor nodes dropped due to power consumption and high background noise in the channel).     

An Efficient Cross-Layer Optimization Algorithm for Data Transmission in Wireless Sensor Networks

In this paper, we propose a cross layer congestion optimization scheme for allocating the resources of wireless sensor networks to achieve maximization of network performance. The congestion control, routing selection, link capacity allocation, and power consumption are all taken account to yield an optimal scheme based on the Lagrangian optimization. The Lagrangian multiplier is adopted to adjust power consumption, congestion rate, routing selection and link capacity allocation, so that the network performance can be satisfied between the trade-off of efficiency and fairness of resource allocation. The proposed algorithm can significantly achieve the maximization of network performance in relieving the network congestion with less power consumption. Excellent simulation results are obtained to demonstrate our innovative idea, and show the efficiency of our proposed algorithm.