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。     

基于博弈理论的无线传感器网络分布式节能路由算法

为了有效解决无线传感器网络路由节能问题,该文提出适合无线传感器网络的节能路由算法。在引入博弈理论概念建立网络模型的基础上,通过对于以往传感器网络簇首选择方法的研究,设计了一种基于博弈论的,兼顾节点剩余能量及簇首分布的节能路由DEER(DistributedEnergy-EconomicalRouting),大大节省了分布式决策网络协议的能量损耗。仿真证明了该方法在无线传感器网络中,能够有效地平衡网络负载,节省节点能量,延长网络寿命。     

智能电网中无线传感器网络的节能节点定位方法

无线传感器网络在智能电网目标检测、监测和定位中得到到越来越多的应用.在无线传感器网络中,能量是一种临界资源,系统寿命通过节能策略得到延长.提出了一种基于能量感知的节点检测和定位方法.这种方法只需要少量的传感器节点信息,由簇头执行定位程序来确定进一步定位所需的传感器子集.这样减少了能量消耗和通信带宽需求,延长了系统寿命.实验结果显示,这种定位方法可以节省高达32％的能量.     

煤矿智能救援系统井下WSN节点分级部署方法

煤矿智能救援系统,通过井下无线传感器网络监测数据,为系统提供安全预警支持.由于井下巷道错综复杂,不同的节点部署方法会影响井下监测数据传输的可靠性.为了节省无线传感嚣网络资源及维持网络的可靠通信,提出一种分级部署无线传感器网络节点方法,主干网节点采用最大通信距离算法部署,备用节点采用分级部署方法.仿真结果表明该方法有助于提高网络通信的可靠性,延长网络寿命,提升网络健壮性.     

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。     

无线传感器网络拓扑结构研究

随着处理技术、存储技术以及无线传输技术的不断发展,由体积小、重量轻、价格低的无线传感器节点所组成的传感器网络已经充分具备了感知客观事物及自然现象,随时随地为用户提供精确信息的能力。通过对于星状网、网状网和混合网等几种常用传感器网络拓扑结构的比较,以及针对这些拓扑结构所形成的网络寿命的仿真,说明了对于常用的基站距离远、节点密度大的传感器网络,分层式的拓扑结构能够大大的节省网络能量,延长网络寿命,改善网络性能。     

无线传感器网络自适应目标跟踪节点调度算法

在无线传感器网络中,设计合理的节点调度算法是提高网络感知能力、降低系统能耗的关键。在分析节点能耗模型的基础上,针对移动目标跟踪型网络应用,提出一种高能效的无线传感器网络自适应节点调度算法ANSTT。该算法根据节点对移动目标的感知能力,以及节点的相对剩余能量水平,自动调整节点工作模式。仿真实验表明,ANSTT算法在维持低感知延时、高目标感知率的同时,可有效降低系统能耗,延长网络寿命。     

WSN中基于网络覆盖控制算法优化研究

无线传感器网络中,传感器节点的能量不易补充,如何提高能量效率成为了传感器网络研究的重大问题。文章首先分析了经典的无线传感器网络节点调度算法（CPNSS算法）。针对其利用率低,能量不均衡的问题,提出了一种高效节能的无线传感器网络覆盖优化算法（Efficient Coverage—Preserving Node Scheduling Scheme）,并具体介绍了ECPNSS算法设计及其实现过程。最后,将ECPNSS算法应用于LEACH协议,仿真结果表明,ECPNSS算法能有效节省网络能量,延长网络生存期。     

无线传感器网络中V-BLAST接收方案性能的研究

由于无线传感器网络部署的地区环境复杂、电池难以更换，因此用传感器能量的高效使用来延长整个网络的寿命，是传感器网络需要考虑的重要方面。在介绍了无线传感器网络中基于虚拟MIMO通信系统的两个模型方案的基础上，针对能量效率高的V—BLAST方案由误码率与信噪比的研究对节省传感器节点的能量进行了分析。     

基于ERPMT改进启发式方法的WSN寿命最大化算法

针对传感器节点的电池容量限制导致无线传感网络寿命低的问题,基于容量最大化(CMAX)、线上最大化寿命(OML)两种启发式方法以及高效路由能量管理技术(ERPMT),提出了基于ERPMT改进启发式方法的无线传感网络寿命最大化算法。首先,通过启发式方法初始化每个传感器节点,将节点能量划分为传感器节点起源数据和其它节点数据延迟;然后利用加入的一种优先度量延迟一跳节点的能量消耗;最后,根据路径平均能量为每个路由分配一个优先级,并通过ERPMT实现最终的无线传感网络优化。针对不同分布类型网络寿命的实验验证了本文算法的有效性及可靠性,实验结果表明,相比较为先进的启发式方法CMAX及OML,本文算法明显增大了无线传感网络的覆盖范围,并且大大地延长了网络的寿命。     

Secure coverage-preserving node scheduling scheme using energy prediction for wireless sensor networks

With the fast development of the micro-electro-mechanical systems(MEMS),wireless sensor networks(WSNs)have been extensively studied.Most of the studies focus on saving energy consumption because of restricted energy supply in WSNs.Cluster-based node scheduling scheme is commonly considered as one of the most energy-efficient approaches.However,it is not always so efficient especially when there exist hot spot and network attacks in WSNs.In this article,a secure coverage-preserved node scheduling scheme for WSNs based on energy prediction is proposed in an uneven deployment environment.The scheme is comprised of an uneven clustering algorithm based on arithmetic progression,a cover set partition algorithm based on trust and a node scheduling algorithm based on energy prediction.Simulation results show that network lifetime of the scheme is 350 rounds longer than that of other scheduling algorithms.Furthermore,the scheme can keep a high network coverage ratio during the network lifetime and achieve the designed objective which makes energy dissipation of most nodes in WSNs balanced.     

A Coverage-Based Scheduling Algorithm for WSNs

Node scheduling in wireless sensor networks (WSNs) plays a vital role in conserving energy and lengthening the lifetime of networks, which are considered as prime design challenges. In large-scaled WSNs, especially where sensor nodes are deployed randomly, 100 % coverage is not possible all the times. Additionally, several types of applications of WSNs do not require 100 % coverage. Following these facts, in this paper, we propose a coverage based node scheduling algorithm. The algorithm shows that by sacrificing a little amount of coverage, a huge amount of energy can be saved. This, in turns, helps to increase the lifetime of the network. We provide mathematical analysis, which verifies the correctness of the proposed algorithm. The proposed algorithm ensures balanced energy consumption over the sensor networks. Moreover, simulation results demonstrate that the proposed algorithm almost doubles the lifetime of a wireless sensor network by sacrificing only 5–8 % of coverage.     

Sink Node Placement Strategies for Wireless Sensor Networks

In wireless sensor networks (WSNs), all the data collected by the sensor nodes are forwarded to a sink node. Therefore, the placement of the sink node has a great impact on the energy consumption and lifetime of WSNs. This paper investigates the energy-oriented and lifetime-oriented sink node placement strategies in the single-hop and multiple-hop WSNs, respectively. The energy-oriented strategy considers only the minimizing of the total energy consumption in the networks, while the lifetime-oriented strategy focuses much more on the lifetime of the nodes which consume energy fastest. Using a routing-cost based ant routing algorithm, we evaluate the performances of different placement strategies in the networks. Simulation results show that the networks with lifetime-oriented strategy achieve a significant improvement on network lifetime.     

基于能量预测的无线传感器网络节点覆盖调度算法

针对无线传感器网络中存在的热区问题,采用非均匀部署方案,并在此基础上提出基于能量预测的无线传感器网络节点覆盖调度算法。并对算法进行了仿真实验和性能分析。结果表明该算法可以延长的网络生命周期并在较长的时间里保持较高的网络覆盖率,能够达到网络内大多数节点能耗均衡的设计目标。     

Optimal base-station locations in two-tiered wireless sensor networks

We consider generic two-tiered wireless sensor networks (WSNs) consisting of sensor clusters deployed around strategic locations, and base-stations (BSs) whose locations are relatively flexible. Within a sensor cluster, there are many small sensor nodes (SNs) that capture, encode, and transmit relevant information from a designated area, and there is at least one application node (AN) that receives raw data from these SNs, creates a comprehensive local-view, and forwards the composite bit-stream toward a BS. This paper focuses on the topology control process for ANs and BSs, which constitute the upper tier of two-tiered WSNs. Since heterogeneous ANs are battery-powered and energy-constrained, their node lifetime directly affects the network lifetime of WSNs. By proposing algorithmic approaches to locate BSs optimally, we can maximize the topological network lifetime of WSNs deterministically, even when the initial energy provisioning for ANs is no longer always proportional to their average bit-stream rate. The obtained optimal BS locations are under different lifetime definitions according to the mission criticality of WSNs. By studying intrinsic properties of WSNs, we establish the upper and lower bounds of maximal topological lifetime, which enable a quick assessment of energy provisioning feasibility and topology control necessity. Numerical results are given to demonstrate the efficacy and optimality of the proposed topology control approaches designed for maximizing network lifetime of WSNs.     

An Energy-Efficient Routing Algorithm Based on Relative Identification and Direction for Wireless Sensor Networks

In studies of wireless sensor networks (WSNs), routing protocols in network layer is an important topic. To date, many routing algorithms of WSNs have been developed such as relative direction-based sensor routing (RDSR). The WSNs in such algorithm are divided into many sectors for routing. RDSR could simply reduce the number of routes as compared to the convention routing algorithm, but it has routing loop problem. In this paper, a less complex, more efficient routing algorithm named as relative identification and direction-based sensor routing (RIDSR) algorithm is proposed. RIDSR makes sensor nodes establish more reliable and energy-efficient routing path for data transmission. This algorithm not only solves the routing loop problem within the RDSR algorithm but also facilitates the direct selection of a shorter distance for routing by the sensor node. Furthermore, it saves energy and extends the lifetime of the sensor nodes. We also propose a new energy-efficient algorithm named as enhanced relative identification and direction-based sensor routing (ERIDSR) algorithm. ERISDR combines triangle routing algorithm with RIDSR. Triangle routing algorithm exploits a simple triangle rule to determine a sensor node that can save more energy while relaying data between the transmitter and the receiver. This algorithm could effectively economize the use of energy in near-sensor nodes to further extend the lifetime of the sensor nodes. Simulation results show that ERIDSR get better performance than RDSR, and RIDSR algorithms. In addition, ERIDSR algorithm could save the total energy in near-sensor nodes more effectively.     

DUCR: Distributed unequal cluster‐based routing algorithm for heterogeneous wireless sensor networks

Designing energy efficient communication protocols for wireless sensor networks (WSNs) to conserve the sensors' energy is one of the prime concerns. Clustering in WSNs significantly reduces the energy consumption in which the nodes are organized in clusters, each having a cluster head (CH). The CHs collect data from their cluster members and transmit it to the base station via a single or multihop communication. The main issue in such mechanism is how to associate the nodes to CHs and how to route the data of CHs so that the overall load on CHs are balanced. Since the sensor nodes operate autonomously, the methods designed for WSNs should be of distributed nature, i.e., each node should run it using its local information only. Considering these issues, we propose a distributed multiobjective‐based clustering method to assign a sensor node to appropriate CH so that the load is balanced. We also propose an energy‐efficient routing algorithm to balance the relay load among the CHs. In case any CH dies, we propose a recovery strategy for its cluster members. All our proposed methods are completely distributed in nature. Simulation results demonstrate the efficiency of the proposed algorithm in terms of energy consumption and hence prolonging the network lifetime. We compare the performance of the proposed algorithm with some existing algorithms in terms of number of alive nodes, network lifetime, energy efficiency, and energy population.     

Lifetime analysis of wireless sensor nodes in different smart grid environments

Wireless sensor networks (WSNs) can help the realization of low-cost power grid automation systems where multi-functional sensor nodes can be used to monitor the critical parameters of smart grid components. The WSN-based smart grid applications include but not limited to load control, power system monitoring and control, fault diagnostics, power fraud detection, demand response, and distribution automation. However, the design and implementation of WSNs are constrained by energy resources. Sensor nodes have limited battery energy supply and accordingly, power aware communication protocols have been developed in order to address the energy consumption and prolong their lifetime. In this paper, the lifetime of wireless sensor nodes has been analyzed under different smart grid radio propagation environments, such as 500 kV substation, main power control room, and underground network transformer vaults. In particular, the effects of smart grid channel characteristics and radio parameters, such as path loss, shadowing, frame length and distance, on a wireless sensor node lifetime have been evaluated. Overall, the main objective of this paper is to help network designers quantifying the impact of the smart grid propagation environment and sensor radio characteristics on node lifetime in harsh smart grid environments.     

Energy conservation in wireless sensor networks: A survey

In the last years, wireless sensor networks (WSNs) have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery-powered devices, the critical aspects to face concern how to reduce the energy consumption of nodes, so that the network lifetime can be extended to reasonable times. In this paper we first break down the energy consumption for the components of a typical sensor node, and discuss the main directions to energy conservation in WSNs. Then, we present a systematic and comprehensive taxonomy of the energy conservation schemes, which are subsequently discussed in depth. Special attention has been devoted to promising solutions which have not yet obtained a wide attention in the literature, such as techniques for energy efficient data acquisition. Finally we conclude the paper with insights for research directions about energy conservation in WSNs.     

Prolonging lifetime for wireless rechargeable sensor networks through sleeping and charging scheduling

Prolonging network lifetime is a fundamental requirement in wireless sensor network (WSN). Existing charging scheduling algorithms suffer from high node redundancy and energy consumption issues. In this paper, we study WSN charging problem from the perspectives of energy conservation combined with energy replenishment scheduling. Firstly, we detect the redundant nodes whose energy is wasted in the network functionality and develop a K‐covering redundant nodes sleeping scheduling algorithm (KRSS) for reducing energy. Secondly, we employed multiple wireless charging vehicles (WCVs) for energy replenishment and optimize the charging scheduling algorithm to prevent any exhaustion of nodes, and we proposed a distance and energy–oriented charging scheduling algorithm (DECS) with multiple WCVs. Simulation experiments are conducted to show the advantages of the proposed KRSS+DECS, confirming that our scheme is capable of removing redundant nodes, lowering node failures, and prolonging network lifetime.