基于移动节点的无线传感器网络覆盖洞修复方法

针对静态无线传感器网络中常常出现的覆盖洞问题,采用了移动节点进行修复的思路,提出了三角形贴片式的逐步增加移动节点方法。该方法利用覆盖洞边缘节点提供的辅助信息,指导移动节点移动到"最佳"位置。首先从几何理论上分析了最佳位置的存在条件,随后证明了在相关位置部署移动节点可以保证最低覆盖率大于90%,最后以仿真实验验证并分析了该算法的覆盖度、稳定性、冗余度等指标,并从移动节点覆盖能力利用率的角度,与相关工作进行了对比实验分析。     

基于Voronoi图的无线传感器网络覆盖算法研究

覆盖问题在无线传感器网络研究中具有很重要的地位,用最少的节点获得最大的覆盖面积是研究目标。Voronoi图,又叫泰森多边形或Dirichlet图,它是由一组由连接两邻点直线的垂直平分线组成的连续多边形组成。在一对邻近节点间,垂直平分线上的每个点被感知到的概率最小。文章中,作者提出一种基于Voronoi图的无线传感器网络覆盖算法,算法中先找出最大可能盲点,然后重新部署节点,以达到用最少的节点获得最大的监测面积。仿真实验证明了算法有效性。     

无线传感器网络覆盖连通性研究

针对无线传感器网络部署区域由于通信障碍和其他一些因素产生的某些节点无法与网络通信的情况,绐出了一种使用节点代理解决监测区域内节点通信不可达的方案,并基于一般意义的网络系统模型提出了一种探测覆盖区域内节点连通性的算法,即基于深度探测的节点覆盖连通性判定算法DBDAFNCJ.节点连通性分析和仿真实验结果表明,节点代理方案可以很好改善节点部署区域内节点通信不可达的情况,同时表明DBDAFNCJ算法可以高效、准确地获悉部署区域内节点连通性的情况.     

一种面向三维感知的无线多媒体传感器网络覆盖增强算法

 覆盖作为无线传感器网络中的基础问题直接反映了网络感知服务质量.本文在分析现有无线多媒体传感器网络覆盖增强算法的基础上,构建节点三维感知模型,提出面向三维感知的多媒体传感器网络覆盖增强算法(Three-Dimensional Perception Based Coverage-Enhancing Algorithm,TDPCA).该算法将节点主感知方向划分为仰俯角和偏向角,并根据节点自身位置及监测区域计算并调整各节点最佳仰俯角,在此基础上基于粒子群优化调整节点偏向角,从而有效减少节点感知重叠区及感知盲区,最终实现监测场景的区域覆盖增强.仿真实验表明:对比已有的覆盖增强算法,TDPCA可有效降低除节点感知重叠区和盲区,最终实现网络的高效覆盖.     

无线传感器网络覆盖控制技术综述

覆盖控制是无线传感器网络的一个基本问题,可以使无线传感网络的空间资源得到优化分配,进而更好地完成环境感知、信息获取和有效传输的任务;覆盖控制决定了传感器网络对物理世界的监测性能,分析了网络覆盖技术在国内外研究的现状与发展,指出了传感器网络能量受限、规模大、动态性强,给覆盖控制的研究带来了巨大挑战。总结覆盖控制基本概念,最后提出当前亟待解决的问题,并对其未来的发展趋势进行展望。     

基于粒子群算法的无线传感器网络覆盖优化

传统无线传感器网络覆盖优化方法所选算法的结构不合理,使其覆盖能力、迭代能力和有效性无法维系网络基本功能,为此提出粒子群算法的无线传感器网络覆盖优化方法。通过构建无线传感器网络认知模型,将网络覆盖优化工作转化成求取目标物体最大覆盖几率问题,使用粒子群算法对模型进行编码,利用模型适应度函数给出的约束值对网络节点位置进行更新,实现对无线传感器网络覆盖率的优化。通过分析仿真实验结论可知,与传统方法相比,该方法具有更强的覆盖能力、迭代能力和有效性。     

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.     

无线传感器网络覆盖优化控制技术分析

覆盖控制问题是无线传感器组网的一个基本问题，本文对传感节点的组成、定位方法，网络的拓扑结构等进行了简要的介绍。分析了无线传感器网络覆盖问题的背景，并针对覆盖冗余检测的主要方法和数学模型，讨论了无线传感器网络能量高效覆盖优化与网络连通性的关系。重点阐述了覆盖控制的技术手段，最后对无线传感器网络的覆盖控制关键技术进行了展望。     

基于PSO的无线多媒体传感器网络覆盖增强算法

在无线多媒体传感器网络(Wireless Multimedia Sensor Networks,WMSNs)中,由于节点部署的不合理,往往存在较多的监控盲区,影响了网络的服务质量。为了提高网络的覆盖率,在有向感知模型基础的基础上,提出了一种基于粒子群算法的WMSNs覆盖增强算法PSOCE。PSOCE算法以网络覆盖率为优化目标,以粒子群算法为计算工具,同时对节点的位置与主感知方向进行调整。仿真试验表明,PSOCE算法能够有效地改进WMSNs的覆盖质量,网络的覆盖率能提高6%～12%。     

基于节点休眠的水下无线传感器网络覆盖保持分簇算法

为有效延长水下无线传感器网络的生命周期、保持网络覆盖率,该文提出一种基于节点休眠的覆盖保持分簇算法。首先计算网络节点的覆盖冗余度,并对覆盖冗余度高的节点执行休眠策略,然后以网络覆盖率及节点能耗均衡性为目标,采用多目标算法进行求解,再利用TOPSIS法从非支配解集中选出较优解,当有节点死亡时,通过唤醒策略保持网络覆盖率。仿真结果表明,与目前较好的网络规划算法相比,该文算法能够更好地降低网络能耗,延长网络生命周期并保持网络对环境的覆盖率。     

一种基于有向感知模型的传感器节点覆盖算法

覆盖控制作为无线传感器网络中的一个基本问题,反映了传感器网络所能提供的“感知”服务质量.优化传感器网络覆盖对于合理分配网络的空间资源,更好地完成环境感知、信息获取任务以及提高网络生存能力都具有重要的意义.针对无线传感器网络方向个数固定的有向感知模型提出一种覆盖增强算法,采用复杂网络社团结构算法划分对网络进行节点子集划分,重新调整节点的感知方向,增强网络的覆盖率,同时有效降低了算法的时间复杂度.     

异构传感器网络覆盖势力剖分算法

对于普遍存在的异构传感器网络,目前尚缺乏有力的方法解决其覆盖势力的剖分问题。对此,该文提出一种本地化的覆盖势力剖分算法CFA(Coverage Force Algorithm)。该算法根据节点感应能力的差异,构建基于感应异构性的通用Voronoi图,能有效对网络中异构节点的覆盖势力范围进行剖分。实验证明,CFA算法解决了异构网络覆盖性能分析问题,和传统的Voronoi图方法相比,具有广普性和本地化的特点。     

WSN中能量有效分簇多跳路由算法

针对现有无线传感器网络(WSN)分簇路由算法存在的能耗不均衡问题,提出一种能量有效分簇多跳路由算法,该算法包括两个方面:一是选举簇首时引入簇内平均剩余能量因子,根据上一轮结束后簇内各节点剩余能量和簇内节点的平均剩余能量的比值更新簇首在所有节点中所占的百分比;二是要求簇首根据MTE多跳路由协议与基站通信,从而均衡WSN整...     

Power control based cooperative opportunistic routing in wireless sensor networks

This paper proposes an approach called PC-CORP (Power Control based Cooperative Opportunistic Routing Protocol) for WSN (Wireless Sensor Networks), providing robustness to the random variations in network connectivity while ensuring better data forwarding efficiency in an energy efficient manner. Based on the realistic radio model, we combine the region-based routing, rendezvous scheme, sleep discipline and cooperative communication together to model data forwarding by cross layer design in WSN. At the same time, a lightweight transmission power control algorithm called PC-AIMD (Power Control Additive Increase Multiplicative Decrease) is introduced to utilize the cooperation of relay nodes to improve the forwarding efficiency performance and increase the robustness of the routing protocol. In the simulation, the performance of PC-COPR is investigated in terms of the adaptation of variations in network connectivity and satisfying the QoS requirements of application.     

Connectivity maintenance and coverage preservation in wireless sensor networks

In wireless sensor networks, one of the main design challenges is to save severely constrained energy resources and obtain long system lifetime. Low cost of sensors enables us to randomly deploy a large number of sensor nodes. Thus, a potential approach to solve lifetime problem arises. That is to let sensors work alternatively by identifying redundant nodes in high-density networks and assigning them an off-duty operation mode that has lower energy consumption than the normal on-duty mode. In a single wireless sensor network, sensors are performing two operations: sensing and communication. Therefore, there might exist two kinds of redundancy in the network. Most of the previous work addressed only one kind of redundancy: sensing or communication alone. Wang et al. [Intergrated Coverage and Connectivity Configuration in Wireless Sensor Networks, in: Proceedings of the First ACM Conference on Embedded Networked Sensor Systems (SenSys 2003), Los Angeles, November 2003] and Zhang and Hou [Maintaining Sensing Coverage and Connectivity in Large Sensor Networks. Technical report UIUCDCS-R-2003-2351, June 2003] first discussed how to combine consideration of coverage and connectivity maintenance in a single activity scheduling. They provided a sufficient condition for safe scheduling integration in those fully covered networks. However, random node deployment often makes initial sensing holes inside the deployed area inevitable even in an extremely high-density network. Therefore, in this paper, we enhance their work to support general wireless sensor networks by proving another conclusion: “the communication range is twice of the sensing range” is the sufficient condition and the tight lower bound to ensure that complete coverage preservation implies connectivity among active nodes if the original network topology (consisting of all the deployed nodes) is connected. Also, we extend the result to k-degree network connectivity and k-degree coverage preservation.     

The novel communication algorithm and the throughput analysis for wireless sensor networks

Aiming at the significance of the energy controls of wireless sensor networks, an economical energy consumption algorithm for wireless communicating in Wireless Sensor Networks (WSN) is presented. Based on the algorithm, the maximal system throughput of WSN is analyzed, and the upper bound of throughput of WSN is proposed and proved. Some numerical simulations are conducted and analyzed. The conclusions include that the transmitting radius of sensor node and the parameters of the energy cost function have significant influence upon the throughput, but the monitoring region radius has little influence. For the same transmitting distance, the more the hopping of information trans- mitting, the better the throughput of WSN. On the other hand, for the energy optimization of the whole WSN, the trade-off problem between the throughput capacity and the relay nodes is proposed, and the specific expression of relay hops that minimized the energy consumptions and the maximal throughput of WSN under the specific situation is derived.     

MST-based clustering topology control algorithm for wireless sensor networks

In this paper, we propose a novel clustering topology control algorithm named Minimum Spanning Tree (MST)-based Clustering Topology Control (MCTC) for Wireless Sensor Networks (WSNs), which uses a hybrid approach to adjust sensor nodes’ transmission power in two-tiered hierarchical WSNs. MCTC algorithm employs a one-hop Maximum Energy &; Minimum Distance (MEMD) clustering algorithm to decide clustering status. Each cluster exchanges information between its own Cluster Members (CMs) locally and then deliveries information to the Cluster Head (CH). Moreover, CHs exchange information between CH and CH and afterwards transmits aggregated information to the base station finally. The intra-cluster topology control scheme uses MST to decide CMs’ transmission radius, similarly, the inter-cluster topology control scheme applies MST to decide CHs’ transmission radius. Since the intra-cluster topology control is a full distributed approach and the inter-cluster topology control is a pure centralized approach performed by the base station, therefore, MCTC algorithm belongs to one kind of hybrid clustering topology control algorithms and can obtain scalability topology and strong connectivity guarantees simultaneously. As a result, the network topology will be reduced by MCTC algorithm so that network energy efficiency will be improved. The simulation results verify that MCTC outperforms traditional topology control schemes such as LMST, DRNG and MEMD at the aspects of average node’s degree, average node’s power radius and network lifetime, respectively.     

Defense against collusion scheme based on elliptic curve cryptography for wireless sensor networks

Wireless Sensor Networks (WSNs) are being deployed for a wide variety of applications and the security problems of them have received considerable attention. Considering the limitations of power, com-putation capability and storage resources, this paper proposed an efficient defense against collusion scheme based on elliptic curve cryptography for wireless sensor networks in order to solve the problems that sensor node-key leaking and adversaries make compromised nodes as their collusions to launch new attack. In the proposed scheme, the group-key distribution strategy is employed to compute the private key of each sensor node, and the encryption and decryption algorithms are constructed based on Elliptic Curve Cryptography (ECC). The command center (node) only needs to broadcast a controlling header with three group elements, and the authorized sensor node can correctly recover the session key and use it to decrypt the broadcasting message. Analysis and proof of the proposed scheme’s efficiency and security show that the proposed scheme can resist the k-collusion attack efficiently.     

An efficient UE cluster head selection algorithm in wireless sensor networks and cellular networks

Wireless Sensor Networks (WSNs) have been applied in many different areas. Energy efficient algorithms and protocols have become one of the most challenging issues for WSN. Many researchers focused on developing energy efficient clustering algorithms for WSN, but less research has been concerned in the mobile User Equipment (UE) acting as a Cluster Head (CH) for data transmission between cellular networks and WSNs. In this paper, we propose a cellular-assisted UE CH selection algorithm for the WSN, which considers several parameters to choose the optimal UE gateway CH. We analyze the energy cost of data transmission from a sensor node to the next node or gateway and calculate the whole system energy cost for a WSN. Simulation results show that better system performance, in terms of system energy cost and WSNs life time, can be achieved by using interactive optimization with cellular networks.     

A local dynamic cluster self-organization algorithm in wireless sensor networks for rainfall monitoring

Wireless Sensor Networks for Rainfall Monitoring (RM-WSNs) is a sensor network for the large-scale regional and moving rainfall monitoring, which could be controlled deployment. Delivery delay and cross-cluster calculation leads to information inaccuracy by the existing dynamic collaborative self-organization algorithm in WSNs. In this letter, a Local Dynamic Cluster Self-organization algorithm (LDCS) is proposed for the large-scale regional and moving target monitoring in RM-WSNs. The algorithm utilizes the resource-rich node in WSNs as the cluster head, which processes target information obtained by sensor nodes in cluster. The cluster head shifts with the target moving in chance and re-groups a new cluster. The target information acquisition is limited in the dynamic cluster, which can reduce information across-clusters transfer delay and improve the real-time of information acquisition. The simulation results show that, LDCS can not only relieve the problem of “too frequent leader switches” in IDSQ, also make full use of the history monitoring information of target and continuous monitoring of sensor nodes that failed in DCS.