Adaptive cluster-based relay-node placement for disjoint wireless sensor networks

Wireless Networks - Wireless sensor networks are formed with very small sensor devices with limited energy and short transmission range. Sensors are randomly deployed in remote areas with harsh...     

Biogeography-based optimization scheme for solving the coverage and connected node placement problem for wireless sensor networks

Wireless Networks - In wireless sensor networks, coverage and connectivity are the fundamental problems for monitoring the targets and guaranteed information dissemination to the far away base...     

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。     

Strategies and techniques for node placement in wireless sensor networks: A survey

The major challenge in designing wireless sensor networks (WSNs) is the support of the functional, such as data latency, and the non-functional, such as data integrity, requirements while coping with the computation, energy and communication constraints. Careful node placement can be a very effective optimization means for achieving the desired design goals. In this paper, we report on the current state of the research on optimized node placement in WSNs. We highlight the issues, identify the various objectives and enumerate the different models and formulations. We categorize the placement strategies into static and dynamic depending on whether the optimization is performed at the time of deployment or while the network is operational, respectively. We further classify the published techniques based on the role that the node plays in the network and the primary performance objective considered. The paper also highlights open problems in this area of research.     

Relay sensor placement in wireless sensor networks

This paper addresses the following relay sensor placement problem: given the set of duty sensors in the plane and the upper bound of the transmission range, compute the minimum number of relay sensors such that the induced topology by all sensors is globally connected. This problem is motivated by practically considering the tradeoff among performance, lifetime, and cost when designing sensor networks. In our study, this problem is modelled by a NP-hard network optimization problem named Steiner Minimum Tree with Minimum number of Steiner Points and bounded edge length (SMT-MSP). In this paper, we propose two approximate algorithms, and conduct detailed performance analysis. The first algorithm has a performance ratio of 3 and the second has a performance ratio of 2.5. Xiuzhen Cheng is an Assistant Professor in the Department of Computer Science at the George Washington University. She received her MS and PhD degrees in Computer Science from the University of Minnesota - Twin Cities in 2000 and 2002, respectively. Her current research interests include Wireless and Mobile Computing, Sensor Networks, Wireless Security, Statistical Pattern Recognition, Approximation Algorithm Design and Analysis, and Computational Medicine. She is an editor for the International Journal on Ad Hoc and Ubiquitous Computing and the International Journal of Sensor Networks. Dr. Cheng is a member of IEEE and ACM. She received the National Science Foundation CAREER Award in 2004. Ding-Zhu Du received his M.S. degree in 1982 from Institute of Applied Mathematics, Chinese Academy of Sciences, and his Ph.D. degree in 1985 from the University of California at Santa Barbara. He worked at Mathematical Sciences Research Institutea, Berkeley in 1985-86, at MIT in 1986-87, and at Princeton University in 1990-91. He was an associate-professor/professor at Department of Computer Science and Engineering, University of Minnesota in 1991-2005, a professor at City University of Hong Kong in 1998-1999, a research professor at Institute of Applied Mathematics, Chinese Academy of Sciences in 1987-2002, and a Program Director at National Science Foundation of USA in 2002-2005. Currently, he is a professor at Department of Computer Science, University of Texas at Dallas and the Dean of Science at Xi’an Jiaotong University. His research interests include design and analysis of algorithms for combinatorial optimization problems in communication networks and bioinformatics. He has published more than 140 journal papers and 10 written books. He is the editor-in-chief of Journal of Combinatorial Optimization and book series on Network Theory and Applications. He is also in editorial boards of more than 15 journals. Lusheng Wang received his PhD degree from McMaster University in 1995. He is an associate professor at City University of Hong Kong. His research interests include networks, algorithms and Bioinformatics. He is a member of IEEE and IEEE Computer Society. Baogang Xu received his PhD degree from Shandong University in 1997. He is a professor at Nanjing Normal University. His research interests include graph theory and algorithms on graphs.     

Gossip‐based scalable directed diffusion for wireless sensor networks

Directed diffusion (DD) is a promising data‐centric routing scheme for wireless sensor networks (WSNs). But the heavy flooding overhead involved in interest propagation causes scalability issues when DD is applied in large scale, interactive and dynamically changing sensor networks. To solve this problem, we propose a scalable version of DD called gossip‐based scalable directed diffusion (GSDD) in this paper. GSDD uses the same routing framework as DD but integrates gossiping in interest propagation and employs dynamic regional gossiping in path exploration phase to reduce the flooding overhead. Our analysis and simulation results demonstrate that GSDD is able to reduce the data delivery cost of DD by up to 25%; thus, significantly reduce energy consumption and prolong the lifetime of sensor nodes. Therefore, GSDD overcomes the scalability problem of DD and is suitable for large‐scale WSNs. Copyright © 2011 John Wiley & Sons, Ltd.     

异构传感器网络中汇聚节点位置优化路由算法

在异构无线传感器网络模型下,针对采集节点发送数据能量消耗过高及路由时分组丢失率过大等情况,对数据汇聚节点的位置优化及路由进行了研究,提出了移动汇聚节点位置优化路由算法（MLOYIH）。先根据蚁群算法的原理对移动节点与静态节点进行分组,再在组内寻找适合的位置放置汇聚节点,最后根据供电情况,选择合适的跳算进行路由。经过仿真实验与性能分析表明,MLOYIH算法与传统算法比较,能量消耗降低到64%,分组丢失率不高于3%。     

Backbone construction with relay node placement for energy‐efficient wireless sensor networks

In this paper, we address the energy‐efficient connectivity problem of a wireless sensor network (WSN) that consists of (1) static sensor nodes that have a short communication range and limited energy level, and (2) relay nodes that have a long communication range and unlimited power supply, and that can be added or relocated arbitrarily. For such a WSN, existing studies have been focused on the design of efficient approximation algorithms to minimize the number of relay nodes. By contrast, we propose a unified backbone construction framework that can be performed in a centralized manner with two objectives: (1) to minimize the number of nodes in the backbone and (2) to maximize the lifetime of the network. To solve such a challenging problem, we formulate three subproblems: (1) partial dominating set with energy threshold (PDSET); (2) partial dominating set with largest residual energy (PDSLE); and (3) minimum relay node placement (MRNP). For these three subproblems, we develop polynomial‐time algorithms. We also prove that our algorithm for PDSLE is optimal, and our algorithm for the PDSET and MRNP problems have small approximation ratios. Numerical results show that the proposed framework can significantly improve energy efficiency and reduce backbone size. Copyright © 2012 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.     

Energy-efficient node deployment strategy for wireless sensor networks

To balancing energy consumption in wireless sensor networks, we proposed a fixed time interval node broadcasting scheme under variational acceleration straight-line movement model. Simulation results show that the approach proposed in this paper has a superior performance on energy consumption balance compared to uniform broadcasting methods.     

基于序列的传感器网络节点定位算法

针对MSP算法需要借助额外的外部扫描设备,不适合应用于对野外大规模部署的传感器网络进行定位这一缺点,提出了一种HG-MSP算法。该算法通过锚节点发出扫描信息,不需要额外的外部设备进行辅助定位,提高了算法的可用性。仿真实验表明,在去掉辅助设备的情况下,算法的定位精度并无明显下降。     

基于矢量的无线传感器网络节点定位综合算法

基于DV-hop设计了一种节点的定位综合算法,并将其应用于移动节点.利用节点间估计距离和测量距离的差异构建位置校正矢量;通过改进的粒子群优化方法得到节点的校正步长;节点将其与位置校正矢量的乘积作为自身位置的校正值.通过仿真进行算法验证并分析了复杂度和有效性,结果证明该算法可以将DV-hop的定位误差下降75%,并且适用于稀疏网络.     

无线传感器网络自适应功率调整机制研究

无线传感器网络功率调整技术对于WSN节点的能量效率、生存时间、丢包率等性能均有显著影响,是其实用化的重要支撑技术。现提出了一种适用于无线传感器网络的自适应功率调整机制,只需要利用节点间的接收信号强度指示(RSSI)值,通过动态调整终端节点的功率值可以获得相对合适的发射功率,从而降低终端节点的能耗,可以适当延长节点的生存时间。实验结果证实了所提方法的有效性。     

Adaptive packet prioritisation for large wireless sensor networks

Large wireless sensor networks consisting of hundreds of devices are often used to conduct distinct monitoring tasks simultaneously. Furthermore, the significant events that can be detected by the network may be detected in many different parts of the network. As a consequence, these multiple tasks and diverse events may also cause resource contention and degradation of network quality of service. For instance, congestion created by regularly occurring events which do not need urgent forwarding to the monitoring centres may create delays for other events which need to be reported very rapidly. The Random Re-Routing (RRR) protocol for wireless sensor networks has therefore been proposed to adaptively prioritise the packets of certain urgent events above those of other less urgent events which may be of a more routine nature. In this paper we extend the RRR protocol to improve performance, and we use simulation experiments to illustrate heuristic algorithms for matching routing priorities to the requirements of the sensor network??s monitoring tasks. The approaches are based on selecting the protocol??s parameters prior to network deployment, and on using an acknowledgement mechanism for adapting the parameters during network operation.     

基于RSSI的传感器网络节点安全定位机制

针对RSSI测距存在的脆弱性问题,提出了一种基于完整性编码和不间断占用信道的安全RSSI测距协议,该协议不仅可以抵抗伪造插入、重放/虫洞等常规攻击,而且可以防止信标信号被恶意干扰而削弱,即可抵抗虚增测距的外部攻击。在此基础上,设计了一种基于RSSI的传感器网络节点安全定位机制,该机制采用可校验的多边测量法来过滤虚减测距的外部攻击,实现安全定位,并对测距协议和定位机制的安全性进行了理论分析。     

无线传感器网络节点应用的硬件设计

针对无线传感器网络技术引入到矿下安全监测中,首先分析了无线传感器网络的结构、特点及研究重点,提出了无线传感器网络节点的整体设计方案.介绍了传感器的选择和处理器、通信器件的选择,并将硬件分为数据采集单元、数据处理单元和数据传输单元进行详细的说明.     

Reference node placement and selection algorithm based on trilateration for indoor sensor networks

The key problem of location service in indoor sensor networks is to quickly and precisely acquire the position information of mobile nodes. Due to resource limitation of the sensor nodes, some of the traditional positioning algorithms, such as two‐phase positioning (TPP) algorithm, are too complicated to be implemented and they cannot provide the real‐time localization of the mobile node. We analyze the localization error, which is produced when one tries to estimate the mobile node using trilateration method in the localization process. We draw the conclusion that the localization error is the least when three reference nodes form an equilateral triangle. Therefore, we improve the TPP algorithm and propose reference node selection algorithm based on trilateration (RNST), which can provide real‐time localization service for the mobile nodes. Our proposed algorithm is verified by the simulation experiment. Based on the analysis of the acquired data and comparison with that of the TPP algorithm, we conclude that our algorithm can meet real‐time localization requirement of the mobile nodes in an indoor environment, and make the localization error less than that of the traditional algorithm; therefore our proposed algorithm can effectively solve the real‐time localization problem of the mobile nodes in indoor sensor networks. Copyright © 2008 John Wiley & Sons, Ltd.     

基于节点聚类的可伸缩多应用无线传感器网络模拟

提出一种基于节点聚类的无线传感器网络模拟方法,部署同类应用的节点在模拟器中采用单一实体建模,通过多个实体之间的通信实现不同节点的交互,并利用实体之间的同步驱动模拟事件的顺序进行.基于节点聚类方法,在主流模拟工具TOSSIM的基础上设计并实现了一个无线传感器网络模拟器ETMA;实验结果表明,基于节点聚类的模拟方法不仅可支持多应用无线传感器网络的模拟,同时还具有良好的可伸缩性.     

距离辅助的无线传感器网络节点覆盖判别模型

提出了距离辅助的节点覆盖判别模型DANCI(distance-assistant node coverage identification model),通过邻居节点到本节点的距离信息,判别该节点被邻居节点覆盖的程度.理论分析与仿真结果表明,在节点随机部署情况下,计算所得的覆盖度与节点位置已知情况下,其覆盖度的最大误差仅为6.396 0%.相对于邻居节点个数与最近邻居距离覆盖判别方法,极大提高了覆盖判别的精确性.     

Optimum node placement in wireless opportunistic routing networks

In recent years there has been a growing interest in opportunistic routing as a way to increase the capacity of wireless networks by exploiting its broadcast nature. In contrast to traditional uni-path routing, in opportunistic routing the nodes overhearing neighbor’s transmissions can become candidates to forward the packets towards the destination.In this paper we address the question: What is the maximum performance that can be obtained using opportunistic routing? To answer this question we use an analytical model that allows to compute the optimal position of the nodes, such that the progress towards the destination is maximized. We use this model to compute bounds to the minimum expected number of transmissions that can be achieved in a network using opportunistic routing.