Connectivity-Guaranteed and Obstacle-Adaptive Deployment Schemes for Mobile Sensor Networks

Mobile sensors can relocate and self-deploy into a network. While focusing on the problems of coverage, existing deployment schemes largely oversimplify the conditions for network connectivity: they either assume that the communication range is large enough for sensors in geometric neighborhoods to obtain location information through local communication, or they assume a dense network that remains connected. In addition, an obstacle-free field or full knowledge of the field layout is often assumed. We present new schemes that are not governed by these assumptions, and thus adapt to a wider range of application scenarios. The schemes are designed to maximize sensing coverage and also guarantee connectivity for a network with arbitrary sensor communication/sensing ranges or node densities, at the cost of a small moving distance. The schemes do not need any knowledge of the field layout, which can be irregular and have obstacles/holes of arbitrary shape. Our first scheme is an enhanced form of the traditional virtual-force-based method, which we term the connectivity-preserved virtual force (CPVF) scheme. We show that the localized communication, which is the very reason for its simplicity, results in poor coverage in certain cases. We then describe a floor-based scheme which overcomes the difficulties of CPVF and, as a result, significantly outperforms it and other state-of-the-art approaches. Throughout the paper our conclusions are corroborated by the results from extensive simulations.     

移动传感器网络非均匀事件区域节点部署优化

针对移动传感器网络中热点事件监测场景,研究传感器节点的快速优化部署策略.首先假定事件随机产生,针对事件优先模型及节点感知误差函数推导基于Voronoi剖分时感知误差最小,然后定义节点有效覆盖权值,证明了当所有节点有效覆盖权值一致时,整个网络覆盖效能将达到最大.结合虚拟力及节点有效覆盖权提出一种分布式优化部署算法SDOA(Sparse Deployment Optimization Algorithm),其在保证覆盖能效最大化时保证网络连通性.最后仿真比较了本文提出部署策略能够快速有效实现对热点区域部署,并保证较高的覆盖效能.     

Adaptive Power Control Scheme for Mobile Wireless Sensor Networks

Wireless Personal Communications - One of the major factors that affects the performance of wireless sensor networks (WSN) is its limited battery capacity. Mobile wireless sensor networks (MWSN)...     

无线移动传感器网络自适应体系结构的设计

随着无线网络技术的日益成熟及其对小型、微型移动设备的支持，无线移动传感器网络已经逐渐成为一个研究的热点。主要讨论了为无线移动传感器网络设计的一个自适应的体系结构。在该体系结构中，使用了一个区域和核心路由节点相结合的多层结构的方法来增加无线移动网络的信息传输能力、可扩充性和可靠性，并降低网络的能耗，这样就可以适应无线移动网络的高度动态性和移动性。     

无线移动传感器网络自适应体系结构的设计

随着无线网络技术的日益成熟及其对小型、微型移动设备的支持,无线移动传感器网络已经逐渐成为一个研究的热点。主要讨论了为无线移动传感器网络设计的一个自适应的体系结构。在该体系结构中,使用了一个区域和核心路由节点相结合的多层结构的方法来增加无线移动网络的信息传输能力、可扩充性和可靠性,并降低网络的能耗,这样就可以适应无线移动网络的高度动态性和移动性。     

Enabling Applications Deployment on Mobile Networks

There is much interest in the possibility of both wireless and wireline network operators earning new revenues by encouraging the independent application development community to create new, useful ways of exploiting network capabilities; historically such capabilities have been under the exclusive control of the network operator. There are various initiatives supporting this aim through the specifications and promotion of standard application programming interfaces (APIs) that can be used to access these network functions. This paper gives an overview of the main initiatives and examines factors such as developer engagement and policing, that will affect the successful deployment and use of network APIs but that are unrelated to their exact technical specification. This revised version was published online in July 2006 with corrections to the Cover Date.     

移动混合传感网中节点自主部署算法

针对节点感知半径不均衡的移动传感网络节点的部署问题,论文提出一种基于VL(Voronoi Laguerre)图分割的节点自主部署算法(Autonomous Deployment Algorithm, ADA)。ADA先对目标区域做VL图划分,将目标区域的覆盖任务在各个传感器节点之间进行分配。分配到覆盖子区间任务的节点通过构造VL受控多边形来确定下一轮候选目标位置。未分配到覆盖子区间的节点则根据自身与邻居节点感知圆及目标区域边界的几何位置关系计算所受虚拟力,最终确定下一轮目标点坐标。网络各个节点通过逐轮更新自身位置,从而提高网络覆盖。仿真结果表明,ADA算法在网络覆盖率、节点部署速度和节点分布均匀性等方面具有明显的优势。     

无线可充电传感器网络中的充电桩部署

在传统的无线传感器网络中,由于自身能量存储的限制,电池供电的传感器节点缩短了整个网络的使用寿命,严重影响了网络性能。针对充电桩部署位置固定、位置不固定且不受限以及位置不固定且受限的3种情况,利用整数规划分别给出了具体的部署算法,使得整个传感器网络区域的充电效用最大化。最后利用Matlab进行仿真分析,与传统的全覆盖部署相比,使用该算法可以显著地减少所需要的充电桩数量。     

WSN中一种改进的节点部署方案

节点部署是无线传感器网络的基本问题之一,关系到网络的感知范围和信息传输服务质量。现有的部署算法需要额外探测和修复边界上的覆盖空洞,从而增加了网络部署的成本而且使得节点分布不均匀。针对这一问题,提出了一种改进的节点部署方案,首先进行边界部署,以保证边界上的完全覆盖和连通;然后在感应区域内生成一个新的凸多边形区域,在此新区域上再递归调用边界部署算法,直到整个感应区域被完全覆盖。理论分析和仿真实验表明,在部署节点个数和可扩展性方面均优于已有的部署方案。     

移动无线传感网能量时延约束的自适应路由及性能评估

 针对间歇性连通的移动无线传感网提出一种能量时延约束的自适应路由协议(EDCA),EDCA由初始化阶段、转发决策阶段、转发阶段和等待阶段组成,传感器节点根据目标时延实时判断是否转发副本,并选择剩余能量多的节点进行副本转发.EDCA对平均时延和网络负载具有控制力,对网络环境变化具有自适应能力,能够有效延长网络生命周期.     

无线传感器网络部署及其覆盖问题研究

无线传感器网络是近几年发展起来的一种新兴技术,在条件恶劣和无人坚守的环境监测和事件跟踪中显示了很大的应用价值。节点部署是无线传感器网络工作的基础,对网络的运行情况和寿命有很大的影响。部署问题涉及覆盖、连接和节约能量消耗3个方面。该文重点讨论了网络部署中的覆盖问题,综述了现有的研究成果,总结了今后的热点研究方向,为以后的研究奠定了基础。     

Quality of Deployment in Surveillance Wireless Sensor Networks

When wireless sensors are used to keep an area under surveillance, a critical issue is the quality of the deployment from the sensing coverage viewpoint. In this paper, we propose several quality measures, which indicate if the deployment provides sufficient coverage, or whether redeployment is required or not. The terrain is modeled as a grid and the placement of the sensors is uniformly distributed. Neyman–Pearson detection is utilized to determine the effects of false-alarm and signal characteristics on the measures.     

基坑监测系统中传感网的节点部署

基坑监测系统中,需要在各监测点部署传感器节点,系统的监测点围绕基坑工程展开,其监控区域近似圆环。在基站收集监测数据时,离基站越近的区域需要转发的数据越多,节点能量消耗速度也就越快,基站附近的节点将很快消耗完能量,系统随即瘫痪。通过研究圆环形传感网的拓扑特点,得到节点密度公式,使得各区域的总能量与能量消耗速度之比达到平衡。理论分析和仿真实验表明,按照此密度公式部署传感器节点,可显著提高系统生命周期。     

LED Adaptive Deployment Optimization in Indoor VLC Networks

Driven by the continuous penetration of high data rate services and applications,a large amount of unregulated visible light spectrum is used for communication ...     

Achieve Adaptive Data Storage and Retrieval Using Mobile Sinks in Wireless Sensor Networks

Wireless Personal Communications - In WSNs (Wireless Sensor Networks), data storage and retrieval is a challenging problem because of the limited resource and the short communication radius of the...     

Adaptive Sensor Activity Control in Many-to-One Sensor Networks

In this paper, we consider a many-to-one sensor network where a large number of sensors are deployed to monitor a physical environment. We explore sensor activity management to maximize the network lifetime, while meeting the quality-of-service (QoS) requirement. Specifically, in each round the sink estimates the number of active sensors and the control information is fed back to the sensors for activity control. We start with a basic case where the total number of sensors$N$is known, and the estimator of the number of active sensors$mathhatn_t$is accurate. We devise a sensor activity control scheme under which the number of active sensors would converge to the minimum that can meet the QoS requirement. Next, we generalize the study to the following two more complicated cases: (1) The case with known$N$and inaccurate$mathhatn_t$: For this case, we propose a stochastic approximation algorithm to minimize the average number of active sensors while meeting the QoS requirement. (2) The case with unknown$N$and accurate$mathhatn_t$: For this case, we cast the problem as the adaptive control of a Markov chain with unknown parameters and propose a composite optimization-oriented approach for the corresponding sensor activity control. We show that using this composite optimization-oriented approach the number of active sensors would converge to the minimum that can meet the QoS requirement.     

Coverage in Hybrid Mobile Sensor Networks

This paper considers the coverage problem for hybrid networks which comprise both static and mobile sensors. The mobile sensors in our network only have limited mobility, i.e., they can move only once over a short distance. In random static sensor networks, sensor density should increase as O(log L + k log log L) to provide k-coverage in a network with a size of L. As an alternative, an all-mobile network can provide k-coverage with a constant density of O(k), independent of network size L. We show that the maximum distance for mobile sensors is O( 1/sqrt(k) log^(4/3)(kL)). We then propose a hybrid network structure, comprising static sensors and a small fraction of O( 1/sqrt(k)) of mobile sensors. For this network structure, we prove that k-coverage is also achievable with a constant sensor density of O(k). Furthermore, for this hybrid structure, we prove that the maximum distance which any mobile sensor has to move is bounded as O(log^(3/4)L). We then propose a distributed relocation algorithm, where each mobile sensor only requires local information in order to optimally relocate itself. We verify our analysis via extensive numerical evaluations and show an implementation of the mobility algorithm on real mobile sensor platforms.     

k-Connected Relay Node Deployment in Heterogeneous Wireless Sensor Networks

Wireless Personal Communications - Compressive sensing (CS) is a new sampling theory used in many signal processing applications due to its simplicity and efficiency. However, signal reconstruction...     

Relay Node Deployment Strategies in Heterogeneous Wireless Sensor Networks

In a heterogeneous wireless sensor network (WSN), relay nodes (RNs) are adopted to relay data packets from sensor nodes (SNs) to the base station (BS). The deployment of the RNs can have a significant impact on connectivity and lifetime of a WSN system. This paper studies the effects of random deployment strategies. We first discuss the biased energy consumption rate problem associated with uniform random deployment. This problem leads to insufficient energy utilization and shortened network lifetime. To overcome this problem, we propose two new random deployment strategies, namely, the lifetime-oriented deployment and hybrid deployment. The former solely aims at balancing the energy consumption rates of RNs across the network, thus extending the system lifetime. However, this deployment scheme may not provide sufficient connectivity to SNs when the given number of RNs is relatively small. The latter reconciles the concerns of connectivity and lifetime extension. Both single-hop and multihop communication models are considered in this paper. With a combination of theoretical analysis and simulated evaluation, this study explores the trade-off between connectivity and lifetime extension in the problem of RN deployment. It also provides a guideline for efficient deployment of RNs in a large-scale heterogeneous WSN.     

Surveillance Wireless Sensor Networks: Deployment Quality Analysis

Surveillance wireless sensor networks are deployed at perimeter or border locations to detect unauthorized intrusions. For deterministic deployment of sensors, the quality of deployment can be determined sufficiently by analysis in advance of deployment. However, when random deployment is required, determining the deployment quality becomes challenging. To assess the quality of sensor deployment, appropriate measures can be employed that reveal the weaknesses in the coverage of SWSNs with respect to the success ratio and time for detecting intruders. In this article, probabilistic sensor models are adopted, and the quality of deployment issue is surveyed and analyzed in terms of novel measures. Furthermore, since the presence of obstacles in the surveillance terrain has a negative impact on previously proposed deployment strategies and analysis techniques, we argue in favor of utilizing image segmentation algorithms by imitating the sensing area as a grayscale image referred to as the iso-sensing graph. Finally, the effect of sensor count on detection ratio and time to detect the target is analyzed through OMNeT++ simulation of an SWSN in a border surveillance scenario.