基于MOEA/P的无线传感器网络节点部署研究

在无线传感器网络节点部署中,提高网络覆盖性、连通性,降低网络成本,满足过度覆盖约束等是优化无线传感器网络的多个目标,提高无线传感器网络的服务质量的问题成为一个多目标优化问题。研究围绕在二维的平面区域进行传感器节点的部署。在保证连通性的基础上,采用基于投影面的MOEA/P算法实现最大化覆盖区域,最小化节点部署成本。实验结果表明,采用MOEA/P算法进行节点部署优化比采用MOEA/D算法在IGD指标上降低了18.5%。     

基于非可加几何覆盖的无线传感器网络周界覆盖分析

在随机部署中,最为关注的问题是如何判断监控区域被部署的传感器节点所充分覆盖.本文首先将无线传感器网络的信息覆盖从概率测度空间推广到Sugeno测度空间,研究了传感器网络的非可加几何覆盖,并在此基础上提出了一种非可加几何覆盖的周界覆盖分析方法.理论分析结果显示基于非可加几何覆盖的周界覆盖分析方法比圆盘覆盖更加准确地反映了传感器网络的实际的区域覆盖范围,比概率覆盖更加灵活,可以满足实际部署中不同情况的要求.     

无线传感器网络规则部署的k-重覆盖模型特性研究

无线传感器网络规则部署的k-重覆盖模型特性直接影响着网络监测结果的全面性和准确性,决定上层协议的可靠性。本文通过计算几何理论,对正n边形网格k-重覆盖模型的物理特性进行理论分析得出,各模型在确保预设k-重覆盖需求下的节点临界部署距离阈值,为实现网络可靠覆盖控制算法设计提供基础;并通过MAT-LAB仿真实验研究获得了不同k-重覆盖需求下最优覆盖模型,为高效节点部署提供指导依据。     

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。     

一种改进的虚拟力重定位覆盖增强算法

在移动无线传感网络(MWSN)的部署问题中最关键的是如何提供最大的区域覆盖范围。针对现有的覆盖控制算法存在覆盖率不理想、部署效率低、能耗过高的问题,该文提出了一种高效部署策略。第1阶段利用Voronoi图获得整个网络的覆盖孔,检测Voronoi多边形内的未覆盖区域,并提供虚拟力驱动传感器移动,同时采用动态调整策略改变移动步长,从而减少能量损耗;第2阶段提出一种检测机制,利用Delaunay三角网检测传感器之间的局部覆盖孔并进行修复。仿真结果表明,该算法在提高网络覆盖率的同时加快了收敛速度,为部署移动无线传感网络提供了新的解决思路。     

基于执行器的WSAN传感器配置方法研究

传感器网络旨在通过监测环境,完成事件检测和目标跟踪功能。为了实现这一点,覆盖是任意传感器网络的功能基础,影响覆盖的因素包括随机节点撒布、节点失效、受控节点移动性耦合等。通过利用WSAN(无线传感器与执行器网络)中的节点移动性,可以设计多种不同的传感器配置方式。文章介绍了移动传感器的两种迁移方式,分析了LRV(最近最少访问)、SLD(蛇形部署)和BTD(回溯部署)3种基于执行器的传感器配置方法的原理与实现流程。     

无线传感器网络可靠性建模方法

无线传感器网络部署设计的基础就是可靠性,因此,对无线传感器网络可靠性研究已经成为全世界在这个领域中研究的一个重点内容。无线传感器网络可靠性研究的一个有效方法就是建立数学模型。为了能够更好地进行无线传感器网络可靠性的建模,本文先介绍了无线传感器网络结构和节点模型,然后主要对无线传感器网络可靠性建模方法进行分析,提出了K-可靠性模型,并对无线传感器网络系统设计时参考依据进行简单说明。经过实践证明,无线传感器网络的可靠性完全能够通过K-可靠性模型进行测量。     

无线传感器网络中覆盖算法研究综述

覆盖问题是无线传感器网络中的重要问题.覆盖问题的解决对于传感器网络中的数据收集、数据聚集、数据查询、数据挖掘等应用具有重要的意义.近年来,研究者们针对不同拓扑结构的无线传感器网络中的不同类型的覆盖问题展开了研究.本文将针对现有覆盖问题的算法进行总结,并对现存算法所存在的问题进行分析.     

基于半径可调的三维无线传感器网络覆盖控制

针对三维空间下的无线传感器网络覆盖问题,考虑在满足最优覆盖节点集的基础上,同时减少网络能耗,提出了一种半径可调的三维无线传感器网络的低能耗覆盖方法。根据节点具有可调节传感半径的属性,在三维空间中利用遗传算法动态优化节点布局。仿真结果表明,节点的部署能够在达到较高的覆盖率和节点休眠率的同时,有效降低网络能耗,从而延长网络的生存时间。     

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。     

Coverage and Lifetime Optimization of Wireless Sensor Networks with Gaussian Distribution

A wireless sensor network (WSN) has to maintain a desirable sensing coverage and periodically report sensed data to the administrative center (i.e., base station) and the reporting period may range from months to years. Coverage and lifetime are two paramount problems in a WSN due to constraint of associated battery power. All previous theoretical analysis on the coverage and lifetime is primarily focused on the random uniform distribution of sensors or some specific network scenarios (e.g., a controllable WSN). In this paper, we provide an analytical framework for the coverage and lifetime of a WSN that follows a two-dimensional Gaussian distribution. We also study the coverage and lifetime when the dimensions of Gaussian dispersion (i.e., x, y) admit different Gaussian parameters (i.e., standard deviation, $sigma_x neqsigma_y$). We identify intrinsic properties of coverage/lifetime in terms of Gaussian distribution parameters, which is a fundamental issue in designing a WSN. Following the results obtained, we further determine the sensor deployment strategies for a WSN that could satisfy a predefined coverage and lifetime. Two deployment algorithms are developed based on using our analytical models and are shown to effectively increase the WSN lifetime.     

Efficient deployment quality analysis for intrusion detection in wireless sensor networks

The intrusion detection in a Wireless Sensor Network is defined as a mechanism to monitor and detect any intruder in a sensing area. The sensor deployment quality is a critical issue since it reflects the cost and detection capability of a wireless sensor network. The quality of deterministic deployment can be determined sufficiently by a rigorous analysis before the deployment. However, when random deployment is required, determining the deployment quality becomes challenging. In the intrusion detection application, it is necessary to define more precise measures of sensing range, transmission range, and node density that impact overall system performance. The major question is centred around the quality of intrusion detection in WSN, how we can guarantee that each point of the sensing area is covered by at least one sensor node, and what a sufficient condition to guarantee the network connectivity? In this paper, we propose an appropriate probabilistic model which provides the coverage and connectivity in k-sensing detection of a wireless sensor network. We have proved the capability of our approach using a geometric analysis and a probabilistic model.     

3D node deployment strategies prediction in wireless sensors network

ABSTRACT

3D Deployment plays a fundamental role in setting up efficient wireless sensor networks (WSNs) and IoT networks. In general, WSN are widely utilised in a set of real contexts such as monitoring smart houses and forest fires with parachuted sensors. This study focus on planned 3D deployment in which the sensor nodes must be accurately positioned at predetermined locations to optimise one or more design objectives under some given constraints. The purpose of planned deployment is to identify the type, the number, and the locations of nodes to optimise the coverage, the connectivity and the network lifetime. There have been a large number of studies that proposed algorithms resolving the premeditated problem of 3D deployment. The objective of this study is twofold. The first one is to present the complexity of 3D deployment and then detail the types of sensors, objectives, applications and recent research that concerns the strategy used to solve this problem. The second one is to present a comparative survey between the recent optimisation strategies solving the problem of 3D deployment in WSN. Based on our extensive review, we discuss the strengths and limitations of each proposed solution and compare them in terms of WSN design factors.     

A Novel Sensor Node Deployment using Low Discrepancy Sequences for WSN

The foremost challenge in designing Wireless Sensor Networks (WSNs) is careful node placement. Sensor Node placement is a one of the powerful optimization technique for accomplishing the anticipated goals. This paper focuses on categories of node deployment in WSN. The paper highlights various problems and identifies the different objectives in sensor node deployment. The paper proposes a novel node deployment strategy based on Quasi- random method of low-discrepancy sequences to increase the lifetime and the coverage of the network. The aim of the paper is to study how the node deployment affects the different QoS parameters such as packet delivery ratio, average energy consumption, delay, etc. with various multi-objective routing algorithms WSN. To validate the proposal simulation, results are presented in this paper. The paper concludes with the future outlook.     

A Novel Coverage Improved Deployment Strategy for Wireless Sensor Network

Coverage of the bounded region gets importance in Wireless Sensor Network (WSN). Area coverage is based on effective surface coverage with a minimum number of sensor nodes. Most of the researchers contemplate the coverage region of interest as a square and manifest the radio ranges as a circle. The area of a circle is much higher than the area of a square because of the perimeter. To utilize the advantage of the circle, the coverage region of interest is presumed as a circle for sensor node deployment. This paper proposes a novel coverage improved disc shape deployment strategy. Comparative analysis has been observed between circle and square regions of interest based on the cumulative number of sensor nodes required to cover the entire region. A new strategy named as disc shape deployment strategy is also proposed. Traditional hexagon and strip-based deployment strategies are compared with the disc shape deployment strategy. The simulation result shows that the circle shape coverage region of interest extremely reduces the required number of sensor nodes. The proposed deployment strategy provides desirable coverage, and it requires few more sensor nodes than hexagon shape deployment strategy.

     

Wireless Sensor Network Path Optimization Using Sensor Node Coverage Area Calculation Approach

The proposed work is based on the path optimization approach for wireless sensor network (WSN). Path optimization is achieved by using the NSG 2.1 Tool, TCL Script file and NS2 simulator to improve the quality of service (QoS). Path optimization approach finds best suitable path between sensor nodes of WSN. The routing approach is not only the solution to improve the quality but also improves the WSN performance. The node cardinally is taken under consideration using the ad-hoc on demand distance vector routing protocol mechanism. Ad hoc approach emphasize on sensor nodes coverage area performance along with simulation time. NSG 2.1 Tool calculates the sensor node packet data delivery speed which can facilitate inter-node communication successfully. An experimental result verified that the proposed design is the best possible method which can escape from slow network response while covering maximum sensor nodes. It achieves coverage support in sensor node deployment. The result outcomes show best path for transferring packet from one sensor node to another node. The coverage area of sensor node gives the percentage of average coverage ratio of each node with respect to the simulation time.

     

Position and hop-count assisted full coverage control in dense sensor networks

In recent years, wireless sensor networks (WSN’s) have gained much attention due to its various applications in military, environmental monitoring, industries and in many others. All these applications require some target field to be monitored by a group of sensor nodes. Hence, coverage becomes an important issue in WSN’s. This paper focuses on full coverage issue of WSN’s. Based on the idea of some existing and derived theorems, Position and Hop-count Assisted (PHA) algorithm is proposed. This algorithm provides full coverage of the target field, maintains network connectivity and tries to minimize the number of working sensor nodes. Algorithm works for communication range less than root three times of sensing range and it can be extended for arbitrary relation between communication range and sensing range. By using hop-count value, three-connectivity in the network is maintained. Also, neighbors information is used to create logical tree structure which can be utilized in routing, redundant data removal and in other areas. Simulation results show that PHA algorithm outperforms layered diffusion-based coverage control algorithm by providing better area coverage and activating fewer nodes.     

An energy efficient hole repair node scheduling algorithm for WSN

A sensor node in the wireless sensor network has limited energy and it normally cannot be replaced due to the random deployment, so how to prolong the network life time with limited energy while satisfying the coverage quality simultaneously becomes a crucial problem to solve for wireless sensor networks (WSN). In this work, we propose an energy efficient algorithm based on the sentinel scheme to reduce the sleeping node detection density by defining a new deep sleeping state for each sensor node. The average energy consumed by probing neighboring nodes is introduced as a factor to calculate the detection rate. In addition, after some theoretical analysis of the existence of coverage holes in WSN, a triangle coverage repair procedure is defined to repair coverage holes. Simulation results show that our proposed algorithm obtained better performance in terms of the coverage quality and network life time compared with some existing algorithms in the literature.     

Enhancing Coverage Using Weight Based Clustering in Wireless Sensor Networks

Energy conservation in wireless sensor networks (WSNs) is a fundamental issue. For certain surveillance applications in WSN, coverage lifetime is an important issue and this is related to energy consumption significantly. In order to handle these two interlinked aspects in WSN, a new scheme named Weight based Coverage Enhancing Protocol (WCEP) has been introduced. The WCEP aims to obtain longer full coverage and better network life time. The WCEP is based on assigning different weight values to certain governing parameters which are residual energy, overlapping degree, node density and degree of sensor node. These governing parameters affect the energy and coverage aspects predominantly. Further, these four different parameters are prime elements in cluster formation process and node scheduling mechanisms. The weight values help in selection of an optimal group of Cluster Heads and Cluster Members, which result in enhancement of complete coverage lifetime. The simulation results indicate that WCEP performs better in terms of energy consumption also. The enhancement of value 24% in full coverage lifetime has been obtained as compared to established existing techniques.

     

基于人工蜂群寻优算法的WSN中继节点布局方案

无线传感器网络(WSN)环境下,中继节点位置布局性能优劣是影响网络寿命的关键因素之一。目前,针对三维空间高密度WSN,缺少能够在硬件成本和连通性双重约束条件下提高网络寿命的中继节点位置布局方案。基于网格布局方式,提出了一种基于人工蜂群优化算法的中继节点布局方案(ABC-RNDS)。ABC-RNDS方案采用双层网络拓扑结构,首先使用最小生成树法构建骨干网络,再使用人工蜂群优化算法通过网络参数寻优和限制中继节点总数的方法实现网络寿命的延长。实验验证分析表明,在成本和连通性受约束的条件下,ABC-RNDS算法与传统方案相比能够显著提高网络寿命。