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.

     

Impact of Interference on Coverage in Wireless Sensor Networks

The quality of surveillance is dependent on the sensing coverage of a wireless sensor network. In the present paper, we examine how interference affects the coverage of a wireless sensor network. The coverage fraction and required number of sensors for randomly deployed and well-planned deployed wireless sensor networks in the presence of interferers are computed. The required number of sensors to achieve higher level of coverage increases drastically for randomly distributed sensor nodes where the interference effect is high. In the case of well-planned distributed sensor network, required sensors increases linearly as interference effects become more pronounced. Algorithms for computing the required number of sensors to obtain the desired level of coverage in the presence of non-uniform interference is presented. The simulation results suggest that the coverage per subregion and coverage per sensor approaches towards, the improvement achieved is constant. The sensor saving ratio is independent of the level of the desired coverage provided the coverage per subregion is larger than or equal to the coverage per sensor.     

无线传感器网络中基于区域通信覆盖的节点定位投放算法

针对无线传感器网络中传感器节点投放分布对投放区域有效通信信号覆盖的影响,该文提出了一种基于通信覆盖的分布式投放概率覆盖(DDCP)算法。在保证投放精度的前提下,该算法根据传感器节点在投放区域中位置的不确定性以及信号衰减特性,建立信号覆盖模型,并通过概率优化获取传感器节点的最佳投放位置和投放数目。这样改善了区域通信覆盖,同时提高了投放效率和节省网络资源。通过仿真比较了在不同定位投放方法下的各相关性数据,验证了该算法实现高效投放的优越性和正确性。     

人工鱼群优化的方向传感器覆盖增强

为提高无线多媒体传感器网络区域覆盖率,提出了人工鱼群优化的覆盖增强算法,算法基于三维方向传感器感知模型,优化网络传感器方向角度值,减少重叠覆盖以提升网络覆盖率。仿真实验表明该方法能有效增强网络覆盖率,并就传感器参数对覆盖率影响进行分析,分析结果表明优化后的网络覆盖率更加接近理想覆盖率。     

三维水下传感器网络覆盖优化算法

针对三维水下传感器网络模型,对水下传感器网络的覆盖优化问题进行了描述,提出利用虚拟势场算法CAT（coverage-enhancing algorithm for three-dimensional sensor networks）调整水下传感器节点与浮标节点间缆绳的距离,逐渐消除网络中的感知重叠区域和覆盖盲区,进而实现整个水下传感器网络覆盖增强.在仿真实验中,通过CAT算法与ETG算法的比较,验证了CAT算法的有效性.     

分布式无线感知网络节点部署算法研究

在无线感知网络节点部署中,目标区域的覆盖率大小对信号检测的效果具有重要的意义,通过智能优化算法来提高区域覆盖率已成为当前无线感知网络节点部署领域的研究热点之一。为了提高分布式无线感知网络对目标区域内的重点区域的覆盖率和减少冗余感知节点的投放,论文提出了一种分布式无线感知网络节点部署算法。该算法首先通过随机部署满足连通性的少量感知节点后初次工作来定位和估计出重点区域,然后将估计出的重点区域融入到粒子群算法的目标函数和粒子更新方程中实现对感知节点的重新部署,从而更好的优化了重点区域的覆盖率和减少冗余感知节点数量。仿真结果表明,与标准粒子群算法及其他优化算法相比,论文所研究的算法有更高的覆盖率和更低的迭代次数。      

基于Clifford代数传感器网络覆盖理论的 平面目标覆盖分析

 平面目标覆盖问题是传感器网络对目标覆盖的基本问题之一.本文提出了基于Clifford代数传感器网络覆盖理论的平面目标覆盖分析方法,利用Clifford几何代数表示平面目标,并给出了传感器网络中节点对平面目标的覆盖率计算方法,通过该方法,提出基于平面目标的传感器网络最大间隙路径算法,通过实验验证其有效性和实用性.     

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.

     

无线传感器网络中覆盖问题的研究

简要介绍了无线传感器网络体系结构、特点和应用领域.针对无线传感器网络节点覆盖问题进行了研究,提出了基于最短路径的覆盖算法,并给出了仿真结果.     

An Energy Efficient Barrier Coverage Algorithm for Wireless Sensor Networks

Intrusion detection is one of the most important applications of wireless sensor networks. When mobile objects are entering into the boundary of a sensor field or are moving cross the sensor field, they should be detected by the scattered sensor nodes before they pierce through the field of sensor (barrier coverage). In this paper, we propose an energy efficient scheduling method based on learning automata, in which each node is equipped with a learning automaton, which helps the node to select best node to guarantee barrier coverage, at any given time. To apply our method, we used coverage graph of deployed networks and learning automata of each node operates based on nodes that located in adjacency of current node. Our algorithm tries to select minimum number of required nodes to monitor barriers in deployed network. To investigate the efficiency of the proposed barrier coverage algorithm several computer simulation experiments are conducted. Numerical results show the superiority of the proposed method over the existing methods in term of the network lifetime and our proposed algorithm can operate very close to optimal method.     

无线传感器网络的覆盖优化机制研究

如何实现最优覆盖是无线传感器组网的一个基本问题.文章分析了传感器覆盖问题的背景,给出了节点调度方案的主要方法和技术原理,探讨了基于网络能量高效的覆盖优化与网络连通性之间的关系,重点阐述了实现区域覆盖和点覆盖的机制.对于覆盖薄弱地区,文章提出了采用分簇方式将覆盖地区划分成许多子区域或簇,用动态移动修复机制提供细粒度的网络监测与覆盖控制.文章认为调度传感器节点在休眠和活动模式之间进行切换,是一种重要节能方法;对于资源受限且拓扑动态变化的无线传感器网络,宜采用分布式和局部化的覆盖控制协议和算法.     

节点位置无关的无线传感器网络连通性部分覆盖协议

提出了一种节点位置无关的连通性覆盖协议。协议首先利用了随机部署网络在已知监测区域大小和节点感知范围情况下,应用期望的覆盖质量与所需的工作节点数量之间的数学关系,随机选取工作节点满足应用需求;然后根据每个节点距基站最小跳数,执行Add-On规则,增加额外节点保证网络连通。实验结果表明,EECPC协议能够在较长时间内能量有效地提供满足应用要求的覆盖率,而且保证网络连通。     

基于融合的无线传感器网络k-集覆盖的分布式算法

当节点采用概率感知模型且融合多个节点的数据进行联合感知的情况下,提出了一个新的无线传感器网络的覆盖优化问题:基于融合的k-集覆盖优化问题.首先,将优化问题建模为融合覆盖博弈,证明该博弈是势博弈,且势函数与优化目标函数一致,因此,最优解是一个纯策略Nash均衡解.其次,给出了节点间融合覆盖效用独立的判定条件,进而分别提出同步、异步控制的、基于局部信息的、分布式的覆盖优化算法,证明了算法收敛到纯策略Nash均衡.最后,仿真实验结果表明,当算法收敛时,网络能达到高的覆盖率且具有好的覆盖稳定性.     

Distributed Sensor Networks Deployment Using Fuzzy Logic Systems

The effectiveness of distributed wireless sensor networks highly depends on the sensor deployment scheme. Given a finite number of sensors, optimizing the sensor deployment will provide sufficient sensor coverage and ameliorate the quality of communications. In this paper, we apply fuzzy logic systems to optimize the sensor placement after an initial random deployment. We use the outage probability due to co-channel interference to evaluate the communication quality. Fenton–Wilkinson method is applied to approximate the sum of log-normal random variables. Our algorithm is compared against the existing distributed self-spreading algorithm. Simulation results show that our approach achieves faster and stabler deployment and maximizes the sensor coverage with less energy consumption. Outage probability, as a measure of communication quality gets effectively decreased in our algorithm but it was not taken into consideration in the distributed self-spreading algorithm.     

Coverage and Connectivity-Based 3D Wireless Sensor Deployment Optimization

The wireless sensor network technology of Internet of Things (IoT) senses, collects and processes the data from its interconnected intelligent sensors to the base station. These sensors help the IoT to understand the environmental change and respond towards it. Thus sensor placement is a crucial device of IoT for efficient coverage and connectivity in the network. Many existing works focus on optimal sensor placement for two dimensional terrain but in various real-time applications sensors are often deployed over three-dimensional ambience. Therefore, this paper proposes a vertex coloring based sensor deployment algorithm for 3D terrain to determine the sensor requirement and its optimal spot and to obtain 100% target coverage. Further, the quality of the connectivity of sensors in the network is determined using Breadth first search algorithm. The results obtained from the proposed algorithm reveal that it provides efficient coverage and connectivity when compared with the existing methods.

     

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。     

无线传感器网络的WPCS覆盖策略

延长无线传感器网络生存时间的有效方法是让冗余节点进入休眠状态。而现有研究多是基于传感器感知模型为圆形的假设前提。该文集中讨论传感器感知模型非圆时,覆盖与连通性之间的联系,并提出适用性更广的WPCS(Well-Proportioned Coverage Strategy)覆盖策略。WPCS覆盖策略以最小化重叠面积为准则,其目的是最大化网络生存时间。仿真实验表明,WPCS性能优于CCP(Coverage Configuration Protocol),且具有一般性,并能很好地减少工作传感器数目,延长网络寿命。     

Sensor allocation in diverse environments

Sensor coverage varies with location due to factors such as weather, terrain, and obstacles. If a field can be partitioned into zones of homogeneous sensing areas, then the area covered by a random deployment of sensors can be optimized by controlling the number of sensors deployed in each zone. This paper provides formulas to directly calculate the optimal sensor partition in runtime asymptotically equal to the number of zones; to determine the minimum sensor count required to achieve a specific coverage threshold; and to bound the maximum increase in coverage over a strategy oblivious to differences in sensing areas. Results show that this bound is no greater than 13% for a field with two zones. While the analytical solutions assume that each zone is covered independently, sensors are allowed to affect neighboring zones in simulations. Nevertheless, the simulation results support the optimality of the solutions.     

Maximum Lifetime Target Coverage in Wireless Sensor Networks

Wireless Personal Communications - The challenge in the deployment of wireless sensor networks is to ensure the coverage of targets with high energy efficiency, particularly when coverage and...     

Connectivity-Preserved and Force-Based Deployment Scheme for Mobile Sensor Network

This paper considers the self-deployment of wireless sensor networks. Conventional deployment problem usually focuses on enhancing the coverage, while the conditions for network connectivity are largely simplified. We present a deployment scheme to enhance the coverage while keeping the network connected at each step of the deployment. Our scheme contains two parts. The coverage improvement part proposes an improved force-based mechanism. A limit is provided to determine the sensors which should attractive each other, so the wasted overlap and communication resource can be reduced. The connectivity preservation part provides constrains for the movement distance of each sensor, in order to take account of both connectivity and coverage enhancement. Some simulation results are presented to show the connectivity preservation and coverage maximization properties of our mechanism.