Unconstrained Face Detection of Multiple Humans Present in the Video

Accurate and fast localization of randomly deployed sensor nodes is needed for many applications in wireless sensor networks. Localization also benefits in recognizing the geographically area where an event took place. There is no meaning of any event information without the knowledge of its location coordinates. DV-Hop is one of the main range free localization technique, which estimates the position of nodes using distance vector. Particle swarm optimization is suitable for the localization issues because of its fast computing speed and high precision. To further reduce the positioning error, the traditional DV-Hop localization algorithm based on single objective optimization algorithm is converted into a multi objective optimization algorithm. In our proposed scheme, we have considered six different single objective functions and three different multi objective functions. In this paper, a multi objective particle swarm optimization based DV-Hop localization is proposed in 3-dimensional wireless sensor networks. The proposed functions has been evaluated on the basis of computation time, average localization error and localization error variance. The simulation results show that our proposed multi objective function performs better as compared to traditional single objective function.

     

Power efficient range-free localization algorithm for wireless sensor networks

Considering energy consumption, hardware requirements, and the need of high localization accuracy, we proposed a power efficient range-free localization algorithm for wireless sensor networks. In the proposed algorithm, anchor node communicates to unknown nodes only one time by which anchor nodes inform about their coordinates to unknown nodes. By calculating hop-size of anchor nodes at unknown nodes one complete communication between anchor node and unknown node is eliminated which drastically reduce the energy consumption of nodes. Further, unknown node refines estimated hop-size for better estimation of distance from the anchor nodes. Moreover, using average hop-size of anchor nodes, unknown node calculates distance from all anchor nodes. To reduce error propagation, involved in solving for location of unknown node, a new procedure is adopted. Further, unknown node upgrades its location by exploiting the obtained information in solving the system of equations. In mathematical analysis we prove that proposed algorithm has lesser propagation error than distance vector-hop (DV-Hop) and other considered improved DV-Hop algorithms. Simulation experiments show that our proposed algorithm has better localization performance, and is more computationally efficient than DV-Hop and other compared improved DV-Hop algorithms.     

Novel DV-Hop localization algorithm for wireless sensor networks

Many improved DV-Hop localization algorithm have been proposed to enhance the localization accuracy of DV-Hop algorithm for wireless sensor networks. These proposed improvements of DV-Hop also have some drawbacks in terms of time and energy consumption. In this paper, we propose Novel DV-Hop localization algorithm that provides efficient localization with lesser communication cost without requiring additional hardware. The proposed algorithm completely eliminates communication from one of the steps by calculating hop-size at unknown nodes. It significantly reduces time and energy consumption, which is an important improvement over DV-Hop—based algorithms. The algorithm also uses improvement term to refine the hop-size of anchor nodes. Furthermore, unconstrained optimization is used to achieve better localization accuracy by minimizing the error terms (ranging error) in the estimated distance between anchor node and unknown node. Log-normal shadowing path loss model is used to simulate the algorithms in a more realistic environment. Simulation results show that the performance of our proposed algorithm is better when compared with DV-Hop algorithm and improved DV-Hop—based algorithms in all considered scenarios.     

DV-Hop定位算法在随机传感器网络中的应用研究

DV-Hop节点定位算法是一种重要的与距离无关的定位算法。在各向同性的密集网络中,DV-Hop可以得到比较合理的定位精度,然而在随机分布的网络中,节点定位误差较大。该文根据DV-Hop算法定位过程,在平均每跳距离估计、未知节点到各参考节点之间距离的计算和节点位置估计方法等3个方面进行了改进,分析和仿真了不同改进措施和综合改进的定位性能。结果表明,与有关方法相比,该文提出的改进措施可极大地提高节点定位精度。此外,该文改进措施不改变DV-Hop算法的定位过程,因此不需要增加网络通信量和额外硬件支持,是理想的与距离无关算法。     

一种无需测距的无线传感器网络定位算法研究

定位信息是在无线传感器网络许多应用中不可缺少的,并且越来越重要。DV-Hop是一种典型的无需测距的定位算法。通过对DV-Hop算法的理论分析,找出其产生误差的主要原因,提出了一种改进的DV-Hop定位算法。增加锚节点数量及减少每条平均距离误差,有效提高节点定位精度。不用额外的硬件支持能够得到更接近实际位置的估算位置。仿真结果表明,提出的改进算法性能比原来的算法显著提升。     

An Advanced DV-Hop Localization Algorithm for Wireless Sensor Networks

In emerging sensor network applications, localization in wireless sensor network is a recent area of research. Requirement of its applications and availability of resources need feasible localization algorithm with lower cost and higher accuracy. In this paper, we propose an Advanced DV-Hop localization algorithm that reduces the localization error without requiring additional hardware and computational costs. The proposed algorithm uses the hop-size of the anchor (which knows its location) node, from which unknown node measures the distance. In the third step of Advanced DV-Hop algorithm, inherent error in the estimated distance between anchor and unknown node is reduced. To improve the localization accuracy, we use weighted least square algorithm. Furthermore, location of unknown nodes is refined by using extraneous information obtained by solving the equations. By mathematical analysis, we prove that Advanced DV-Hop algorithm has lesser correction factor in the distance between anchor and the unknown node compared with DV-Hop algorithm, improved DV-Hop algorithm (Chen et al. 2008) and improved DV-Hop algorithm (Chen et al. in IEICE Trans Fundam E91-A(8), 2008), which is cause of better location accuracy. Simulation results show that the performance of our proposed algorithm is superior to DV-Hop algorithm and improved DV-Hop algorithms in all considered scenarios.     

A fast handover protocol for 6LoWPAN wireless mobile sensor networks

Node localization is one of the most critical issues for wireless sensor networks, as many applications depend on the precise location of the sensor nodes. To attain precise location of nodes, an improved distance vector hop (IDV-Hop) algorithm using teaching learning based optimization (TLBO) has been proposed in this paper. In the proposed algorithm, hop sizes of the anchor nodes are modified by adding correction factor. The concept of collinearity is introduced to reduce location errors caused by anchor nodes which are collinear. For better positioning coverage, up-gradation of target nodes to assistant anchor nodes has been used in such a way that those target nodes are upgraded to assistant anchor nodes which have been localized in the first round of localization. For further improvement in localization accuracy, location of target nodes has been formulated as optimization problem and an efficient parameter free optimization technique viz. TLBO has been used. Simulation results show that the proposed algorithm is overall 47, 30 and 22% more accurate than DV-Hop, DV-Hop based on genetic algorithm (GADV-Hop) and IDV-Hop using particle swarm optimization algorithms respectively and achieves high positioning coverage with fast convergence.     

Improved 3-dimensional DV-hop localization algorithm based on information of nearby nodes

DV-Hop, a range-free localization algorithm, has been one of the most popular localization algorithm. It is easy and inexpensive to implement. Therefore, in the literature, many improved variants of this algorithm exist. However, poor location accuracy and higher power consumption by DV-Hop algorithm always open new avenues for research on this algorithm and makes it a favorite among the researchers. In this paper, we have proposed an Improved 3-Dimensional DV-Hop algorithm based on the information of nearby nodes (I3D-DVLAIN). In the algorithm, by calculating hopsize at the unknown nodes, we eliminate one communication among the nodes, which reduces power consumption in the network. The hopsize calculation and location estimation is done by using only the nearby anchor nodes, which minimizes the network usage and decreases the computational effort. For the selection of nearby anchor nodes, we introduce a new method. Further, for localization, a novel method is used for solving the system of distance equations that restricts propagation of inherent error in the distance and increases localization accuracy. Furthermore, by mathematically analyzing the propagation of error in solving the system of equations, we prove the superiority of I3D-DVLAIN over other compared algorithms. The results obtained through simulation and complexity analysis of the computation and communication further strengthens our observations about the superiority of the proposed algorithm.

     

针对虫洞攻击的无线传感器网络安全定位方法

节点定位技术是无线传感器网络的关键技术之一,是很多基于无线传感器网络的应用的基础。然而,无线传感器网络通常部署在无人值守的敌对环境中,攻击节点能够很容易地破坏网络中节点的定位过程。本文针对无线传感器网络中距离无关的定位技术,分析了虫洞攻击对DV-Hop定位过程的影响,提出了一种无线传感器网络中抵御虫洞攻击的DV-Hop安全定位方法。仿真结果表明所提出的安全定位方法能够有效降低虫洞攻击对DV-Hop定位过程的影响,验证了该方法的有效性。     

Cross-layer optimization using two-level dual decomposition in multi-flow ad-hoc networks

Localization is one of the most important issues in wireless sensor networks and designing accurate localization algorithms is a common challenge in recent researches. Among all localization algorithms, DV-Hop attracts more attention due to its simplicity; so, we use it as a basis for our localization algorithm in order to improve accuracy. The various evolutionary algorithms such as Genetic, Shuffled Frog Leaping and Particle Swarm Optimization are employed in different phases of the main DV-Hop localization algorithm. Simulation results prove that our proposed method decreases the localization error efficiently without additional hardware.     

Multiobjective optimization‐based DV‐hop localization using NSGA‐II algorithm for wireless sensor networks

Localization is one of the important requirements in wireless sensor networks for tracking and analyzing the sensor nodes. It helps in identifying the geographical area where an event occurred. The event information without its position information has no meaning. In range‐free localization techniques, DV‐hop is one of the main algorithm which estimates the position of nodes using distance vector algorithm. In this paper, a multiobjective DV‐hop localization based Non‐Sorting Genetic Algorithm‐II (NSGA‐II) is proposed in WSNs. Here, we consider six different single‐objective functions to make three multiobjective functions as the combination of two each. Localization techniques based on proposed multiobjective functions has been evaluated on the basis of average localization error and localization error variance. Simulation results demonstrate that the localization scheme based on proposed multiobjective functions can achieve good accuracy and efficiency as compared to state‐of‐the‐art single‐ and multiobjective GA DV‐hop localization scheme.     

A novel approach for designing delay efficient path for mobile sink in wireless sensor networks

In the recent years, the use of mobile sink has drawn enormous attention for data collection in wireless sensor networks (WSNs). Mobile sink is well known for solving hotspot or sinkhole problem. However, the design of an efficient path for mobile sink has tremendous impact on network lifetime and coverage in data collection process of WSNs. This is particularly an important issue for many critical applications of WSNs where data collection requires to be carried out in delay bound manner. In this paper, we propose a novel scheme for delay efficient trajectory design of a mobile sink in a cluster based WSN so that it can be used for critical applications without compromising the complete coverage of the target area. Given a set of gateways (cluster heads), our scheme determines a set of rendezvous points for designing path of the mobile sink for critical applications. The scheme is based on the Voronoi diagram. We also propose an efficient method for recovery of the orphan sensor nodes generated due to the failure of one or more cluster heads during data collection. We perform extensive simulations over the proposed algorithm and compare its results with existing algorithms to demonstrate the efficiency of the proposed algorithm in terms of network lifetime, path length, average waiting time, fault tolerance and adaptability etc. For the fault tolerance, we simulate the schemes using Weibull distribution and analyze their performances.     

改进的DV-HOP无线传感器网络定位算法

为了提高无需测距的距离矢量（DV-Hop）定位算法对随机分布网络节点的定位精度。在分析了DV-Hop算法实现思想的基础上,提出了一种锚节点整体均匀分布优化方案,对该算法节点跳数进行优化。另一方面,在双通信半径算法基础上提出了一种三通信半径改进方法,使得两节点之间的跳数与距离的关系更接近线性规律,最后结合两种改进方法,进行整体仿真。仿真结果表明,锚节点均匀分布的三通信半径DV-Hop算法比双通信半径DV-Hop算法提高定位精度约为7%~8%。     

基于改进DV-Hop的无线传感器网络节点定位算法

针对DV-Hop距算法定位误差大的难题,提出一种改进离估计误差,并利用DV-Hop的传感器节点定位算法。首先修正知节点与信标节DV-Hop算法对节点进行定位;然后对进V-Hop算法定位误差行校正,最后在Matlab 2012平台上对算法性能进行仿真分析。仿真结果表明,本文算法可以较好地克服DV-Hop算法存在的不足,提高了传感器节点的定位精度。     

Weighted Hyperbolic DV-Hop Positioning Node Localization Algorithm in WSNs

The localization of nodes plays a fundamental role in Wireless Sensor and Actors Networks (WSAN) identifying geographically where an event occurred, which facilitates timely response to this action. This article presents a performance evaluation of multi-hop localization range-free algorithms used in WSAN, such as Distance Vector Hop (DV-Hop), Improved DV-Hop (IDV-Hop), and the Weighted DV-Hop (WDV-Hop). In addition, we propose a new localization algorithm, merging WDV-Hop, with the weighted hyperbolic localization algorithm (WH), which includes weights to the correlation matrix of the estimated distances between the node of interest (NOI) and the reference nodes (RN) in order to improve accuracy and precision. As performance metrics, the accuracy, precision, and computational complexity are evaluated. The algorithms are evaluated in three scenarios where all nodes are randomly distributed in a given area, varying the number of RNs, the density of nodes in the network, and radio coverage of the nodes. The results show that in networks with 100 nodes, WDV-Hop outperforms the DV-Hop and IDV-Hop even if the number of RNs is reduced to 10. Moreover, our proposal shows an improvement in terms of accuracy and precision at the cost of increased computational complexity, specifically in the algorithm execution time, but without affecting the hardware cost or power consumption.     

MANCL: a multi‐anchor nodes collaborative localization algorithm for underwater acoustic sensor networks

Localization is an essential and major issue for underwater acoustic sensor networks (UASNs). Almost all the applications in UASNs are closely related to the locations of sensors. In this paper, we propose a multi‐anchor nodes collaborative localization (MANCL) algorithm, a three‐dimensional (3D) localization scheme using anchor nodes and upgrade anchor nodes within two hops for UASNs. The MANCL algorithm divides the whole localization process into four sub‐processes: unknown node localization process, iterative location estimation process, improved 3D Euclidean distance estimation process, and 3D DV‐hop distance estimation process based on two‐hop anchor nodes. In the third sub‐process, we propose a communication mechanism and a vote mechanism to determine the temporary coordinates of unknown nodes. In the fourth sub‐process, we use two‐hop anchor nodes to help localize unknown nodes. We also evaluate and compare the proposed algorithm with a large‐scale localization algorithm through simulations. Results show that the proposed MANCL algorithm can perform better with regard to localization ratio, average localization error, and energy consumption in UASNs. Copyright © 2014 John Wiley & Sons, Ltd.     

水下光无线传感器网络的连接性分析与定位技术

针对水下光无线传感器网络(UOWSN)节点的传输范围受限和间歇性连接的问题,利用多跳通信扩大传输范围来增强网络连接性,提出一种网络节点定位算法.首先,将UOWSN建模为三维(3D)随机缩放模型图,并根据网络节点数、通信范围以及光发散角推导了该模型下网络节点的连接性概率表达式;然后,利用接收信号强度(RSS)定位算法修正...     

一种基于误差距离加权与跳段算法选择的遗传优化DV-Hop定位算法

针对Distance Vector-Hop (DV-Hop) 定位算法存在较大定位误差的问题,该文提出了一种基于误差距离加权与跳段算法选择的遗传优化DV-Hop定位算法,即WSGDV-Hop定位算法。改进算法用基于误差与距离的权值处理锚节点的平均每跳距离;根据判断的位置关系选择适合的跳段距离计算方法;用改进的遗传算法优化未知节点坐标。仿真结果表明,WSGDV-Hop定位算法的性能明显优于Distance Vector-Hop (DV-Hop) 定位算法,减小了节点定位误差、提高了算法定位精度。     

WSN中一种改进的DV-Hop节点定位算法

DV-Hop算法是一种经典的距离无关的无线传感器网络节点定位算法.详细分析了DV-Hop算法的定位过程,针对其局限性提出一种改进的DV-Hop算法.该改进算法在传统DV-Hop算法的第一阶段采用分簇策略以减小通信开销和分组冲突概率,并且用拟牛顿优化算法代替传统的最小二乘法计算节点位置,最后用Matlab7.0进行仿真....     

一种具有连续跳数值的三维DV-Hop改进算法

设计精确的定位算法是无线传感器网络（Wireless Sensor Networks,WSNs）的研究热点.针对DV-Hop（Distance Vector-Hop）定位算法中节点间距离估计误差较大导致定位不精确的问题,提出了一种具有连续跳数值的三维DV-Hop改进算法.探究了邻居节点间的距离与相应节点位置和通信半径构成的相交球体体积之间的关系,提出了连续跳数值的定义,并通过参数修正给出了其计算方法.通过仿真实验探究了网络环境对参数的影响并确定了参数的取值,使用连续跳数值代替DV-Hop算法中的跳数来降低节点间距离估计误差.仿真实验表明,该算法在不增加算法复杂度以及额外硬件的情况下有效地降低了定位误差.