共查询到15条相似文献,搜索用时 15 毫秒
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事件监测是无线传感器网络的一种重要应用。针对该应用中软故障节点提供的错误数据会降低监测的准确性的问题,提出了一种分布式的容错事件边界检测算法。节点只需与邻节点交换一次传感数据,通过简单地计算识别故障;正常的事件节点利用统计比较的方法判断其是否处于事件边界,边界宽度可根据网络用户的要求调节。该算法执行时所需的通信量小,计算复杂度低,时延小,对大规模网络具有很好的可扩展性。仿真结果表明即使节点故障率很高,应用该算法仍可以获得很好的检测效果。 相似文献
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研究了一维和二维无线传感器网络(WSN)在空间信号源相关条件下的最优传感器配置方法。WSN通过分布的传感器节点得到与位置相关的测量数据, 然后恢复出具有空间相关性的信号。WSN重建信号的基本准则是使重建信号和原信号在单位区域能量恒定条件下的均方误差(MSE)最小。研究了在具有有限节点的小网络和具有有限节点密度的大网络中传感器节点密度和空间数据相关性对网络性能的影响, 定量分析了各种不同网络参数间的相互作用及其对网络性能的影响。其结果为实用WSN的设计提供了基础。 相似文献
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由于无线传感器网络中可能会出现覆盖漏洞,导致网络无法提供高质量的数据,所以需要检测边界节点以准确找到覆盖漏洞进行修复。已有研究大多是通过传感器的坐标或者依据大量节点信息进行检测, 现提出算法通过检测每个节点的邻居节点是否能形成包围检测节点的闭合环来判别当前节点是否为边界节点。该算法使得节点能够仅基于小邻域的信息自主地决定它是否是边界节点,使其适用于节点分布不均匀的网络中。仿真实验验证了该算法在识别准确率、降低通信量等方面的有效性。 相似文献
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无线传感器网络节点部署在复杂环境时,节点间相关性无法通过节点间距离来准确描述.为了克服该缺陷,本文提出了数据密度相关度公式.该公式反映了节点数据的ε邻域内数据的聚集程度,也反映了该节点数据相对其ε邻域内数据的相对位置.同时,将数据密度相关度公式应用到代表式数据融合算法中,提出了数据密度相关度融合算法.该融合算法得到的相关区域具有相关区域内节点数据相关度大,相关区域问节点数据相关度小的优点.仿真实验结果表明了该融合算法在数据准确性和能耗方面较基于α-局部空间数据融合算法和基于皮尔森相关系数的数据融合算法优越. 相似文献
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AbstractIn wireless sensor network, data aggregation can cause increased transmission overhead, failures, data loss and security-related issues. Earlier works did not concentrate on both fault management and loss recovery issues. In order to overcome these drawbacks, in this paper, a reliable data aggregation scheme is proposed that uses support vector machine (SVM) for performing failure detection and loss recovery. Initially, a group head, selected based on node connectivity, splits the nodes into clusters based on their location information. In each cluster, the cluster member with maximum node connectivity is chosen as the cluster head. When the aggregator receives data from the source, it identifies node failures in the received data by classifying the faulty data using SVM. Furthermore, a reserve node-based fault recovery mechanism is developed to prevent data loss. Through simulations, we show that the proposed technique minimises the transmission overhead and increases reliability. 相似文献
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All properties of mobile wireless sensor networks (MWSNs) are inherited from static wireless sensor networks (WSNs) and meanwhile have their own uniqueness and node mobility. Sensor nodes in these networks monitor different regions of an area of interest and collectively present a global overview of monitored activities. Since failure of a sensor node leads to loss of connectivity, it may cause a partitioning of the network. Adding mobility to WSNs can significantly increase the capability of the WSN by making it resilient to failures, reactive to events, and able to support disparate missions with a common set of sensor nodes. In this paper, we propose a new algorithm based on the divide-and-conquer approach, in which the whole region is divided into sub-regions and in each sub-region the minimum connected sensor cover set is selected through energy-aware selection method. Also, we propose a new technique for mobility assisted minimum connected sensor cover considering the network energy. We provide performance metrics to analyze the performance of our approach and the simulation results clearly indicate the benefits of our new approach in terms of energy consumption, communication complexity, and number of active nodes over existing algorithms. 相似文献
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Ahmed M. KhedrAuthor Vitae Walid OsamyAuthor Vitae 《Journal of Parallel and Distributed Computing》2011,71(10):1318-1326
Target tracking is an important sensing application of wireless sensor networks. In these networks, energy, computing power, and communication bandwidth are scarce. We have considered a random heterogeneous wireless sensor network, which has several powerful nodes for data aggregation/relay and large number of energy-constrained sensor nodes that are deployed randomly to cover a given target area. In this paper, a cooperative approach to detect and monitor the path of a moving object using a minimum subset of nodes while maintaining coverage and network connectivity is proposed. It is tested extensively in a simulation environment and compared with other existing methods. The results of our experiments clearly indicate the benefits of our new approach in terms of energy consumption. 相似文献
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为提高无线传感器/执行器网络(WSAN)的可靠性,提出一种基于遗传算法(GA)的WSAN故障检测滤波器的优化设计方法。在系统建模时将无线网络传输延迟对网络控制系统的影响建模为一种系统扰动噪声,将由敏感度和鲁棒性构成的复合优化指标作为故障检测滤波器的优化目标函数,即适应度函数。同时根据优化目标在自动控制系统中的数值特性,选择与之相适应的实数编码、均匀变异和算术交叉等处理方法,以期在加快收敛速度的同时也兼顾计算结果的精确度。所提的优化滤波器设计,不仅能抑制滤波器信号中的噪声分量,而且能放大故障信号。最后,通过Matlab/OMNET++的仿真平台验证了这一设计的有效性。 相似文献
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In this article, an improved negative selection algorithm (INSA) has been proposed to identify faulty sensor nodes in wireless sensor network (WSN) and then the faults are classified into soft permanent, soft intermittent, and soft transient fault using the support vector machine technique. The performance metrics such as fault detection accuracy, false alarm rate, false positive rate, diagnosis latency (DL), energy consumption, fault classification accuracy (FCA), and false classification rate (FCR) are used to evaluate the performance of the proposed INSA. The simulation result shows that the INSA gives better result as compared to the existing algorithms in terms of performance metrics. The fault classification performance is measured by FCA and FCR. It has also seen that the proposed algorithm gives less DL and consumes less energy than that of existing algorithms proposed by Mohapatra et al, Zhang et al, and Panda et al for WSN. 相似文献
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《Computers & Electrical Engineering》2014,40(7):2089-2100
Mobile sink trajectory plays a pivotal role for network coverage, data collection and data dissemination in wireless sensor networks. Considering this, we propose a novel approach for mobile sink trajectory in wireless sensor networks. Our proposed approach is based on Hilbert Space Filling Curve, however, the proposed approach is different from the previous work in a sense that the curve order changes according to node density. In this paper, we investigate the mobile sink trajectory based on Hilbert Curve Order which depends upon the size of the network. Second, we calculate the Hilbert Curve Order based on node density to re-dimension the mobile sink trajectory. Finally, we perform extensive simulations to evaluate the effectiveness of proposed approach in terms of network coverage and scalability. Simulation results confirm that our proposed approach outperforms with size based Hilbert Curve in terms of network coverage, packet delivery ratio and average energy consumption. 相似文献
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Understanding optimal data gathering in the energy and latency domains of a wireless sensor network 总被引:3,自引:0,他引:3
The problem of optimal data gathering in wireless sensor networks (WSNs) is addressed by means of optimization techniques. The goal of this work is to lay the foundations to develop algorithms and techniques that minimize the data gathering latency and at the same time balance the energy consumption among the nodes, so as to maximize the network lifetime. Following an incremental-complexity approach, several mathematical programming problems are proposed with focus on different network performance metrics. First, the static routing problem is formulated for large and dense WSNs. Optimal data-gathering trees are analyzed and the effects of several sensor capabilities and constraints are discussed, e.g., radio power constraints, energy consumption model, and data aggregation functionalities. Then, dynamic re-routing and scheduling are considered. An accurate network model is proposed that captures the tradeoff between the data gathering latency and the energy consumption, by modeling the interactions among the routing, medium access control and physical layers.For each problem, extensive simulation results are provided. The proposed models provide a deeper insight into the problem of timely and energy efficient data gathering. Useful guidelines for the design of efficient WSNs are derived and discussed. 相似文献