无线传感器网络节点自调度冗余覆盖算法

对于能量受限的无线传感器网络,延长网络存活的时间很关键。针对这个问题,提出了一种基于能量均衡的传感器节点自调度冗余覆盖协议（SRCP）,通过仿真实验对该算法的有关性能进行了评价,性能评价表明：这种算法能有效使用节点能力,延长网络存活时间。     

无线传感器网络动态覆盖的CVT算法

覆盖控制是无线传感器网络中的基本问题之一,动态覆盖问题又在很多领域有其独到的应用价值。为了更好地实现动态覆盖,基于集中式Voronoi网格细分（ CVT）理论,结合Lloyd算法,提出了一种无线传感器网络动态覆盖算法,通过调整目标覆盖区域几何边界,协同调度无线传感器网络节点,从而实现目标区域无线传感器网络动态覆盖。在仿真中,进行了正方形、正方形—圆形障碍静态边界区域覆盖实验和正方形—长方形目标区域、正方形—十字形目标区域、正方形—H形目标区域动态边界覆盖实验,验证了控制算法的有效性,并对不同目标覆盖区域形状、节点数量、覆盖程度、覆盖效率进行了分析。     

基于激素调节的传感器网络覆盖算法*

人体内环境的平衡是由各种激素的相互作用来协同调节和控制的,根据抽象出的激素作用机理,提出了一种基于激素调节的传感器网络覆盖算法(HCA),该算法是完全分布式的,节能的传感器网络覆盖算法,算法中节点状态(sleep或active)的选择通过激素来调节和控制,即通过给邻居节点发送激活荷尔蒙或抑制荷尔蒙来刺激或抑制邻居节点成为active状态。仿真实验表明,与DELIC和UC算法相比,该算法既能有效地保证区域覆盖,又可以使得active状态的节点尽可能少。     

A novel adaptive cooperative location algorithm for wireless sensor networks

To overcome the disadvantages of the location algorithm based on received signal strength indication(RSSI) in the existing wireless sensor networks(WSNs),a novel adaptive cooperative location algorithm is proposed.To tolerate some minor errors in the information of node position,a reference anchor node is employed.On the other hand,Dixon method is used to remove the outliers of RSSI,the standard deviation threshold of RSSI and the learning model are put forward to reduce the ranging error of RSSI and improve the positioning precision effectively.Simulations are run to evaluate the performance of the algorithm.The results show that the proposed algorithm offers more precise location and better stability and robustness.     

一种基于遗传算法的无线传感器网络覆盖模型

在无线传感器网络中,传感器节点的分布通常具有随机性和密集性,监测区域会出现覆盖盲区或者覆盖重叠.为此,推导出了无线传感器最优覆盖模型计算最少节点个数的公式,对遗传算法中的适应度函数公式做了改进,将多重覆盖率和覆盖率的组合作为适应度函数.根据遗传算法的相关内容和流程图,利用遗传算法对覆盖策略做了仿真模拟,证明了所选用的方法的正确和优越性.     

自适应半径调整的无线传感器网络覆盖算法

针对随机分布的无线传感器网络中节点分布不均匀造成的覆盖冗余,以及同时存在的覆盖空洞,提出了一种自适应半径调整无线传感器网络覆盖算法,通过阈值判断监测区域内传感器节点密度,根据监测区域内传感器节点疏密程度,利用节点半径步长系数对监测区域内节点半径进行自适应调整,建立无线传感器节点发射功率与节点发射半径的模型,计算无线传感器发射功率,通过实验和仿真,表明上述方法能够保证网络覆盖率的基础上减少无线传感器网络总功耗,提高网络寿命.     

无线传感器网络中一种能量有效k度覆盖算法

覆盖率是衡量无线传感器网络性能的重要指标之一。在对目标节点进行k覆盖的过程中,会出现大量数据冗余迫使网络出现拥塞的现象,导致网络通信能力和覆盖能力降低、网络能量快速消耗等问题。为此,提出了一种能量有效[k]度覆盖算法（Energy Efficient k_degree Coverage Algorithm,EEKCA）。该算法利用节点之间的位置关系构造出覆盖网络模型,通过分析网络模型给出监测区域内节点覆盖期望值及对整个监测区域覆盖所需最少节点数量的求解过程;在能耗方面,给出了工作节点和邻居节点之间的能量转换函数比例关系,利用函数比例关系完成低能量节点的调度,进而达到全网能量平衡,优化了网络资源。最后,仿真实验结果表明,该算法不仅可以提高网络覆盖质量,还可有效抑制节点能量快速消耗,从而延长网络生存周期。     

能量有效的三维无线传感器网络覆盖算法

无线传感器网络通常都工作在三维空间中,因此需要三维空间中的覆盖算法。结合三维空间的特点对二维空间内的覆盖算法SGA进行改进,在此基础上提出一种三维空间的覆盖算法——SSG算法,该覆盖算法的优点是不依赖于节点位置信息,并通过仿真实验给出了覆盖质量分析。     

A novel energy-efficient clustering protocol with area coverage awareness for wireless sensor networks

Coverage is a key metric in evaluating the monitoring capacity and quality of services in wireless sensor networks. The energy consumption of self-contained sensors is also a challenging problem for energy-efficient use while still achieving better coverage performance. Although techniques have been developed to mitigate the problem of area coverage, particularly together with efficient clustering methods, none focuses intensively on the sensor activation stage, which is used to maintain coverage while optimizing energy usage. In this research, we thus propose a cover set to find the minimum set of sensors that completely cover the sensing ranges within an interest area as a criterion for sensor activation. Our main goal is to select an optimal number of active sensors considering residual energy and the cover set and to keep alive the important sensors for the sensing coverage task as long as possible. Additionally, this research proposes an area coverage-aware clustering protocol (ACACP) with energy consumption optimization with respect to the activation sensor, network clustering, and multi-hop communication to improve overall network lifetime while preserving coverage. Throughout the intensive simulation, given a diversity of deployments with scalability concern, the results demonstrate the effectiveness of ACACP when compared with other competitive approaches such as ECDC and DECAR, including state-of-the-art clustering protocols such as LEACH, in terms of coverage ratio and overall network lifetime.     

A novel differential evolution based clustering algorithm for wireless sensor networks

Clustering is an efficient topology control method which balances the traffic load of the sensor nodes and improves the overall scalability and the life time of the wireless sensor networks (WSNs). However, in a cluster based WSN, the cluster heads (CHs) consume more energy due to extra work load of receiving the sensed data, data aggregation and transmission of aggregated data to the base station. Moreover, improper formation of clusters can make some CHs overloaded with high number of sensor nodes. This overload may lead to quick death of the CHs and thus partitions the network and thereby degrade the overall performance of the WSN. It is worthwhile to note that the computational complexity of finding optimum cluster for a large scale WSN is very high by a brute force approach. In this paper, we propose a novel differential evolution (DE) based clustering algorithm for WSNs to prolong lifetime of the network by preventing faster death of the highly loaded CHs. We incorporate a local improvement phase to the traditional DE for faster convergence and better performance of our proposed algorithm. We perform extensive simulation of the proposed algorithm. The experimental results demonstrate the efficiency of the proposed algorithm.     

无位置信息的无线传感器网络漏洞发现算法*

无线传感器网络广泛应用的前提是能够检监测目标区域特定事件的发生。而节点能量受限、难补给的特点导致监测性能难以保证,造成监测盲区出现。针对无线传感器网络节点的地理位置信息未知的情况进行了研究,提出覆盖漏洞发现算法CHDA (Coverage Holes Discovery Algorithm),在以节点为极点建立的极坐标中计算出相邻节点的相对位置信息和该节点被其邻居节点覆盖的边缘弧的信息,并且根据节点的单纯覆盖弧序列的定义计算出节点被其邻居节点覆盖的单纯覆盖弧序列,从而得到网络中的覆盖漏洞。覆盖漏洞的发现克服的地理位置信息未知的限制,为漏洞的修补提供了必要的前提条件进而保证传感器网络的覆盖率。     

一种混合无线传感器网络内覆盖洞修补的分布式启发算法

首先对最小化最大移动开销移动传感器分布式算法设计进行了分析, 并指出在分布式条件下难以对此类算法中的输出分派移动传感器的最大开销进行限制, 随后提出了一种分布式启发算法。该算法将移动传感器和覆盖洞视为节点, 在节点和节点的邻居间通过有限数量消息实现匹配。仿真结果显示, 算法可实现最高达到85%的覆盖洞修补率以及较低的移动传感器最大移动开销, 使其更能适用于实际无线传感器网络环境。     

Node localization algorithm for wireless sensor networks using compressive sensing theory

In recent years, localization has been recognized as an important supporting technology for wireless sensor networks (WSNs). Along with the increase in WSN indoor applications, indoor localization has become a hot research topic and many localization algorithms have been studied. Among these algorithms, the localization method based on compressive sensing theory emerges as a popular approach to indoor localization. In this approach, the nodes are sparse when compared to the number of grids utilized to represent the locations of the nodes, so the locations are considered as sparse signal and can be reconstructed using the compressive sensing techniques. The localization problem is formulated as the sparse reconstruction of sparsifying matrix which is comprised of measurement of received signal at grids. In order to improve the localization accuracy and meet the real-time requirement of localization applications in large indoor area, an indoor localization algorithm based on dynamic measurement compressive sensing for wireless sensor networks is proposed. Using the bounding-box method, we firstly identify a potential area that possesses the independent features. Instead of using the entire node deployment region as the measurement area, our method can decrease the number of meshing and also the dimension of measurement matrix. Meanwhile, we assume that only the anchor nodes which have communication relationship with the unknown nodes can be used as the measuring nodes; the measurement matrix of unknown nodes which need to be localized can be dynamically constructed according to the potential area and the received anchor node information, and the maximum number of measurement is decided by the number of grids of potential area. The proposed algorithm can mitigate the measurement redundancy and improve the real-time feature. Simulation results indicate that the proposed algorithm can reduce the time complexity and also maintain good localization accuracy and localization efficiency.     

Connectivity preserving localized coverage algorithm for area monitoring using wireless sensor networks

Efficient network coverage and connectivity are the requisites for most Wireless Sensor Network (WSN) deployments, particularly those concerned with area monitoring. Due to the resource constraints of the sensor nodes, redundancy of coverage area must be reduced for effective utilization of the available resources. If two nodes have the same coverage area in their active state, and if both the nodes are activated simultaneously, it leads to redundancy in network and wastage of precious sensor resources. In this paper, we address the problem of network coverage and connectivity and propose an efficient solution to maintain coverage, while preserving the connectivity of the network. The proposed solution aims to cover the area of interest (AOI), while minimizing the count of the active sensor nodes. The overlap region of two sensor nodes varies with the distance between the nodes. If the distance between two sensor nodes is maximized, the overall coverage area of these nodes will also be maximized. Also, to preserve the connectivity of the network, each sensor node must be in the communication range of at least one other node. Results of simulation of the proposed solution indicate up to 95% coverage of the area, while consuming very less energy of 9.44 J per unit time in the network, simulated in an area of 2500 m².     

一种基于地理位置的无线传感器网络分簇路由算法

针对大规模无线传感器网络,提出了一种基于地理位置的双基站分簇路由算法。该算法在网络覆盖区域边缘设置两个基站,按照地理位置将区域划分为若干均匀分布网格。每个网格根据节点剩余能量和到网格内其它节点平均距离远近选择簇头。通过仿真分析,证明该算法能减少网络能耗,延长网络生存时间。     

A testbed for coverage control using mixed wireless sensor networks

Wireless sensor networks (WSNs) is a relatively new technology that has been proposed for several applications including wide area monitoring. Such applications may include stationary or mobile sensor platforms or they may include several stationary and some mobile-robotic sensor nodes that can move in the area in order to achieve certain objectives, e.g., monitor areas that are not adequately covered or assist in the transfer of data to prevent the energy depletion of certain critical nodes. Such networks that consist of both stationary and mobile nodes are referred to as mixed WSNs. This paper presents the development of an experimental testbed for mixed WSNs consisting of stationary and mobile sensor nodes that collaborate to improve the sensing coverage and event detection of the network in a given deployment area. The paper describes the hardware and infrastructure of the testbed as well as a case study for coverage control that was investigated using the testbed. We point out that the developed testbed can be used for the evaluation and validation of different algorithms for coverage control that involve collaboration between stationary and mobile sensors to improve the WSN's monitoring capabilities. In addition, it can also be used to investigate other objectives as well as other concepts (e.g., network control).     

无线传感器网络动态重传算法

无线传感器网络路由协议通过点到点的重传来提高数据传输的可靠性,其重传机制没有考虑不同业务数据的可靠性需求差异,统一设定一个静态的最大重传次数。本文提出了一种动态重传算法,为每种业务分别根据其可靠性需求动态设定最大重传次数。对于较低可靠性需求的业务,相比于传统重传机制减少了重传次数。仿真表明动态重传算法能有效降低网络能耗。     

一种距离无关的无线传感器网络定位算法

通过分析和仿真,指出距离无关的无线传感器网络定位算法DV-Hop在节点分布密度不均匀的网络中的局限性.由此,提出一种新的定位算法.该算法中,各节点感知周边的节点密度,基于此对周边锚节点分区,利用相同区域的锚节点执行定位计算.通过仿真验证,在节点分布密度不均的网络中,该算法有效地降低了未知节点的定位误差,提高了定位精度.     

无线传感器网络中基于遗传算法的优化覆盖机制

覆盖作为无线传感器网络应用的一个基本问题．反映了网络监测和实现目标跟踪的质量效果．针对传感器节点的高密度部署情况,研究了工作节点集选取问题．提出两种基于加权遗传算法和基于约束遗传算法的优化覆盖机制．根据生成的适值函数进行遗传算法操作．并计算传感器网络充分覆盖区域所需的近似最优工作节点集．仿真结果表明该算法能快速收敛于最优解．完成工作节点集的优化选取,从而降低网络冗余,延长网络生存时间．     

无线传感器网络部分覆盖算法及连通性研究

研究了无线传感器网络在部分覆盖下的节点配置及网络连通性问题。首先,基于最优正六边形拓扑架构,给出了节点密集分布条件下的覆盖率与相邻工作节点间距的解析关系,并在已有的最优完全覆盖算法OGDC的基础上进行了扩展和改进,从而得到了一种新的网络节点配置算法EGDC（Extended OGDC Algorithm）。该算法可以有效地选择出合适的工作节点以达到任意给定覆盖率下的部分覆盖。此外,还给出了一种检验和评价网络连通性的方法,通过该方法可以对网络的连通性进行量化分析,并给出了一项评价网络连通性的指标。仿真表明,EGDC可以有效地实现任意期望覆盖率下的网络配置并保持网络的连通。