一种连通性覆盖的无线传感器网络节点调度算法

研究传感器节点随机部署于监测区域内,无节点地理位置信息情况下,如何能量有效地保证网络的通信连通与感知覆盖;节点采用基于概率的联合感知模型。提出CDS-based SSCA算法,其为一种基于连通支配集构造树的节点调度机制,每个节点根据剩余能量和与父节点的距离来设置等待时间及成为候选节点优先级。模拟实验结果显示,本算法能够能量有效地满足感知覆盖和连通覆盖要求;与ASW算法相比较,工作节点个数较少,网络生命周期明显延长,降低了网络整体耗能。     

Sensor selection for parameterized random field estimation in wireless sensor networks

We consider the random field estimation problem with parametric trend in wireless sensor networks where the field can be described by unknown parameters to be estimated. Due to the limited resources, the network selects only a subset of the sensors to perform the estimation task with a desired performance under the D-optimal criterion. We propose a greedy sampling scheme to select the sensor nodes according to the information gain of the sensors. A distributed algorithm is also developed by consensus-based ...     

On infinite-horizon sensor scheduling

In this paper we consider the problem of infinite-horizon sensor scheduling for estimation in linear Gaussian systems. Due to possible channel capacity, energy budget or topological constraints, it is assumed that at each time step only a subset of the available sensors can be selected to send their observations to the fusion center, where the state of the system is estimated by means of a Kalman filter. Several important properties of the infinite-horizon schedules will be presented in this paper. In particular, we prove that the infinite-horizon average estimation error and the boundedness of a schedule are independent of the initial covariance matrix. We further provide a constructive proof that any feasible schedule with finite average estimation error can be arbitrarily approximated by a bounded periodic schedule. We later generalized our result to lossy networks. These theoretical results provide valuable insights and guidelines for the design of computationally efficient sensor scheduling policies.     

Mobility increases the surface coverage of distributed sensor networks

Coverage is a fundamental issue in sensor networks, which usually dictates the overall network performance. Previous studies on coverage issues mainly focused on sensor networks deployed on a 2D plane or in 3D space. However, in many real world applications, the target fields can be complex 3D surfaces where the existing coverage analysis methodology cannot be applied. This paper investigates the coverage of mobile sensor networks deployed over convex 3D surfaces. This setting is highly challenging because this dynamic type of coverage depends on not only sensors’ movement but also the characteristics of the target field. Specifically, we have made three major contributions. First, we generalize the previous analysis of coverage in the 2D plane case. Second, we derive the coverage characterization for the sphere case. Finally, we consider the general convex 3D surface case and derive the coverage ratio as a function of sensor mobility, sensor density and surface features. Our work timely fills the blank of coverage characterization for sensor networks and provides insights into the essence of the coverage hole problem. Numerical simulation and real-world evaluation verify our theoretical results. The results can serve as basic guidelines for mobile sensor network deployment in applications concerning complex sensing fields.     

无线传感网中基于正方形剖分的节点调度算法

节点调度机制是解决无线传感器网络节点能量受限问题的重要方法,提出了一种基于节点位置信息和正方形剖分模型的传感区域分布式快速分区方法;在此基础上,提出了一种基于分组的分布式节点调度算法。理论分析与仿真实验表明,新算法具有比传统方法更好的节点调度性能,可同时保持100%的网络覆盖率与分组全局连通性。     

无线传感器网络分簇拓扑的覆盖区域节点调度优化算法研究

利用区域分割的方法建立了一种覆盖区域冗余节点的优化调度机制,实现对完全覆盖区域内冗余节点的休眠调度,并将该机制引入无线传感器网络的分簇结构中,提出一种基于分簇拓扑的节点调度优化算法。算法通过控制簇内冗余节点进行休眠,减少簇首的数据通信量和簇成员中工作的冗余节点个数,降低了网络能耗。仿真结果表明,与未考虑冗余节点休眠调度的分簇算法相比,该算法有效提高了网络能量利用率,延长了网络生命期。     

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。     

Tracking a moving object via a sensor network with a partial information broadcasting scheme

Tracking a moving object is one of the key applications of wireless sensor networks (WSNs) for facility management, logistics, healthcare, etc. The quantitative relationship between tracking accuracy and resource consumption is crucial for designing a WSN-based tracking system. A partial information broadcasting scheme (PIBS) is developed as a decentralized tracking strategy in this paper, where only a part of the nodes broadcast their tracking estimation results to their neighbors. The relationship between tracking accuracy and resource consumption is quantified with this scheme. Two broadcasting policies are proposed by balancing the residual energy among sensors and reducing time delay, where the “Randomly Broadcast” (RB) policy takes energy consumption as a first priority and the “Good Estimates Broadcast First” (GEBF) policy consider time delay first. Both of them can be implemented as a decentralized tracking strategy. It is shown that the PIBS with RB or PIBS with GEBF can reduce required resources with minor degradation in tracking accuracy in comparison with the centralized tracking strategy. The finite sensing range of a sensor node is considered and a node activation scheme with variable activation radius is introduced for energy saving. The activation radius is adjusted to guarantee tracking coverage with trade-off between tracking accuracy and resource consumption. The analytical conditions on tracking coverage and the bounds on tracking accuracy are obtained. The numerical experiments demonstrate that this activation scheme outperforms the existing schemes.     

无线传感器网络随机调度算法研究

无线传感器网络(WSN)具有节点能量有限、节点冗余度高等特点,这使得轮换成为解决网络覆盖问题的基本工作机制之一。基于轮换工作机制对随机调度模型下的网络特性进行了研究,分析了网络中有效节点总数与轮换周期数的关系,并提出了根据网络中有效节点总数来动态调节节点工作概率的算法。该算法能很好地解决网络因有效节点数目减少、工作概率固定所造成的网络运行后期网络性能无法满足网络需求的问题,保证每轮中的网络性能基本一致。仿真实验证明了所提算法的有效性及分析的正确性。     

无线传感器网络中节点选择机制综述*

节点选择是保证无线传感器网络满足系统QoS需求的最重要问题之一,一种性能较好的节点选择机制可以在保证数据精度的前提下延长网络生命周期。针对WSN节点选择问题进行了描述及分类,着重研究了几类当前具有代表性的节点选择机制,并分析比较了各自的性能及缺点;最后对节点选择的进一步研究方向进行了展望。     

Link scheduling in wireless sensor networks: Distributed edge-coloring revisited

We consider the problem of link scheduling in a sensor network employing a TDMA MAC protocol. Our algorithm consists of two phases. The first phase involves edge-coloring: an assignment of a color to each edge in the network such that no two edges incident on the same node are assigned the same color. Our main result for the first phase is a distributed edge-coloring algorithm that needs at most (Δ+1) colors, where Δ is the maximum degree of the network. To our knowledge, this is the first distributed algorithm that can edge-color a graph using at most (Δ+1) colors. The second phase uses the edge-coloring solution for link scheduling. We map each color to a unique timeslot and attempt to assign a direction of transmission along each edge such that the hidden terminal problem is avoided; an important result we obtain is a characterization of network topologies for which such an assignment exists. Next, we consider topologies for which a feasible transmission assignment does not exist for all edges, and obtain such an assignment using additional timeslots. Finally, we show that reversing the direction of transmission along every edge leads to another feasible direction of transmission. Using both the transmission assignments, we obtain a TDMA MAC schedule which enables two-way communication between every pair of adjacent sensor nodes. For acyclic topologies, we prove that at most 2(Δ+1) timeslots are required. Results for general topologies are demonstrated using simulations; for sparse graphs, we show that the number of timeslots required is around 2(Δ+1). We show that the message and time complexity of our algorithm is O(nΔ²+n²m), where n is the number of nodes and m is the number of edges in the network. Through simulations, we demonstrate that the energy consumption of our solution increases linearly with Δ. We also propose extensions to account for non-ideal radio characteristics.     

一种节能多属性目标监测的感知网络覆盖算法

研究了一种多属性目标的覆盖问题,这种覆盖问题与单一类型数据的目标不同,其待测区域中的每个目标同时包含多种类型的现场数据。如果布置一个无线感知网络去担任监测任务,其节点需要配置多种不同类型的传感器单元。针对这种需要采集多种类型的数据才能对目标进行监测的无线感知网络的应用,节能而有效的覆盖目标更是一个突出的问题。首先用ILP模型将问题进行了形式化,然后通过设计一种分布式算法求得问题的解。最后,在不同的节点密度下,对网络的使用寿命进行了模拟仿真;仿真结果表明,这种分布式算法比直接求解ILP求出的网络寿命很接近。由于直接求解ILP问题必须依靠中心节点完成,对于节点较多并且电量受限的无线感知网络,这种分布式算法更适合。     

An algorithm for clock synchronization with the gradient property in sensor networks

We introduce a distributed algorithm for clock synchronization in sensor networks. Our algorithm assumes that nodes in the network only know their immediate neighborhoods and an upper bound on the network’s diameter. Clock-synchronization messages are only sent as part of the communication–assumed to be reasonably frequent–that already takes place among nodes. The algorithm has the gradient property of [R. Fan, N. Lynch, Gradient clock synchronization, Distributed Computing 18 (2006) 255–266], achieving an O(1)$O\left(1\right)$ worst-case skew between the logical clocks of neighbors. The algorithm’s actions are such that no constant lower bound exists on the rate at which logical clocks progress in time, and for this reason the lower bound of [R. Fan, N. Lynch, Gradient clock synchronization, Distributed Computing 18 (2006) 255–266; L. Meier, L. Thiele, Brief announcement: Gradient clock synchronization in sensor networks, in: Proceedings of the Twenty-Fourth Annual ACM Symposium on Principles of Distributed Computing, 2005, p. 238] that forbids a constant clock skew between neighbors does not apply.     

面向差异化覆盖的异构有向传感器节点调度算法

为延长异构有向传感器网络的寿命,提出一种基于改进珊瑚礁优化算法（ECRO）的面向不同监测目标有不同监测要求的节点调度算法。利用ECRO将传感器集合划分成符合覆盖要求的多个集合,通过集合间的调度达到延长网络寿命的目的。对珊瑚礁优化算法（CRO）的改进体现在四个方面：一是在珊瑚礁的雌雄同体繁殖过程中融入生物地理学优化算法中的迁移操作,保留原有种群的优秀解;二是在雌雄同体繁殖过程中采用一种带有混沌参数的差分变异因子,增强子代的优化能力;三是通过对最差个体执行随机反向学习,增强种群的多样性;四是通过CRO与模拟退火算法的结合,增强算法的局部搜索能力。对数值基准函数和节点调度进行了大量的仿真实验。在数值测试方面的结果表明,与遗传算法、模拟退火算法、差分进化算法及其改进算法相比,ECRO的优化能力更强;在传感器网络节点调度方面的结果表明,与贪婪算法、基于学习自动机的差分进化（LADE）算法和未改进的CRO相比,ECRO使网络寿命分别提高了53.8%、19.0%和26.6%,验证了所提算法的有效性。     

Distributed estimation for adaptive sensor selection in wireless sensor networks

Wireless sensor networks (WSNs) are usually deployed for monitoring systems with the distributed detection and estimation of sensors. Sensor selection in WSNs is considered for target tracking. A distributed estimation scenario is considered based on the extended information filter. A cost function using the geometrical dilution of precision measure is derived for active sensor selection. A consensus-based estimation method is proposed in this paper for heterogeneous WSNs with two types of sensors. The convergence properties of the proposed estimators are analyzed under time-varying inputs. Accordingly, a new adaptive sensor selection (ASS) algorithm is presented in which the number of active sensors is adaptively determined based on the absolute local innovations vector. Simulation results show that the tracking accuracy of the ASS is comparable to that of the other algorithms.     

一种用于无线传感器网络的质心定位算法

在建立定位算法求解数学模型和定位性能描述的基础上,提出了一种无线传感器网络定位算法——去中心化场强加权多跳质心定位算法。该算法对单跳质心算法进行多跳扩展以改善定位比率,并加入场强加权过程和去中心化过程以提高定位精度。通过仿真实验分析可以看到,与原始质心算法相比,此质心定位算法的平均定位误差可下降一半左右,并使节点密度较低情况下的定位比率提高至接近1。     

On redundant coverage maximization in wireless visual sensor networks: Evolutionary algorithms for multi-objective optimization

Wireless visual sensor networks can provide valuable information for a variety of monitoring and control applications. Frequently, a set of targets must be covered by visual sensors, as such visual sensing redundancy is a desired condition specially when applications have availability requirements for multiple coverage perspectives. If visual sensors become rotatable, their sensing orientations can be adjusted to optimize coverage and redundancy, bringing different challenges as there may be different coverage optimization objectives. Actually, the specific issue of redundant coverage maximization is inherently a multi-objective problem, but usual approaches are not designed accordingly to compute visual sensing redundancy. This article proposes two different evolutionary algorithms that exploit the multi-objective nature of the redundant coverage maximization problem: a lexicographic ”a priori” algorithm and a NSGA-II ”a posteriori” algorithm. The performance of both algorithms are compared, using a previously proposed single-objective greedy-based algorithm as a reference. Numerical results outline the benefits of employing evolutionary algorithms for adjustments of sensors’ orientations, potentially benefiting deployment and management of wireless visual sensor networks for different monitoring scenarios.     

基于Bayes与多层Bayes估计的WSN链路选择算法

无线传感器网络（WSN）节点能量有限,采用传统的链路选择的方法（经验法）进行链路选择,需要发送大量的数据包作为测试样本,这在WSN中是不合适的。设计了两种基于Bayes估计与一种基于多层Bayes估计的WSN链路选择算法,分别记为BLSP-B1、BLSP-B2、BLSP-HE。仿真实验发现,在小样本的条件下,BLSP-B1、BLSP-B2、BLSP-HE选择高质量的链路的概率比经验法要高出10%～20%,其中BLSP-HE算法最稳健,性能较好。     

Distributed wireless power transfer in sensor networks with multiple Mobile Chargers

We investigate the problem of efficient wireless power transfer in wireless sensor networks. In our approach, special mobile entities (called the Mobile Chargers) traverse the network and wirelessly replenish the energy of sensor nodes. In contrast to most current approaches, we envision methods that are distributed and use limited network information. We propose four new protocols for efficient charging, addressing key issues which we identify, most notably (i) what are good coordination procedures for the Mobile Chargers and (ii) what are good trajectories for the Mobile Chargers. Two of our protocols (DC, DCLK) perform distributed, limited network knowledge coordination and charging, while two others (CC, CCGK) perform centralized, global network knowledge coordination and charging. As detailed simulations demonstrate, one of our distributed protocols outperforms a known state of the art method, while its performance gets quite close to the performance of the powerful centralized global knowledge method.     

Aggregation in sensor networks with a user-provided quality of service goal

Significant research has been devoted to aggregation in sensor networks with the purpose of optimizing its performance. Existing research has mostly concentrated on maximizing network lifetime within a user-given error bound. In general, the greater the error bound, the longer the lifetime. However, in some situations, it may not be realistic for the user to provide an error bound. Instead, the user may want to provide a quality of service (QoS) goal that has a combined objective of lifetime and error. Indeed, the error tolerable by the user may depend on how long the sensor network can last. This paper presents an aggregation protocol and related algorithms for reaching such a QoS goal. The key idea is to periodically modify a filter threshold for each sensor in a way that is optimal within the user objective, the key technical method being to translate the problem into a mathematical programming formulation with constraints coming from various sources, such as the user, the sensor network, and the data characteristics. Extensive experiments demonstrate the high accuracy, high flexibility and low overhead of this QoS-based optimization approach.