Cooperative distributed target tracking algorithm in mobile wireless sensor networks

The paper proposes a cooperative distributed target tracking algorithm in mobile wireless sensor networks.There are two main components in the algorithm:distributed sensor-target assignment and sensor motion control.In the key idea of the sensor-target assignment,sensors are considered as autonomous agents and the defined objective function of each sensor concentrates on two fundamental factors:the tracking accuracy and the tracking cost.Compared with the centralized algorithm and the noncooperative distrib...     

A cellular learning automata-based deployment strategy for mobile wireless sensor networks

One important problem which may arise in designing a deployment strategy for a wireless sensor network is how to deploy a specific number of sensor nodes throughout an unknown network area so that the covered section of the area is maximized. In a mobile sensor network, this problem can be addressed by first deploying sensor nodes randomly in some initial positions within the area of the network, and then letting sensor nodes to move around and find their best positions according to the positions of their neighboring nodes. The problem becomes more complicated if sensor nodes have no information about their positions or even their relative distances to each other. In this paper, we propose a cellular learning automata-based deployment strategy which guides the movements of sensor nodes within the area of the network without any sensor to know its position or its relative distance to other sensors. In the proposed algorithm, the learning automaton in each node in cooperation with the learning automata in the neighboring nodes controls the movements of the node in order to attain high coverage. Experimental results have shown that in noise-free environments, the proposed algorithm can compete with the existing algorithms such as PF, DSSA, IDCA, and VEC in terms of network coverage. It has also been shown that in noisy environments, where utilized location estimation techniques such as GPS-based devices and localization algorithms experience inaccuracies in their measurements, or the movements of sensor nodes are not perfect and follow a probabilistic motion model, the proposed algorithm outperforms the existing algorithms in terms of network coverage.     

Decomposition algorithms for maximizing the lifetime of wireless sensor networks with mobile sinks

We address the problem of maximizing the lifetime of a wireless sensor network with energy-constrained sensors and a mobile sink. The sink travels among discrete locations to gather information from all the sensors. Data can be relayed among sensors and then to the sink location, as long as the sensors and the sink are within a certain threshold distance of each other. However, sending information along a data link consumes energy at both the sender and the receiver nodes. A vital problem that arises is to prescribe sink stop durations and data flow patterns that maximally prolong the life of the network, defined as the amount of time until any node exhausts its energy. We describe linear programming and column generation approaches for this problem, and also for a version in which data can be delayed in its transmission to the sink. Our column generation approach exploits special structures of the linear programming formulations so that all subproblems are shortest path problems with non-negative costs. Computational results demonstrate the efficiency of the proposed algorithms.     

分布式无线传感器网络故障检测算法综述

阐述了传感器网络中节点发生故障的原因并建立了故障模型。将当前主要的分布式节点故障检测算法分成了基于多数投票策略、基于中值策略、基于决策扩散策略、基于加权和基于分簇的算法五大类,详细阐述了分布式无线传感器网络故障检测算法的原理和步骤,并指出了各个算法的优势与不足。最后,对各个算法的性能进行了分析与比较,讨论了算法存在的问题,并指出了进一步的研究方向。     

异构无线传感器网络中基于模拟退火算法的成本最优部署机制

针对异构传感器网络节点的高密度部署和监测目标非均匀分布的情况,提出了一种基于模拟退火算法的成本最优部署方法.算法在保证网络覆盖和容错性的条件下,以异构节点部署成本最小为优化目标进行操作.仿真结果表明该算法能快速收敛于最优解,有效降低网络部署的成本,提高了目标监测质量.     

Deployment algorithms for a power‐constrained mobile sensor network

This paper presents distributed coverage algorithms for mobile sensor networks in which agents have limited power to move. Rather than making use of a constrained optimization technique, our approach accounts for power constraints by assigning non‐homogeneously time‐varying regions to each robot. This leads to novel partitions of the environment into limited‐range, generalized Voronoi regions. The motion control algorithms are then designed to ascend the gradient of several types of locational optimization functions. In particular, the objective functions reflect the global energy available to the group and different coverage criteria. As we discuss in the paper, this has an effect on limiting each agent's velocity to save energy and balance its expenditure across the network. Copyright © 2009 John Wiley & Sons, Ltd.     

管道支持移动传感器网络部署和调度研究综述*

在分析移动传感网络用途的基础上,综述了移动传感网络部署和调度的研究现状,提出了基于管道支持的移动传感器网络部署和调度方法,识别和分析了其当前面临的一组关键挑战,展望和讨论了其未来的发展方向。     

Selection and navigation of mobile sensor nodes using a sensor network

Hybrid sensor networks comprise of mobile and static sensor nodes set up for the purpose of collaboratively performing tasks like sensing a phenomenon or monitoring a region. In this paper, we present a novel approach for navigating a mobile sensor node (MSN) through such a hybrid sensor network. The static sensor nodes in the sensor network guide the MSN to the phenomenon. One or more MSNs are selected based on their proximity to the detected phenomenon. Navigation is accomplished using the concepts of credit based field setup and navigation force from static sensor nodes. Our approach does not require any prior maps of the environment, thus cutting down the cost of the overall system. The simulation results have verified the effectiveness of the proposed approach. In each of the simulation runs, the static sensor nodes were able to successfully guide the MSN towards the phenomenon.     

Optimizing data collection path in sensor networks with mobile elements

Exploiting mobile elements (MEs) to accomplish data collection in wireless sensor networks (WSNs) can improve the energy efficiency of sensor nodes, and prolong network lifetime. However, it will lead to large data collection latency for the network, which is unacceptable for data-critical applications. In this paper, we address this problem by minimizing the traveling length of MEs. Our methods mainly consist of two steps: we first construct a virtual grid network and select the minimal stop point set (SPS) from it; then, we make optimal scheduling for the MEs based on the SPS in order to minimize their traveling length. Different implementations of genetic algorithm (GA) are used to solve the problem. Our methods are evaluated by extensive simulations. The results show that these methods can greatly reduce the traveling length of MEs, and decrease the data collection latency.     

一种基于虚拟力的移动传感器网络再部署算法

针对移动传感器网络中,数据的大规模定向传输的实际特性,提出一种基于虚拟力的移动传感器网络节点精确部署算法（VFPDA）。通过引入“中继节点簇”的概念,在源节点到目的节点之间生成多条虚拟“引力线”,这些引力线相互衔接从而构成一条虚拟的通路,然后吸引周围的移动节点向其靠拢,在“引力线”所产生的引力以及节点之间的斥力等作用力的共同作用下,构建一条从源节点到目的节点的通路。实验仿真验证了该算法的有效性。     

基于差分进化算法的移动传感器网络节点的分布优化

针对传感器节点的分布优化问题,研究了在保证网络连通性的前提下,极大化移动传感器网络的有效覆盖面积问题,提出了一种基于差分进化算法的移动传感器网络节点分布优化机制.仿真实验结果表明,该算法能以相对较小的代价快速完成移动传感器网络节点的分布优化,提高网络的有效覆盖率,实现移动传感器网络布局的全局优化.     

移动传感网中基于虚拟货币的路由策略

移动无线传感器网络中,针对节点基于随机运动模型的路由问题,提出一种基于虚拟货币的低能耗路由策略——DTVC。根据节点的属性和数据消息的属性进行买方和卖方的定价并据此选择转发节点。为了提升网络性能,通过控制数据消息的副本数以及对节点的缓存队列中的数据消息排序,把网络中的节点分为源节点和中继节点,只有数据消息的源节点可以复制该数据消息,并依据数据消息的延迟容忍度对消息进行排序,延迟容忍度越小则优先级越高。为了减少网络中的能量消耗,根据sink节点广播的消息删除缓存队列中已经传输成功的数据消息。在Matlab上的仿真实验结果表明,与基于消息容错的自适应数据传输算法（FAD）、基于距离和能量感知模糊逻辑的路由算法（FLDAER）和基于能耗自选演进机制的路由算法相比,DTVC的数据消息投递率至少提高2.5%,平均副本数至少减少25%。     

延迟容忍移动无线传感器网络路由分析

延迟容忍移动无线传感器网络DTMSN（Delay Tolerant Mobile Sensor Networks）用于广泛数据收集,传统传感器网络的数据收集方法在DTMSN中并不适用。为此研究了DTMSN的特性,分析了目前常用的几种DTMSN路由算法的特点,并通过详细的仿真实验给出了这几种算法的性能指标,如数据的平均传输成功率,传输能耗、传输延迟及网络寿命。     

Time-optimized contextual information forwarding in mobile sensor networks

We study on the forwarding of quality contextual information in mobile sensor networks (MSNs). Mobile nodes form ad-hoc distributed processing networks that produce accessible and quality-stamped information about the surrounding environment. Due to the dynamic network topology of such networks the context quality indicators seen by the nodes vary over time. A node delays the context forwarding decision until context of better quality is attained. Moreover, nodes have limited resources, thus, they have to balance between energy conservation and quality of context. We propose a time-optimized, distributed decision making model for forwarding context in a MSN based on the theory of optimal stopping. We compare our findings with certain context forwarding schemes found in the literature and pinpoint the advantages of the proposed model.     

基于距离的分布式无线传感器网络定位算法*

针对水下无线传感器节点的定位问题进行研究,提出了一种可实现网络规模升级的分布式无信标节点的自定位算法。该定位算法无须额外的硬件支持,仅采用节点间的距离信息建立相对坐标系,确定各节点的相对位置。详细介绍了该算法的实现过程,通过仿真讨论了求精过程、通信半径等对定位误差的影响,并验证了该算法的合理性。为目标跟踪、地理路由、网络管理等系统功能提供了有力的技术支持。     

Distributed network control for mobile multi-modal wireless sensor networks

A sensor network operates on an infrastructure of sensing, computation, and communication, through which it perceives the evolution of events it observes. We propose a fusion-driven distributed dynamic network controller, called MDSTC, for a multi-modal sensor network that incorporates distributed computation for in-situ assessment, prognosis, and optimal reorganization of constrained resources to achieve high quality multi-modal data fusion. For arbitrarily deployed sensors, a certain level of data quality cannot be guaranteed in sparse regions. MDSTC reallocates resources to sparse regions; reallocation of network resources in this manner is motivated by the fact that an increased density of sensor nodes in a region of interest leads to better quality data and enriches the network resilience. Simulation results in NS-2 show the effectiveness of the proposed MDSTC. ¹     

无线传感器网络的设计与部署

首先分析了无线传感器网络与传统无线自组织网络的区别,从侧面阐述了无线传感器网络的特点。接着,讨论了对无线传感器网络设计与部署具有指导意义的无线传感器网络的评价指标。最后,从无线传感器节点到无线传感器网络、从个体到整体、从微观到宏观,较为全面地讨论了无线传感器网络的设计与部署问题,为无线传感器网络的实际应用提供了有价值的参考。     

A smart node architecture for adding mobility to wireless sensor networks

Adding a few mobile nodes into the conventional wireless sensor networks can greatly improve the sensing and control capabilities of the networks and can help researchers solve many challenges such as network deployment and repair. This paper presents an enhanced node architecture for adding controlled mobility to wireless sensor networks. The structural model, the power model and the networking model of the proposed mobile node have been built respectively for better node control. And it provides a novel robotic platform for experimental research in hybrid sensor networks or other distributed measurement and control systems. A testbed has finally been created for validating the basic functions of the proposed mobile sensor node. The results of a coverage experiment show that the mobile node can provide additional support for network coverage and can ensure that the sensor network will work properly in undesirable environments.     

Flocking based evolutionary computation strategy for measuring centrality of online social networks

Centrality in social network is one of the major research topics in social network analysis. Even though there are more than half a dozen methods to find centrality of a node, each of these methods has some drawbacks in one aspect or the other. This paper analyses different centrality calculation methods and proposes a new swarm based method named Flocking Based Centrality for Social network (FBCS). This new computation technique makes use of parameters that are more realistic and practical in online social networks. The interactions between nodes play a significant role in determining the centrality of node. The new method has been calculated both empirically as well as experimentally. The new method is tested, verified and validated for different sets of random networks and benchmark datasets. The method has been correlated with other state of the art centrality measures. The new centrality measure is found to be realistic and suits well with online social networks. The proposed method can be used in applications such as finding the most prestigious node and for discovering the node which can influence maximum number of users in an online social network. FBCS centrality has higher Kendall’s tau correlation when compared with other state of the art centrality methods. The robustness of the FBCS centrality is found to be better than other centrality measures.     

EE-UDRA: 带环境元素的水下传感器网络分布式路由算法

现阶段的水下传感器网络(UWSN,underwater sensor networks)路由算法的研究工作大多都没有对部署的水下环境做具体分析,不同水下环境与网络性能之间的相关性研究较少,同时针对水下信道利用率低、能量消耗和延迟时间较大等问题,提出融合了环境元素的水下传感器网络分布式路由算法(EE-UDRA),分析了不同的水下传播环境以及环境元素对路由算法性能的影响,通过增长型分组队列的管理方法重点解决了水下信道利用率较低的问题,并在提高信道利用率的基础上通过分析能耗或延迟的可控因素来寻找能耗最低或延迟最小的路由路径。实验结果显示,环境元素对相同算法的运行结果带来了一定的影响。在提高信道利用率的同时,EE-UDRA算法选择的最佳路由路径在减少能量消耗,缩短延迟时间上具有较好的效果。