Localized motion-based connectivity restoration algorithms for wireless sensor and actor networks

In wireless sensor and actor networks maintaining inter-actor connectivity is very important in mission-critical applications where actors have to quickly plan optimal coordinated response to detected events. Failure of one or multiple actors may partition the inter-actor network into disjoint segments, and thus hinders the network operation. Autonomous detection and rapid recovery procedures are highly desirable in such a case. This paper presents DCR, a novel distributed partitioning detection and connectivity restoration algorithm to tolerate the failure of actors. DCR proactively identifies actors that are critical to the network connectivity based on local topological information, and designates appropriate, preferably non-critical, backup nodes. Upon failure detection, the backup actor initiates a recovery process that may involve coordinated relocation of multiple actors. We also present an extended version of DCR, named RAM, to handle one possible case of a multi-actor failure. The proposed algorithms strive to avoid procrastination, localize the scope of recovery and minimize the movement overhead. Simulation results validate the performance of the proposed algorithms.     

Decentralized estimation and control of graph connectivity for mobile sensor networks

The ability of a robot team to reconfigure itself is useful in many applications: for metamorphic robots to change shape, for swarm motion towards a goal, for biological systems to avoid predators, or for mobile buoys to clean up oil spills. In many situations, auxiliary constraints, such as connectivity between team members or limits on the maximum hop-count, must be satisfied during reconfiguration. In this paper, we show that both the estimation and control of the graph connectivity can be accomplished in a decentralized manner. We describe a decentralized estimation procedure that allows each agent to track the algebraic connectivity of a time-varying graph. Based on this estimator, we further propose a decentralized gradient controller for each agent to maintain global connectivity during motion.     

Localization from connectivity in sensor networks

We propose an approach that uses connectivity information - who is within communications range of whom - to derive the locations of nodes in a network. The approach can take advantage of additional information, such as estimated distances between neighbors or known positions for certain anchor nodes, if it is available. It is based on multidimensional scaling (MDS), an efficient data analysis technique that takes O(n/sup 3/) time for a network of n nodes. Unlike previous approaches, MDS takes full advantage of connectivity or distance information between nodes that have yet to be localized. Two methods are presented: a simple method that builds a global map using MDS and a more complicated one that builds small local maps and then patches them together to form a global map. Furthermore, least-squares optimization can be incorporated into the methods to further improve the solutions at the expense of additional computation. Through simulation studies on uniform as well as irregular networks, we show that the methods achieve more accurate solutions than previous methods, especially when there are few anchor nodes. They can even yield good relative maps when no anchor nodes are available.     

基于费马点的网络连通性修复策略

连通性修复是保证网络有效性、可靠性的重要手段，而目前关于1-连通性修复的策略没有将图形的几何性质与网络的拓扑结构很好地结合，因此难以用最少的中继节点完成修复。将费马点、三角剖分与最小生成树有效结合，设计了一种基于费马点的网络连通性修复策略，并且从理论上证明了该策略的近似比和复杂度分别为$\frac{3\sqrt{3}}{4-\sqrt{3}}$ 与O(n log n)，而仿真实验表明该策略在中继节点消耗上明显少于其他同类型策略。     

无线传感器网络中移动传感器的再定位技术

回顾了在传感器网络中引入移动传感器的过程。介绍了移动传感器再定位技术可解决传感器网络中的事件深入感知、传感器失效和非精确投放等问题。详细阐述了现有的移动传感器移动至感兴趣区域深入感知、扩大网络覆盖面积和修补网络覆盖洞三类技术。剖析了现有技术中存在的问题。总结分析了主要解决方法和模型,并对未来研究方向进行了展望。     

Multivariate context collection in mobile sensor networks

We focus on the treatment of quality-stamped contextual information in mobile sensor networks. Sensing nodes capture and forward context for consumption by mobile context aware applications. Due to the dynamic network topology the quality indicators seen by consumers vary over time. Context quality is a decreasing function of time and context can be consumed with a certain delay from its capturing time. We propose the sequential assessment of the network-circulated context information according to the Generalized Secretary Problem, a known paradigm in the Optimal Stopping Theory. The consumer node delays the processing (consumption) of incoming context until better quality is attained. We extend this basic model to include the cardinality of contextual components (i.e., different types of measurements coming from, possibly, different sources). Hence, the consumer node is interested not only in the higher possible quality of context but also in the widest possible range of context parameters (context “quantity”). We compare our findings to simple consumption strategies and pinpoint the advantages of the proposed model.     

Quantifying connectivity in wireless sensor networks with grid-based deployments

Measuring network connectivity under grid-based deployment in 3D space is a challenging problem in wireless sensor networks (WSNs). Solving such a problem becomes an even more intricate task with realistic deployment factors such as placement uncertainty and hindrances to wireless communication channels. While much work has been published on optimizing connectivity, only a few papers have addressed such realistic aspects which cause severe connectivity problems in practice. In this paper, we introduce a novel grid-based deployment metric, called Average Connectivity Percentage in order to characterize the deployed network connectivity when sensor placements are subject to random errors around their corresponding grid locations. A generic approach is proposed to assess and evaluate the proposed metric. This generic approach is independent of the grid-shape, random error distributions, and different environment-based channel characteristics. We apply the generic approach in two practical deployment scenarios: the grid-based deployment with bounded uniform errors and with unbounded normal errors. In both cases, the average connectivity percentage is computed numerically and verified via extensive simulations. Based on the numerical results, quantified effects of positioning errors and grid edge length on the average connectivity percentage are outlined.     

无线传感器网络连通恢复综述

针对无线传感器网络中连通恢复问题,分析和总结了近年来相关的主要方向和研究成果,同时对无线传感器网络连通恢复解决方法进行了分类和总结,并指出了其中的不足与未来的研究方向。     

无线传感器网络的连通性问题研究

无线传感器网络的初始配置最优可以减少传感器网络的拓扑变化和降低网络重置的能量消耗.对初始均匀随机分布的无线传感器网络的连通性进行了研究.运用覆盖理论给出了传感器节点的连通度概率分布模型,并在此模型基础上推导出传感器节点的通信半径与期望连通度概率最大之间的关系.仿真结果表明了结论的正确性.     

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.     

水下移动无线传感器网络研究综述

水下移动传感器网络是水下机器人与水下传感器网络的结合,解决了传统水下监控网络存在的无法自动实现节点投放与回收,容易存在监测盲区以及不能动态组网等问题,按照自下而上的体系结构,对水下移动传感器网络的研究内容及发展方向进行了归纳阐述,包括水下节点设计、节点互联和动态组网,即点、线、面的层次结构;着重分析了节点移动特性对水下传感器网络的影响及相应的解决方法.虽然水下移动传感器网络的研究面临很多挑战,但它必将具有广阔的应用前景.     

基于重叠区域的无线传感反应网络连接性恢复机制

针对无线传感反应网络(WSAN)中反应节点的失效导致的网络连接性被破坏问题,提出了一种新的网络连接性恢复机制。反应节点首先根据2跳网络拓扑信息来确定是否为局部关键节点,然后利用反应节点间存在的管理区域的重叠性来计算新的移动位置,最后采用局部级联重定位方式来实现连接性的恢复。通过NS2仿真结果表明,该机制能够正确恢复网络的连接性并实现较小的恢复开销。     

Voronoi-based localisation algorithm for mobile sensor networks

Localisation is an essential and important part in wireless sensor networks (WSNs). Many applications require location information. So far, there are less researchers studying on mobile sensor networks (MSNs) than static sensor networks (SSNs). However, MSNs are required in more and more areas such that the number of anchor nodes can be reduced and the location accuracy can be improved. In this paper, we firstly propose a range-free Voronoi-based Monte Carlo localisation algorithm (VMCL) for MSNs. We improve the localisation accuracy by making better use of the information that a sensor node gathers. Then, we propose an optimal region selection strategy of Voronoi diagram based on VMCL, called ORSS-VMCL, to increase the efficiency and accuracy for VMCL by adapting the size of Voronoi area during the filtering process. Simulation results show that the accuracy of these two algorithms, especially ORSS-VMCL, outperforms traditional MCL.     

水下移动无线传感器网络拓扑

水下移动无线传感器网络是当今世界各国的研究热点之一. 水下复杂环境以及传感器节点移动特性使得水 下移动无线传感器网络拓扑具备了动态演化性, 同时, 水声通信也对水下移动无线传感器网络的可靠性产生了一定 影响. 首先归纳分析水下移动无线传感器网络国内外的研究现状及进展, 并剖析了水声通信对水下移动无线传感器 网络拓扑的影响; 然后凝炼出3 个科学问题, 重点论述了拓扑生成、拓扑愈合及拓扑优化; 最后对未来研究方向进行 了展望, 以期为该领域的深入研究提供清晰的思路.

     

Distributed patching for mobile wireless sensor networks

Mobile wireless sensor networks (MWSNs), the continuous movement of sensor nodes, may cause complete disconnection of the network or at best a part of it. The design of such networks should guarantee that all sensor nodes at all times have a path to the sink node(s). Prolonging the lifetimes of the MWSNs is a crucial design issue but should not be at the expense of other essential functions such as connectivity. In this paper, we propose an energy efficient distributed framework for connectivity maintenance of MWSNs. In the proposed framework, sensor nodes of the MWSNs schedule and control their radio frequency (RF) modules based on dynamic coordinated reconstruction mechanism, some senor nodes may lose their connectivity with the network due to mobility, depletion of energy and/or incurred faults. Two protocols are developed to patch up the disconnection of the MWSNs. The first protocol reestablishes the network connection consuming far less energy than state-of-the-art alternatives. However, it is capable of reestablishing the connection when no more than 20% of the MWSN backbone nodes lose connection concurrently. The second protocol extends this limit to operate when up to 35% of the MWSN backbone nodes lose connection simultaneously.     

Energy-aware self-organisation algorithms with heterogeneous connectivity in wireless sensor networks

Heterogeneity of node energy is a common phenomenon in wireless sensor networks. In such node energy heterogeneous sensor network, how to balance the energy consumption is the key problem on extending the lifetime of the sensor network system. An energy-efficient self-organisation algorithm with heterogeneous connectivity based on energy-awareness is proposed. Each sensor node in the network adjusts its own transmission radius based on the local energy information during the constructing and operating phase. Thus heterogeneous network topology, in which the nodes can choose different transmission radius, is formed. In contrast to the homogeneous network model, in which the node carries the same radius, simulation and analysis are conducted to explore the topology characteristics and robustness with different node energy distribution. The degree distribution shows the scale-free property in the heterogeneous model. The proposed network model enjoys higher efficiency of transmitting data, less clustering, higher robustness under node random failures and longer network lifetime than those in the homogeneous ones.     

基于VWMC的传感器网络移动节点定位算法

为了解决无线传感器网络移动节点定位精度低、计算方法复杂以及响应时间长的问题,提出了一种基于VWMC的传感器网络移动节点定位算法(VWMCL).该算法利用Monte Carlo算法作为移动节点的基本定位算法,并在预测阶段加入航位推算方法,通过减少预测角度的误差来提高粒子位置预测的精度;并把Voronoi图和权值融合在MCL算法的粒子过滤阶段,采用Voronoi图和权值的双重筛选的机制,提高粒子过滤的准确性.仿真结果表明,该算法可以显著改善定位精度,减少算法的计算量,从而提高定位的效率.     

一种单移动锚节点的无线传感器网络定位算法

研究了无线传感器网络的节点定位算法,提出了一种利用一个移动锚节点来实现定位的新算法。该算法利用一个移动锚节点,按照规划好的路径遍历整个网络,当移动锚节点移动到未知节点的通信半径以内,未知节点就可以接收锚节点的位置信息。当未知节点接收到三个以上的处于其通信半径上的位置信息,就可以计算出未知节点的坐标。最后,通过仿真研究了该算法的特性,仿真结果表明该定位方法在定位误差、能耗等方面均表现出良好的性能。     

An efficient algorithm for mobile localization in sensor networks

Node localization is a fundamental problem in wireless sensor network.There are many existing algorithms to estimate the locations of the nodes.However,most of the methods did not consider the presence of obstacles.In practice,obstacles will lead to blockage and reflection of communication signals between sensor nodes.Therefore,the presence of obstacles will greatly affect the localization result.In this paper,we implement an obstacle-handling algorithm based on the localization tool developed by MIT,The experimental result shows that the enhanced algorithm can reduce the average distance error by up to 46%,compared to the original algorithm.