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一种统一的传感器节点部署和重新部署算法

Sensor Deployment and Relocation: A Unified Scheme

  • 摘要: 传感器网络可以通过监控或者调节我们周围的环境从而使得我们的日常生活发生巨大的变革。目前机器人技术以及低功耗技术的发展已经可以将移动性引入到轻巧、低成本的传感器系统中。在原有的静态传感器网络中引入移动性会产生许多设计方面的挑战。本文阐述了在移动网络中的拓扑控制问题。由于通信,计算能力以及能量的限制,节点的部署以及重新部署需要采用一种分布式的,能量高效的策略。本文提出一种分布式算法来解决节点的部署以及重新部署问题。本算法具有的特点如下,在节点部署阶段,我们的方法可以以一定的节点密度产生一种地理位置均匀分布的格形节点排列,我们把这种规则排列称作监控配置模式,这种模式可以高效的对网络进行覆盖与监控。当监控区域有异常事件发生时,网络节点可以重新定位自身位置来高效的采集和控制事件,并同时保持网络的连通性;而当事件结束时,所有的节点重新回到初始的监控配置模式的位置来继续监控事件。为了实现这个目标,我们使用了一种基于虚拟力的策略,基于虚拟力的计算方法已经被证明同许多优化的集中算法一样高效有效。最后,我们评估了算法在各种模式事件发生时的性能,并且讨论了事件发生时我们算法的瞬时表现。这种评估方法可以充分说明我们的方法在各种环境条件下的有效性和及时性。

     

    Abstract: Sensor networks are envisioned to revolutionize our daily life byubiquitously monitoring our environment and/or adjusting it to suit our needs.Recent progress in robotics and low-power embedded systems has made itpossible to add mobility to small, light, low-cost sensors to be used inteams or swarms. Augmenting static sensor networks with mobile nodesaddresses many design challenges that exist in traditional staticsensor networks. This paper addresses the problem of topology control inmobile wireless networks. Limitations in communication, computation and energycapabilities push towards the adoption of distributed, energy-efficientsolutions to perform self-deployment and relocation of the nodes.We develop a unified, distributed algorithm that hasthe following features. During deployment, our algorithm yields aregular tessellation of the geographical area with a given nodedensity, called \em monitoring configuration. Upon theoccurrence of a physical phenomenon,network nodes relocate themselves so as to properly sample andcontrol the event, while maintaining the network connectivity.Then, as soon as the event ends, all nodes return to the monitoringconfiguration. To achieve these goals, we use a virtualforce-based strategy which proves to be very effective even whencompared to an optimal centralized solution. We assess the performanceof our approach in the presence of events with different shapes, and weinvestigate the transient behavior of our algorithm. This allows us toevaluate the effectiveness and the response time of the proposedsolution under various environmental conditions.

     

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