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W-Grid: A scalable and efficient self-organizing infrastructure for multi-dimensional data management, querying and routing in wireless data-centric sensor networks

机译:W-Grid:可扩展且高效的自组织基础结构,用于以无线数据为中心的传感器网络中的多维数据管理,查询和路由

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Data-centric sensor networks are advanced ad hoc networks that act like a distributed database managing and indexing sensed data in order to efficiently perform advanced in-network tasks, such as routings, searches, data processing, fusion and analysis. The supplied distributed services, such as routing, content location and information sharing should be provided anywhere and at any time optimizing energy consumptions, computational resources, memory occupation and radio transmissions. Moreover, the network traffic should be equally balanced among participants in order to avoid premature discharge of some devices that may partition the network. This work describes a fully decentralized infrastructure able to self-organize nodes in ad hoc networks by exploiting local interactions and topology learning among devices. In this solution all nodes are peers and nothing prevent the approach to be used in wireless mesh networks as well. Differently from existing solutions, our proposal does not require global information or external help, such as the Global Positioning System, which works only outdoor with a precision and an efficacy both limited by weather conditions and obstacles. The infrastructure natively enables devices to perform routing and data management without using message broadcast/flooding operations. The work introduces also a feature, called full learning, that improves routing performances while balancing the traffic among devices. We report an extensive number of simulations comparing the new solution results with four existing proposals, two of which deriving from preceding versions of the infrastructure.
机译:以数据为中心的传感器网络是高级的ad hoc网络,其作用类似于分布式数据库,用于管理和索引感测到的数据,以便有效地执行高级网络内任务,例如路由,搜索,数据处理,融合和分析。所提供的分布式服务,例如路由,内容定位和信息共享,应在任何地方,任何时间提供,以优化能耗,计算资源,内存占用和无线电传输。此外,网络流量应在参与者之间平均平衡,以避免过早放电可能会划分网络的某些设备。这项工作描述了一种完全分散的基础架构,能够通过利用设备之间的本地交互和拓扑学习来自组织ad hoc网络中的节点。在该解决方案中,所有节点都是对等节点,也没有什么可以阻止该方法在无线网状网络中使用。与现有解决方案不同,我们的建议不需要全球信息或外部帮助,例如全球定位系统,该系统仅在室外工作,其精度和功效受天气条件和障碍的限制。该基础结构使设备本身可以执行路由和数据管理,而无需使用消息广播/洪泛操作。该作品还引入了一项称为“全面学习”的功能,该功能可以提高路由性能,同时平衡设备之间的流量。我们报告了大量的仿真,将新的解决方案结果与四个现有建议进行了比较,其中两个建议来自基础结构的先前版本。

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