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A network-aware framework for energy-efficient data acquisition in wireless sensor networks

机译:一种在无线传感器网络中实现节能数据采集的网络感知框架

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Wireless sensor networks enable users to monitor the physical world at an extremely high fidelity. In order to collect the data generated by these tiny-scale devices, the data management community has proposed the utilization of declarative data-acquisition frameworks. While these frameworks have facilitated the energy-efficient retrieval of data from the physical environment, they were agnostic of the underlying network topology and also did not support advanced query processing semantics. In this paper we present KSpot(+), a distributed network-aware framework that optimizes network efficiency by combining three components: (i) the tree balancing module, which balances the workload of each sensor node by constructing efficient network topologies; (ii) the workload balancing module, which minimizes data reception inefficiencies by synchronizing the sensor network activity intervals; and (iii) the query processing module, which supports advanced query processing semantics. In order to validate the efficiency of our approach, we have developed a prototype implementation of KSpot(+) in nesC and JAVA. In our experimental evaluation, we thoroughly assess the performance of KSpot(+) using real datasets and show that KSpot(+) provides significant energy reductions under a variety of conditions, thus significantly prolonging the longevity of a WSN. (C) 2014 Elsevier Ltd. All rights reserved.
机译:无线传感器网络使用户能够以极高的保真度监控物理世界。为了收集由这些小型设备生成的数据,数据管理社区提出了使用声明性数据获取框架的建议。尽管这些框架有助于从物理环境中高效节能地检索数据,但它们与底层网络拓扑无关,也不支持高级查询处理语义。在本文中,我们提出了KSpot(+),它是一种分布式的网络感知框架,通过组合三个组件来优化网络效率:(i)树平衡模块,该树平衡模块通过构建有效的网络拓扑来平衡每个传感器节点的工作量; (ii)工作量平衡模块,该模块通过同步传感器网络活动间隔来最大程度地减少数据接收效率; (iii)查询处理模块,其支持高级查询处理语义。为了验证我们方法的效率,我们在nesC和JAVA中开发了KSpot(+)的原型实现。在我们的实验评估中,我们使用真实的数据集全面评估了KSpot(+)的性能,并表明KSpot(+)在各种条件下均能显着降低能耗,从而显着延长了WSN的使用寿命。 (C)2014 Elsevier Ltd.保留所有权利。

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