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Imaging Seismic Tomography in Sensor Network

机译:传感器网络中的成像地震断层扫描

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摘要

Tomography imaging, applied to seismology, requires a new, decentralized approach if high resolution calculations are to be performed in a sensor network configuration. The real-time data retrieval from a network of large-amount wireless seismic nodes to a central server is virtually impossible due to the sheer data amount and resource limitations. In this paper, we present a distributed multi-resolution evolving tomography algorithm for processing data and inverting volcano tomography in the network, while avoiding costly data collections and centralized computations. The new algorithm distributes the computational burden to sensor nodes and performs real-time tomography inversion under the constraints of network resources. We implemented and evaluated the system design in the CORE emulator. The experiment results validate that our proposed algorithm not only balances the computation load, but also achieves low communication cost and high data loss tolerance.
机译:应用于地震学的断层摄影成像需要一种新的分散的方法,如果要在传感器网络配置中执行高分辨率计算。由于庞大的数据量和资源限制,从大量无线地震节点网络到中央服务器的实时数据检索几乎不可能。在本文中,我们提出了一种用于在网络中处理数据和反相火山断层扫描的分布式多分辨率不断变化算法,同时避免了昂贵的数据收集和集中计算。新算法将计算负担分配到传感器节点,并在网络资源的约束下执行实时断层扫描反转。我们在核心仿真器中实现和评估了系统设计。实验结果验证了我们所提出的算法不仅余额余额,还实现了低通信成本和高数据丢失公差。

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