• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >A Cloud Computing Solution for the Efficient Implementation of the P-SBAS DInSAR Approach
【24h】

A Cloud Computing Solution for the Efficient Implementation of the P-SBAS DInSAR Approach

机译：有效执行P-SBAS DInSAR方法的云计算解决方案

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We present an efficient Cloud Computing (CC) implementation of the Parallel Small BAseline Subset (P-SBAS) algorithm, which is an advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) technique for the generation of Earth surface displacement time series through distributed computing infrastructures. The rationale of our approach consists in properly distributing the large data volumes and the processing tasks involved in the P-SBAS chain among the available (virtual and/or physical) computing nodes of the CC infrastructure, so that each one of these elements can concurrently work on data that are physically stored on its own local volume. To do this, both an ad hoc management of the data flow and an appropriate scheduling of the parallel jobs have been also implemented to properly handle the high complexity of the P-SBAS workflow. The proposed solution allows minimizing the overall data transfer and network load, thus improving the P-SBAS efficiency and scalability within the exploited CC environments. The presented P-SBAS implementation has been extensively validated through two experimental analyses, which have been carried out by exploiting the Amazon Web Services (AWS) Elastic Cloud Compute (EC2) resources. The former analysis involves the processing of a large (128 SAR images) COSMO-SkyMed dataset, which has been performed by exploiting up to 64 computing nodes, and is aimed at demonstrating the P-SBAS scalable performances. The latter allows us to show the P-SBAS capability to generate DInSAR results at a regional scale (150 000 km2 in Southern California) in a very short time (about 9 h), by simultaneously processing 18 ENVISAT frames that correspond to a total of 741 SAR images, exploiting in parallel 144 AWS computing nodes. The presented results confirm the effectiveness of the proposed P-SBAS CC solution, which may contribute to further extend the frontiers of the DInSAR investigation at a very large scale.
机译：我们介绍了并行小型BAseline子集（P-SBAS）算法的高效云计算（CC）实现，该算法是一种先进的差分干涉合成孔径雷达（DInSAR）技术，用于通过分布式计算基础结构生成地球表面位移时间序列。我们方法的基本原理在于在CC基础结构的可用（虚拟和/或物理）计算节点之间正确分配P-SBAS链中涉及的大数据量和处理任务，以便这些元素中的每个元素可以同时进行处理实际存储在其自身本地卷上的数据。为此，还实施了数据流的临时管理和并行作业的适当调度，以正确处理P-SBAS工作流程的高复杂性。所提出的解决方案允许最小化整体数据传输和网络负载，从而在被利用的CC环境中提高P-SBAS的效率和可扩展性。通过利用Amazon Web Services（AWS）弹性云计算（EC2）资源进行的两次实验分析，已对所提出的P-SBAS实施进行了广泛验证。以前的分析涉及处理大型（128个SAR图像）COSMO-SkyMed数据集，该数据集已通过利用多达64个计算节点来执行，旨在证明P-SBAS可扩展的性能。后者使我们能够展示P-SBAS通过在短时间内（约9小时）内同时处理18个ENVISAT帧来生成DInSAR结果的能力，该结果在一个区域范围内（南加州为15万平方千米）。 741个SAR图像，并行使用144个AWS计算节点。提出的结果证实了所提出的P-SBAS CC解决方案的有效性，这可能有助于进一步大规模扩展DInSAR研究的前沿领域。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号