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Geometry-Assisted Multi Surface-Gateways Placement Topologies for Underwater Sensor Networks

机译:水下传感器网络的几何辅助多表面网关放置拓扑

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Underwater acoustic sensor networks (UWASNs) have been presented as an advanced technology for detection and extraction of data in marine environments. UWASNs have many current real-time applications not limited to: resource exploration, seismic monitoring, marine explorations, oil and gas inspection, and military surveillance applications. However, this advanced technology is constrained to data detection, transmission, and forwarding. In addition, transmitting and receiving large volumes of data is requires an exhaustive amount of time and substantial power to be executed, and still fails to meet real-time constraints. This has directed our research focus to the development of a real-time underwater computing system to meet the required real-time constraints. In our research activities, we discover and extract valuable information from beneath the ocean using data-mining approaches. Previously, we introduced a set of real-time underwater system architectures (RTUSAs) that can address various network configurations according to their applications and data size We also presented architectures that use efficient data-gathering and information-extraction approaches to meet the required real-time constraints for underwater big-data applications. In this study, we extend our results and develop multiple-gateway placement topologies using geometric distribution characteristics to satisfy real-time constraints. The system performance has minimal end-to-end delay, and decreased power consumption. Finally, the simulation results are verified to validate the performance of our system according to multiple-gateway topologies.
机译:水下声传感器网络(UWASN)已作为一种用于检测和提取海洋环境中数据的先进技术而提出。 UWASN具有许多当前的实时应用,不仅限于:资源勘探,地震监测,海洋勘探,石油和天然气检查以及军事监视应用。但是,这项先进技术仅限于数据检测,传输和转发。另外,发送和接收大量数据需要耗费大量的时间和要执行的大量功率,并且仍然不能满足实时约束。这使我们的研究重点转向了实时水下计算系统的开发,以满足所需的实时约束。在我们的研究活动中,我们使用数据挖掘方法从海底发现并提取有价值的信息。之前,我们介绍了一套实时水下系统架构(RTUSAs),可以根据其应用程序和数据大小来处理各种网络配置。我们还介绍了使用有效的数据收集和信息提取方法来满足所需的实时网络架构。水下大数据应用的时间限制。在这项研究中,我们扩展了结果并使用几何分布特征开发了多网关布局拓扑,以满足实时约束。系统性能具有最小的端到端延迟,并降低了功耗。最后,验证了仿真结果,以根据多网关拓扑验证我们系统的性能。

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