NeTS-NOSS: Sensor Networks for Undersea Seismic Experimentation (SNUSE)
NeTS-NOSS: Sensor Networks for Undersea Seismic Experimentation (SNUSE)
批准号:
0435517
负责人:
John Heidemann
金额:
$0.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-09-15 至 2009-08-31
中文摘要
摘要:传感器网络目前已广泛应用于野外和建筑领域,但其在水下的应用却相当有限。海底传感器网络要么基于昂贵的有线设备,要么基于少量相对较大的远程声学通信节点。用于海底地震实验的传感器网络(SNUSE)项目正在开发支持小型、低成本、无线海底传感器节点的基本工具。通过实验室和测试平台的实验和模拟,该项目研究:-用于水下传感器节点的小型,低功耗,中等范围声学遥测的硬件;-时间同步、定位和高能效MAC协议,适用于高延迟、声学通信环境;—超低占空比的应用协议,包括长时间的睡眠和唤醒,高效的应用级数据缓存和转发。该工作可直接应用于海底传感,包括污染物和污染监测、海底微、宏观生物生命跟踪、海底油田地震监测等。虽然主要集中在海底应用,但很大一部分研究也适用于传统的传感器网络。这项工作支持南加州大学的本科生和研究生的研究,无论是直接的还是通过传感器网络实验课和智能油田技术的CiSoft硕士学位。这项工作的结果将通过技术文件、免费提供的硬件设计和项目网站上的软件传播。
英文摘要
Abstract: Sensor networks are today being deployed in scientific applications in fields and buildings, but their use underwater has been quite limited. Undersea sensor networks are either based on expensive wired devices or a small number of relatively large nodes with long-range acoustic communications. The Sensor Networks For Undersea Seismic Experimentation (SNUSE) project is developing fundamental tools to support small, low-cost, wireless undersea sensor nodes. With laboratory and testbed experimentation and simulation, the project investigates:- Hardware for small, low-power, moderate-range acoustic telemetry for underwater sensor nodes;- Time synchronization, localization, and energy-efficient MAC protocols for environments with high-delay, acoustic communication;- Applications protocols for ultra-low duty cycle operation, including long-duration sleep and wakeup and efficient application-level data caching and forwarding.This work is directly applicable to applications in undersea sensing, including contaminant and pollution monitoring undersea micro- and macro-organism -life tracking, and seismic monitoring of undersea oil fields. Although focused on undersea applications, a large portion of the research is also applicable to traditional sensor networks. This work supports undergraduate and graduate research at USC, both directly and through sensor networking laboratory classes and the developing CiSoft Masters Degree in Smart Oil-field technology. The results of this work will be disseminated via technical papers, freely available hardware designs and software on the project web site.
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会议论文
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