III: Large: Collaborative Research: Moving Objects Databases for Exploration of Virtual and Real Environments
III: Large: Collaborative Research: Moving Objects Databases for Exploration of Virtual and Real Environments
批准号:
1212508
负责人:
Roberto Tamassia
金额:
$25.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-10-01 至 2018-09-30
中文摘要
佛罗里达国际大学(IIS-1213026)、伊利诺伊大学芝加哥分校(IIS-1213013)、布朗大学(IIS-1212508)和西北大学(IIS-1213038)的研究人员正在开发一种高性能模型,用于移动环境中的信息处理和融合,提供真实世界和虚拟世界之间的协作集成。该模型适用于计算交通和移动传感领域,可以查询和可视化移动对象数据(MOD)及其与静态和动态地理空间数据的关系。研究项目解决以下问题:平衡进入MOD服务器的基于位置的数据流的处理与可视化相关查询的有效处理;确定查询/任务在多个区域服务器之间的最佳分布;在有效管理对象数据和查询方面最大化预测技术的可扩展性;建模数据不确定性;在不同比例尺缩放时,将地图概化与轨迹数据约简相结合;解决隐私和安全问题;并支持语义查询。TerraFly测试平台(http://TerraFly.fiu.edu)是一个公共地理信息系统(GIS)地图引擎和基于位置的数据存储库。这项工作探索了将真实世界和虚拟世界结合起来的新步骤,这是一个新兴的研究前沿。人们对虚拟世界的理解相对较好,但现实与虚拟的结合带来了巨大的挑战,并有望带来具有高潜在回报的变革性结果,包括车载导航系统、大量移动传感器、自动导航车辆、态势指挥和基于位置的服务。在推进计算机科学的同时,该项目还利用了NSF、NASA、DoI、DoT、DHS和其他利益相关者(如NSF EarthCube项目)的预先投资,并为其提供直接利益。通过提高空间、时间和移动对象数据管理的效率,并通过TerraFly、EarthCube和其他场所将这些结果提供给选民,该项目将产生社会效益。该项目为提高灾害管理、环境监测、交通、教育和物流等多个应用领域的服务质量奠定了基础。由此产生的技术可以作为推进自动导航车辆、机器人和移动传感器研究的基础。特别是,这项工作促进了知情旅行者计划、动态导航、态势控制和机载观测系统等技术的发展。该项目为来自合作院校的学生提供了丰富的教育和研究机会,包括代表性不足的学生。此外,还开发了教育模块,并将研究成果纳入课程扩展。更多信息请访问项目网站(http://CAKE.fiu.edu/MOD)。
英文摘要
Researchers at Florida International University (IIS-1213026), University of Illinois at Chicago (IIS-1213013), Brown University (IIS-1212508), and Northwestern University (IIS-1213038) are developing a high-performance model for information processing and fusion in mobile environments, providing a collaborative integration between the real and virtual worlds. This model, applicable to the fields of computational transportation and mobile sensing, enables querying and visualization of moving objects data (MOD) and their relationship to static and dynamic geospatial data. Research project addresses the issues of: balancing the processing of location-based data streams coming into MOD servers with efficient processing of visualization-related queries; determining optimal distribution of queries/tasks among multiple regional servers; maximizing the scalability of prediction techniques in terms of efficient management of objects' data and queries; modeling data uncertainty; coupling map generalization with trajectories' data reduction when zooming across different scales; resolving issues of privacy and security; and enabling semantic querying. A demonstration of the outcomes is available within the TerraFly testbed (http://TerraFly.fiu.edu) -- a public Geographic Information System (GIS) mapping engine and location-based data repository.This work explores the novel steps towards combining the real and virtual worlds, an emerging research frontier. The virtual world is relatively well understood, but the combination of the real and virtual poses great challenges and promises transformative results with high potential payoff, including in-car navigation systems, massive fleets of mobile sensors, self-navigating vehicles, situation command, and location-based services. While advancing Computer Science, the project also leverages prior investment of, and provides direct benefit to, NSF, NASA, DoI, DoT, DHS, and other stakeholders such as the NSF EarthCube project. By improving the efficiency of spatial, temporal, and moving object data management and making these results available to constituencies via TerraFly, EarthCube and other venues, the project will produce societal benefits. This project provides a foundation for improving the quality of services in multiple applications such as disaster management, environmental monitoring, transportation, education, and logistics. The resulting technologies may serve as a base to advance research on self-navigating vehicles, robots, and mobile sensors. In particular, this work facilitates the technologies of Informed Traveler Programs, dynamic navigation, situation control, and airborne observational systems. The project provides rich educational and research opportunities for students from the collaborating institutions -- including underrepresented students. In addition, educational modules are developed, and research results will be incorporated in curriculum expansions. Further information is available at the project's website (http://CAKE.fiu.edu/MOD).
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Bypassing holes in sensor networks: Load-balance vs. latency
绕过传感器网络中的漏洞:负载平衡与延迟
DOI:
10.1016/j.adhoc.2017.03.002
发表时间:
2017
期刊:
Ad Hoc Networks
影响因子:
4.8
作者:
[Zhou, Fan, Trajcevski, Goce, Tamassia, Roberto, Avci, Besim, Khokhar, Ashfaq, Scheuermann, Peter]
通讯作者:
Scheuermann, Peter
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