NeTS-FIND: Collaborative Research: Network Fabric for Personal, Social, and Urban Sensing Applications
NeTS-FIND: Collaborative Research: Network Fabric for Personal, Social, and Urban Sensing Applications
批准号:
0627084
负责人:
Mani Srivastava
金额:
$0.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-09-01 至 2011-08-31
中文摘要
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英文摘要
This project is investigating the impact on the network architecture of a new class of applications involving embedded sensing technology as it moves from scientific, engineering, defense, and industrial contexts to the wider personal, social and urban contexts. These applications draw on sensed information about people, objects, and physical spaces to enable new kinds of social exchange and offer new and unexpected views of our communities. They require new algorithms and software mechanisms because unlike scientific applications of distributed sensing, a single system is widely distributed, intermittently connected, and privately administered; and unlike traditional Internet applications the physical inputs are critical to the behavior. The project is developing principles and abstractions that are vital for the future Internet to incorporate such applications, to identify the network fabric architecture options, and to develop the key components and services to realize them. These include network services for context verification and resolution control to enable privacy-aware and verifiable sensing, and application services for naming, dissemination, and aggregation of sensed data. In addition, the project is developing concrete instances of personal, social and urban embedded networked sensing applications to act as design drivers for the broader community of researchers architecting the new Internet core, as well tools to assist in application authoring. Broader Impact: Ultimately, this research will yield fundamental understanding of software architectures, networking models and data processing techniques that are needed to support a citizenry actively participating in collection, sharing, and interpretation of physical sensor data in the public sphere at multiple scales.
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