NeTS: Small: Resilient and Efficient Data Access in Cognitive Radio Networks

NeTS：小型：认知无线电网络中弹性且高效的数据访问

• 批准号: 1320278
• 负责人: Guohong Cao
• 金额: $ 46.08万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1320278&HistoricalAwards=false
• 关键词: NeTS; Small; Resilient; Efficient; Data

In cognitive radio networks, to avoid interference with licensed users, unlicensed users must vacate the spectrum accessed by the primary users. Since it takes some time for the unlicensed users to detect and switch to other available spectrum, the ongoing data transmission may have to be interrupted, leading to poor data access performance. Although there is a lot of research on cognitive radio networks, not much work has been done on data access. This project focuses on three intertwined issues to support resilient and efficient data access: (i) Various topology control protocols which carefully assign communication channels considering network robustness and channel interference to achieve better data accessibility, are designed and evaluated; (ii) Delay-constrained caching techniques are introduced to deal with primary user appearance, where data is cached/replicated at appropriate nodes to statistically limit the data access delay; (iii) Spectrum-aware data replication schemes are designed to improve data access performance in intermittently connected cognitive radio networks, by considering both node mobility pattern and primary user appearance. This project will make significant theoretical and technological advances in understanding and supporting resilient and efficient data access in cognitive radio networks. The success of this project is likely to have a broader impact on making cognitive radio networks more affordable and amenable to commercial, civilian, and military applications. The results of the project will be disseminated widely through high quality publications and presentations. The proposed research will also be integrated with the education curricula at the Pennsylvania State University.

在认知无线电网络中，为了避免对授权用户的干扰，非授权用户必须腾出主用户接入的频谱。由于未经许可的用户需要一些时间来检测并切换到其他可用频谱，因此正在进行的数据传输可能不得不中断，导致数据访问性能较差。虽然有很多关于认知无线电网络的研究，但在数据访问方面做的工作还很少。本项目关注三个相互交织的问题，以支持弹性和高效的数据访问：(I)设计和评估了各种拓扑控制协议，这些协议在考虑网络健壮性和信道干扰的情况下仔细分配通信信道，以实现更好的数据可访问性；(Ii)引入延迟受限的缓存技术来处理主用户外观，其中数据被缓存/复制到适当的节点以从统计上限制数据访问延迟；(Iii)频谱感知数据复制方案旨在通过同时考虑节点移动模式和主用户外观来提高间歇连接认知无线电网络的数据访问性能。该项目将在理解和支持认知无线电网络中弹性和高效的数据访问方面取得重大的理论和技术进步。该项目的成功可能会对认知无线电网络产生更广泛的影响，使其更负担得起，更适合商业、民用和军事应用。该项目的成果将通过高质量的出版物和专题介绍广泛传播。拟议的研究还将与宾夕法尼亚州立大学的教育课程相结合。