NeTS: Small: FreeNet: Cognitive Wireless Networking Powered by Green Energy

NetS：小型：FreeNet：绿色能源驱动的认知无线网络

• 批准号: 1320468
• 负责人: Nirwan Ansari
• 金额: $ 49.99万
• 依托单位: New Jersey Institute of Technology
• 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: 2013-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1320468&HistoricalAwards=false
• 关键词: NeTS; Small; FreeNet; Cognitive; Wireless

The project aims to liberate wireless access networks currently constrained by spectral and energy scarcity via a new framework, referred to as FreeNet, by exploiting cognitive networking and green energy. FreeNet will be designed and optimized using a series of novel techniques such as dynamic network architecture optimization, network resource aware traffic scheduling, and spectrum sharing. The network architecture optimization framework will apply advanced probability theory to investigate inherent relationships between the optimal network architecture and the availability of spare spectrum and green energy, and adopt control theory to adapt the network architecture according to the dynamics of the spare spectrum and green energy. The network resource aware traffic scheduling and spectrum sharing algorithms will be designed based on optimization theory. Finally, theoretical analysis will be reduced to practice and translated into communications protocols in enabling and prototyping FreeNet. The theoretical analysis will elicit a series of theorems to direct the utilization of green energy in communication networks. The communication protocols design and FreeNet prototyping will provide guidelines for designing resource aware communication systems. The research activities will advance the understanding of inherent relationships among the network architecture, traffic scheduling, spectrum utilization, and energy consumption. FreeNet will be deployed for offloading mobile traffic in urban areas, delivering content in rural areas, and enhancing emergency communication capacity during natural disasters. FreeNet will improve the availability and capacity of wireless networks, broaden the benefits of wireless networking, and enhance the living environment, the earth, by reducing the release of carbon footprints. Research outcomes from this project will be disseminated via publications and a website with frequent updates. Other broader impacts include integration of research and education through participation of both undergraduate and graduate students in the project, incorporation of research outcomes into course work, interactions and exchanges with invited speakers, and seeking involvement of REU students and under-represented groups.

该项目旨在通过利用认知网络和绿色能源，通过一个称为FreeNet的新框架，解放目前受频谱和能源短缺限制的无线接入网络。FreeNet将使用一系列新技术进行设计和优化，如动态网络架构优化、网络资源感知流量调度和频谱共享。网络架构优化框架将应用先进的概率理论来研究最优网络架构与备用频谱和绿色能量可用性之间的内在关系，并根据备用频谱和绿色能量的动态采用控制理论来适应网络架构。基于最优化理论设计了网络资源感知的业务调度和频谱共享算法。最后，理论分析将被简化为实践，并转化为FreeNet的启用和原型设计中的通信协议。通过理论分析，将得出一系列定理，指导绿色能源在通信网络中的应用。通信协议设计和FreeNet原型将为设计资源感知通信系统提供指导。研究活动将促进对网络架构、流量调度、频谱利用率和能耗之间内在关系的理解。FreeNet将用于卸载城市地区的移动的流量，在农村地区提供内容，并增强自然灾害期间的应急通信能力。FreeNet将提高无线网络的可用性和容量，扩大无线网络的好处，并通过减少碳足迹的释放来改善地球的生活环境。该项目的研究成果将通过出版物和经常更新的网站传播。其他更广泛的影响包括通过本科生和研究生参与该项目，将研究成果纳入课程工作，与受邀演讲者的互动和交流，以及寻求REU学生和代表性不足的群体的参与来整合研究和教育。