Collaborative Research: WiFiUS: Heterogeneous Resource Allocation for Hierarchical Software-Defined Radio Access Networks at the Edge

合作研究：WiFiUS：边缘分层软件定义无线电接入网络的异构资源分配

• 批准号: 1457262
• 负责人: Guoliang Xue
• 金额: $ 14万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-03-15 至 2017-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1457262&HistoricalAwards=false
• 关键词: Collaborative; Research; WiFiUS; Heterogeneous; Resource

Wireless cellular infrastructure is becoming dense and heterogeneous. Software-defined networking has brought new opportunities for enhancing network planning and administration. When applied in geographically large-scale radio access networks, software-defined networking suffers from scalability and survivability problems due to high centralization. In this project, a hierarchical software-defined radio access network architecture is designed. In contrast to a flat version of software defined radio access networks, which have large control overhead and system latency for large scaled networks, the proposed scheme offers reduced control overhead and system latency by exploration locality, thereby enhancing system scalability. In addition, the tree structure of the hierarchical design can easily deal with single points of failure. The plan is to first investigate the architecture design of the hierarchical software-defined radio access network, the protocol design for the control network, survivability, and locality and optimization, followed by large-scale elastic approaches, machine learning based approaches, and matching theory based approaches for network-wide resource allocation. The intellectual merit originates from the interdisciplinary fusion of different technologies including software-defined networking, wireless communications, software-defined radio, machine learning, and game theory. The research plan addresses challenging issues of coexistence of interfering clusters and elastic resource allocation for a large-scale radio access networks, while developing theoretically novel frameworks to tackle these challenges. This research will lead to simpler and more efficient resource allocation schemes for wireless networks by exploring the power of software-defined networks. The transformative and interdisciplinary project involves a complementary mix of network architecture design, theoretical modeling and analysis, and experimental simulations quantifying performance benefits. The outcomes will be made available to the research community through high quality journal articles and conference presentations which may be used by industrial entities for network development and future industrial standardization. This project will strengthen collaboration in the research field of wireless communication between the United States and Finland. The proposed research activities will complement and enrich the growing curriculum on game theory and optimization at the University of Houston and Arizona State University through course development and special topic seminars. Highly skilled personnel in related areas will be trained in carrying out the proposed research tasks. Special efforts will be made to engage minority and underrepresented groups, including African-American, Hispanic and female graduate students. K-12 outreach is also planned so as to motivate high school students in science and engineering.

无线蜂窝基础设施正在变得密集和异构。软件定义网络为加强网络规划和管理带来了新的机遇。当应用于地理上大规模的无线接入网络时，软件定义网络由于高度集中而面临可扩展性和生存性问题。 在该项目中，设计了分层软件定义的无线接入网络架构。与软件定义无线电接入网络的扁平版本相比，该网络对于大规模网络具有较大的控制开销和系统延迟，所提出的方案通过探索局部性来减少控制开销和系统延迟，从而增强系统可扩展性。另外，树形结构的分层设计可以轻松应对单点故障。该计划首先研究分层软件定义无线电接入网络的架构设计、控制网络的协议设计、生存性、局部性和优化，然后研究大规模弹性方法、基于机器学习的方法以及基于匹配理论的全网资源分配方法。智力价值源于不同技术的跨学科融合，包括软件定义网络、无线通信、软件定义无线电、机器学习和博弈论。该研究计划解决了干扰集群共存和大规模无线接入网络的弹性资源分配等具有挑战性的问题，同时开发了理论上新颖的框架来应对这些挑战。这项研究将通过探索软件定义网络的力量，为无线网络带来更简单、更高效的资源分配方案。这个变革性的跨学科项目涉及网络架构设计、理论建模和分析以及量化性能优势的实验模拟的互补组合。研究成果将通过高质量的期刊文章和会议演示向研究界提供，工业实体可以将其用于网络开发和未来的工业标准化。该项目将加强美国和芬兰之间在无线通信研究领域的合作。拟议的研究活动将通过课程开发和专题研讨会补充和丰富休斯顿大学和亚利桑那州立大学不断增长的博弈论和优化课程。相关领域的高技能人才将接受培训以执行拟议的研究任务。我们将特别努力吸引少数群体和代表性不足的群体，包括非裔美国人、西班牙裔和女性研究生。还计划开展 K-12 外展活动，以激励高中生学习科学和工程。