NeTS: Small: LayBack: Layered SDN-Based Backhaul Architecture and Optimization Framework for Small Cells and Beyond

NeTS：Small：LayBack：适用于小型蜂窝及其他蜂窝基站的基于 SDN 的分层回程架构和优化框架

• 批准号: 1716121
• 负责人: Martin Reisslein
• 金额: $ 50万
• 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: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2021-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1716121&HistoricalAwards=false
• 关键词: NeTS; Small; LayBack; Layered; SDN

Wireless networks typically connect users with a technology-specific chain of components to the Internet at large. These isolated networking chains limit the resource sharing and optimization across different wireless technologies. The resulting bottlenecks in wireless Internet access stifle a myriad of wireless network applications in our smart-phone based society. For high-speed wireless Internet access it is increasingly important to efficiently utilize and share wireless networking resources across different technologies, e.g., between the cellular wireless and WiFi technologies. This project develops LayBack, a novel Software Defined Networking (SDN)-based layered backhaul access network architecture and novel multi-stage optimization framework. LayBack will judiciously share the wireless resources of multiple technologies, thus fundamentally speeding up wireless Internet access. LayBack can be overlaid in an evolutionary manner on top of existing wireless networks and can thus effectively work with the installed network infrastructure. The project will support the engineering talent pipeline through innovative outreach activities to middle school students in grades six through eight, who will learn network engineering principles through English Language Arts and Physical Education activities. This project seeks to significantly improve the flexibility and efficiency of radio access networks through the LayBack architecture and optimization framework. The intellectual merit contributions of this project include the development of the LayBack wireless access network architecture, which unifies heterogeneous radio access networks and their gateways through a Software Defined Networking (SDN)-based backhaul. The project also develops the LayBack multi-stage optimization framework, which is tightly integrated with the LayBack architecture. The LayBack optimization framework combines a Lyapunov drift-plus-penalty approach with multi-layer decomposition. The proposed optimization framework will be developed and evaluated to account for the different operational time-scales of the LayBack architecture layers. The project will examine specific case studies that exploit the LayBack architecture and optimization framework, e.g., signaling, coexistence of multiple heterogeneous wireless technologies (LTE and WiFi), and optimized content distribution. The broader impacts of this project include the public distribution of a LayBack software package. The project will also include outreach to middle schools (grades 6-8). The outreach activities will be thoroughly evaluated, refined, and distributed.

无线网络通常将具有特定于技术的组件链的用户连接到整个互联网。这些孤立的网络链限制了不同无线技术之间的资源共享和优化。由此产生的无线互联网接入瓶颈扼杀了我们基于智能手机的社会中的无数无线网络应用。对于高速无线互联网接入，跨不同技术有效地利用和共享无线联网资源越来越重要，蜂窝无线和WiFi技术之间的区别。该项目开发了一种基于软件定义网络（SDN）的分层回程接入网络架构和新的多阶段优化框架LayBack。LayBack将明智地共享多种技术的无线资源，从而从根本上加快无线互联网接入。LayBack可以以渐进的方式覆盖在现有的无线网络之上，因此可以有效地与已安装的网络基础设施一起工作。该项目将通过创新的外展活动支持工程人才管道，以六年级到八年级的中学生，他们将通过英语语言艺术和体育活动学习网络工程原理。该项目旨在通过LayBack架构和优化框架显著提高无线接入网络的灵活性和效率。该项目的智力贡献包括开发回退无线接入网络架构，该架构通过基于软件定义网络（SDN）的回程来统一异构无线接入网络及其网关。该项目还开发了与LayBack架构紧密集成的LayBack多阶段优化框架。回退优化框架结合了李雅普诺夫漂移加惩罚方法与多层分解。建议的优化框架将被开发和评估，以考虑不同的操作时间尺度的回退架构层。该项目将研究利用LayBack架构和优化框架的具体案例研究，例如，信令、多种异构无线技术（LTE和WiFi）的共存以及优化的内容分发。这个项目的更广泛的影响包括一个LayBack软件包的公开发行。该项目还将包括对中学（6-8年级）的宣传。将对外联活动进行全面评估、完善和分发。

项目成果

Hardware-Accelerated Platforms and Infrastructures for Network Functions: A Survey of Enabling Technologies and Research Studies

• DOI: 10.1109/access.2020.3008250
• 发表时间: 2020-01-01
• 期刊: IEEE ACCESS
• 影响因子: 3.9
• 作者: Shantharama, Prateek;Thyagaturu, Akhilesh S.;Reisslein, Martin
• 通讯作者: Reisslein, Martin

Multi-layer Decomposition of Optimal Resource Sharing Problems

• DOI: 10.1109/cdc.2018.8619777
• 发表时间: 2018-12
• 期刊: 2018 IEEE Conference on Decision and Control (CDC)
• 作者: Nurullah Karakoç;A. Scaglione;A. Nedić

FedCo: A Federated Learning Controller for Content Management in Multi-party Edge Systems

FedCo：用于多方边缘系统内容管理的联合学习控制器

• DOI: 10.1109/icccn52240.2021.9522153
• 发表时间: 2021
• 期刊: 2021 International Conference on Computer Communications and Networks (ICCCN
• 作者: Balasubramanian, Venkatraman;Aloqaily, Moayad;Reisslein, Martin
• 通讯作者: Reisslein, Martin

Intelligent Resource Management at the Edge for Ubiquitous IoT: An SDN-Based Federated Learning Approach

• DOI: 10.1109/mnet.011.2100121
• 发表时间: 2021-09-01
• 期刊: IEEE NETWORK
• 影响因子: 9.3
• 作者: Balasubramanian, Venkatraman;Alogaily, Moayad;Scaglione, Anna
• 通讯作者: Scaglione, Anna

School fieldtrip to engineering workshop: pre-, post-, and delayed-post effects on student perceptions by age, gender, and ethnicity

• DOI: 10.1080/03043797.2018.1518408
• 发表时间: 2018-09
• 期刊: European Journal of Engineering Education
• 影响因子: 2.3
• 作者: Gamze Ozogul;C. Miller;M. Reisslein