NeTS: Small: LayBack: Layered SDN-Based Backhaul Architecture and Optimization Framework for Small Cells and Beyond
PIs: Martin Reisslein and Anna Scaglione
Supported by National Science Foundation (NSF), Directorate for Computer & Information Science & Engineering (CISE), Division of Computer and Network Systems (CNS), Award Number 1716121, 10/01/2017 – 11/30/2021.
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.
- Nurullah Karakoc, Anna Scaglione, Martin Reisslein, and Ruiyuan Wu. Federated Edge Network Utility Maximization for a Multi-Server System: Algorithm and Convergence, IEEE/ACM Transactions on Networking, second revised submission under review, ():-, 2022.
- Venkatraman Balasubramanian, Moayed Aloqaily, Martin Reisslein, and Anna Scaglione. Intelligent Resource Management at the Edge for Ubiquitous IoT: An SDN-Based Federated Learning Approach, IEEE Network, 35(5):114-121, September/October 2021.
- Venkatraman Balasubramanian, Moayed Aloqaily, and Martin Reisslein. FedCo: A Federated Learning Controller for Content Management in Multi-party Edge Systems, Proc. IEEE International Conference on Computer Communications and Networks (ICCCN), pages 1-9, July 2021.
- Prateek Shantharama, Akhilesh Thyagaturu, Anil Yatavelli, Poornima Lalwaney, Martin Reisslein, Georgii Tkachuk, and Edward J. Pullin. Hardware Acceleration for Container Migration on Resource-Constrained Platforms, IEEE Access, 8:175070-175085, 2020.
- Nurullah Karakoc, Anna Scaglione, Angelia Nedic, and Martin Reisslein. Multi-Layer Decomposition of Network Utility Maximization Problems, IEEE/ACM Transactions on Networking, 28(5):2077-2091, October 2020.
- Prateek Shantharama, Akhilesh Thyagaturu, and Martin Reisslein. Hardware-Accelerated Platforms and Infrastructures for Network Functions: A Survey of Enabling Technologies and Research Studies, IEEE Access, 8:132021-132085, 2020.
- Gamze Ozogul, Akhilesh Thyagaturu, Martin Reisslein, and Anna Scaglione. Physical Education and English Language Arts Based K-12 Engineering Outreach in Software Defined Networking (Extended Version), arXiv:2006.05545, June 2020.
- Cuiyu Kong, Bhaskar P. Rimal, Martin Reisslein, Martin Maier, Islam S. Bayram, and Michael Devetsikiotis. Cloud-Based Charging Management of Heterogeneous Electric Vehicles in a Network of Charging Stations: Price Incentive vs. Capacity Expansion, IEEE Transactions on Services Computing, in print, 2021.
- Mu Wang, Nurullah Karakoc, Lorenzo Ferrari, Prateek Shantharama, Akhilesh Thyagaturu, Martin Reisslein, and Anna Scaglione. A Multi-Layer Multi-Timescale Network Utility Maximization Framework for the SDN-Based LayBack Architecture Enabling Wireless Backhaul Resource Sharing, Electronics, 8(9):937.1-937.28, September 2019.
- Gamze Ozogul, Cindy Faith Miller, and Martin Reisslein. School Fieldtrip to Engineering Workshop: Pre-, Post-, and Delayed-Post Effects on Student Perceptions by Age, Gender, and Ethnicity, European Journal of Engineering Education, 44(5):745-768, 2019.
- Nurullah Karakoc, Anna Scaglione, and Angelia Nedic. Multi-layer Decomposition of Optimal Resource Sharing Problems, In Proceedings IEEE Conference on Decision and Control (CDC), 178-183, December 2018.
- Prateek Shantharama, Akhilesh Thyagaturu, Nurullah Karakoc, Lorenzo Ferrari, Martin Reisslein, and Anna Scaglione. LayBack: SDN Management of Multi-access Edge Computing (MEC) for Network Access Services and Radio Resource Sharing, IEEE Access, 6:57545-57561, 2018.
- Lorenzo Ferrari, Nurullah Karakoc, Anna Scaglione, Martin Reisslein, and Akhilesh Thyagaturu, Layered Cooperative Resource Sharing at a Wireless SDN Backhaul, Proc. IEEE International Conference on Communications Workshops (ICC Workshops), International Workshop on 5G Architecture (5GARCH), pages 1-6, Kansas City, MO, May 2018.
- The LayBack code base is available as open-source software from https://github.com/athygat/layback.
- The related Federated Edge Network Utility Maximization (FEdg-NUM) code is available from https://github.com/nurullahkarakoc/Simulations-ML-FEDG-NUM.
- Additional code for simulating the layered cooperative resource sharing at a wireless SDN backhaul is available from https://github.com/nurullahkarakoc/code_ICC.