October 25, 2022
Next Generation Networking and its Platform Workshop
China Standard Time (GMT+8)
Location: Virtual
As 5G is being rolled out across the world, wireless researchers are actively developing 6G and WiFi 7 to potentially support Tbps, ultra-low latency, and a wide range of applications. In this workshop, we first present the 6G efforts, including developing smart environments, supporting extreme mobility, and joint sensing and communication.
We then introduce the latest data-centric community research platform on networking (OpenNetLab) and its projects to boost network education and research for emerging mobile and wireless networks.
Speakers
Agenda
| Time (CST) | Session |
|---|---|
| 8:30 AM | Opening Remarks | video (opens in new tab) Lili Qiu, Microsoft Research Asia |
| 8:35 AM | Keynote: A Cloud-based Telecommunications Infrastructure: Business Opportunities and Research Challenges | video (opens in new tab) Victor Bahl, Azure for Operators Abstract: 5G has created an unprecedented opportunity for information technology startups and the established cloud industry to become a part of the next generation telecommunications infrastructure – to radically change it through softwarization, AI and edge computing. I will describe the scientific advances and business needs for bringing us to where we are today and then cast an eye to the future in sharing with the audience a vision for where things are going with telecommunications, including key enablers and potential surprises on the horizon. This will set the context for describing the opportunity ahead for the engineering and research community in the next several years, and beyond, as we stay at the forefront of the modernization that will enable ubiquitous computing via telecommunication networks propelled by innovations in the cloud and edge. I will next move into near-term strategy with Microsoft standing up of a new business division called Azure for Operators (AFO). AFO products are aimed at bringing telecommunications industry into the cloud, as an integral component of Microsoft’s global infrastructure. I will describe the motivation and vision that led to the creation of AFO, its mission, and the significant technical and scientific challenges, which when overcome will lead to the inevitable convergence of two massive industries and new opportunities for established companies, startups, universities and research institutes. |
| Session 1: Emerging 6G mobile networking | |
| 9:10 AM | Research talk: Reconfigurable Metamaterial Surfaces for mmWave and Satellite Networks | video (opens in new tab) Kyle Jamieson, Princeton University Abstract: To support faster and more efficient networks, mobile operators and service providers are bringing 5G millimeter wave (mmWave) networks indoors. However, due to their high directionality, mmWave links are extremely vulnerable to blockage by walls and human mobility. To address these challenges, we exploit advances in artificially-engineered metamaterials, introducing a wall-mounted smart metasurface, called mmWall, that enables a fast mmWave beam relay through the wall and redirects the beam power to another direction when a human body blocks a line-of-sight path. Moreover, our mmWall supports multiple users and fast beam alignment by generating multi-armed beams. We design a real-time system by considering (1) how to design a programmable, metamaterials-based surface that refracts the incoming signal to one or more arbitrary directions, and (2) how to split an incoming mmWave beam into multiple outgoing beams and arbitrarily control the beam energy between these beams. |
| 9:30 AM | Research talk: Low-latency, Real-time Insights from Space | video (opens in new tab) Ranveer Chandra, Microsoft Research Redmond Shadi Noghabi, Microsoft Research Redmond Abstract: More than 80% of the world’s surface does not have Internet connectivity. While multiple companies are commercially bringing broadband connectivity to “people” in remote locations, these solutions are very expensive for Internet of Things (IoT) devices. Over 75B IoT devices are expected by 2025, and the lack of IoT connectivity in 80% of the Earth’s surface is preventing several industries that operate in remote sites, such as Agriculture, Renewables, Fisheries, Supply Chain, etc., from realizing the true potential of data and AI. As a result, a revolution of IoT industry in space has the utmost importance. Several business ventures have already started rolling the wheel. Hundreds of satellites have been launched to date. Although launching satellites has become nondescript nowadays, “IoT in space” brings about unique needs, opportunities, and challenges. In this talk, we will walk you through what today’s “IoT in space” industry looks like and how we can actively shape the future. |
| 9:50 AM | Research talk: Coping with High Mobility for Beyond 5G Cellular Networks | video (opens in new tab) Lili Qiu, Microsoft Research Asia Abstract: The wireless signal propagates via multipath arising from different reflections and penetration between a transmitter and receiver. Extracting multipath profiles (e.g., delay and Doppler along each path) from received signals enables many important applications, such as channel prediction and crossband channel estimation (i.e., estimating the channel on a different frequency). The benefit of multipath estimation further increases with mobility since the channel in that case is less stable and more important to track. Yet high-speed mobility poses significant challenges to multipath estimation. In this talk, instead of using time-frequency domain channel representation, we leverage the delay-Doppler domain representation to accurately extract and predict multipath properties. Specifically, we use impulses in the delay-Doppler domain as pilots to estimate the multipath parameters and apply the multipath information to predicting wireless channels as an example application. Our design rationale is that mobility is more predictable than the wireless channel since mobility has inertial while the wireless channel is the outcome of a complicated interaction between mobility, multipath, and noise. We evaluate our approach via both acoustic and RF experiments, including vehicular experiments using USRP. Our results show that the estimated multipath matches the ground truth, and the resulting channel prediction is more accurate than the traditional channel prediction schemes. |
| Session 2: New platform for emerging mobile and wireless networks | |
| 10:10 AM | Research talk: Enhance Networking Education with OpenNetLab | video (opens in new tab) Ye Tian, University of Science and Technology of China Chen Tian, Nanjing University Abstract: Networking Education at university is a critical topic for the community to raise talents in the network industry and research. However, the velocity of the development of this area is super-fast. Building and updating a networking teaching and experiment platform are challenging for a university individually. OpenNetLab, a community for open networking research with 10+ university members in Asia, is working together to build an ecology for networking education. It enables university professors and teaching assistants in the networking area to take advantage of the community infrastructure and platform for teaching and contribute their resources to the community. Last year, we successfully tested our OpenNetLab Education v1.0 at Nanjing university with 200+ students. Now, we are working on the design and implementation of v2.0 at USTC and Nanjing University. This talk will introduce the vision and the latest effort from the OpenNetLab community. |
| 10:30 AM | Research talk: OpenNetLab: An Open Platform for RL-based Congestion Control for Real-Time Communication | video (opens in new tab) Byung-Gon Chun, Seoul National University Abstract: With the importance of real-time communications (RTC), much attention is being paid to designing congestion control (CC) algorithms for RTC to achieve high Quality of Experience. In this talk, we introduce a project on OpenNetLab that provides system-level support for training and testing Reinforcement Learning(RL)-based CC algorithms for RTC. OpenNetLab supports diverse environments ranging from simulators to real-world testbeds, in which one can design and experiment with her RL-based CC algorithms by exploring tradeoffs in the design space. Early use cases demonstrate that OpenNetLab facilitated coming up with new RL-based CC algorithms that outperform widely used rule-based baselines. |
| 10:50 | Research talk: Network Stack in the Cloud Hong Xu, The Chinese University of Hong Kong Abstract: As cloud computing becomes ubiquitous, the network stack in this virtualized environment is becoming a focal point of research with unique challenges and opportunities. From an architectural perspective, the network stack remains a part of the guest OS inside a VM in the cloud. I will argue that this legacy architecture is becoming a barrier to innovation/evolution. The tight coupling between the network stack and the guest OS causes many deployment troubles to tenants and management and efficiency problems to the cloud provider. I will present our vision of providing the network stack as a service as a way to address these issues. The idea is to decouple the network stack from the guest OS, and offer it as an independent entity implemented by the cloud provider. I will discuss the design and evaluation of a concrete framework called NetKernel to enable this vision. |
| Session 3: Panel Discussion (30 minutes) | video (opens in new tab) | |
| 11:10 AM | We will have a broad discussion on new generation networks (6G, Wi-Fi 7) and the research platform for the new networks. With the new networks, can we achieve other scenarios? What are the challenges to enabling the new networks? Can our current data-centric networking research be applied to the new networks? What are the software and hardware requirements for the new networks? What are the challenges and opportunities for the research platform? Host: Yongqiang Xiong, Microsoft Research Asia Panelists: Lili Qiu, Microsoft Research Asia Mo Li, Nanyang Technological University Chenren Xu, Peking University Hong Xu, The Chinese University of Hong Kong Chen Tian, Nanjing University Ye Tian, University of Science and Technology of China |
Workshop organizers
Zhixiong Niu (Chair), Microsoft Research Asia
Lili Qiu (Chair), Microsoft Research Asia
Beibei Shi (Chair), Microsoft Research Asia
Peng Cheng, Microsoft Research Asia
Yongqiang Xiong, Microsoft Research Asia
Weizhe Shi, Microsoft Research Asia
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