IEEE INFOCOM 2023

Program at a Glance

IEEE INFOCOM 2023

Session Keynote: Opening, Awards, and Keynote

Session Break-1-Day1: Coffee Break Session Lunch-Day1: Conference Lunch Session Dinner-Day1: Chartered Cruise Dinner (for attendees with Full Conference Registrations)

Session A-1: Cloud/Edge Computing 1 Session A-2: Wireless/Mobile Learning Session A-3: Security and Privacy

Session B-1: Federated Learning 1 Session B-2: Federated Learning 2 Session B-3: Federated Learning 3

Session C-1: LoRa and LPWAN Session C-2: Satellite/Space Networking Session C-3: Internet Routing

Session D-1: mmWave 1 Session D-2: mmWave 2 Session D-3: mmWave 3

Session E-1: Video Streaming 1 Session E-2: Video Streaming 2 Session E-3: Video Streaming 3

Session F-1: Datacenter and Switches Session F-2: Memory/Cache Management 1 Session F-3: Internet Measurement

Session G-1: Theory 1 Session G-2: Theory 2 Session G-3: 5G

Session Demo-1: Demo Session 1

Session Demo-1

Demo Session 1

Conference

3:30 PM — 5:30 PM EDT

Local

May 17 Wed, 12:30 PM — 2:30 PM PDT

Location

Babbio Lobby

Demo Abstract: Scaling Out srsRAN Through Interfacing Wirelessly srsENB With srsEPC

Neha Mishra, Yamini V Iyengar, Akshay C. Raikar, Nikitha Thomas and Sabarish Krishna Moorthy (University at Buffalo, USA); Jiangqi Hu (University of Buffalo, USA); Zhiyuan Zhao and Nicholas Mastronarde (University at Buffalo, USA); Elizabeth Serena Bentley (AFRL, USA); Michael Medley (US Air Force Research Laboratory/Information Directorate & SUNY Polytechnic Institute, USA); Zhangyu Guan (University at Buffalo, USA)

Software radio suite Radio Access Network (srsRAN) has been widely used in experimental research for 5G, 6G and their evolutions. However, in the current implementation of srsRAN, the Evolved Node B (srsENB) and Evolved Packet Core (srsEPC) are interfaced through wired connections, which makes it challenging to conduct experiments with mobile srsENBs and dynamic association between User Equipment (srsUE) and srsENB in future wireless networks. To address this challenge, we propose to interface srsENB and srsEPC by allowing srsENB to interface with srsEPC through wireless links and hence enabling easy integration of multiple possibly mobile srsENBs in experimental research. We show the effectinveness and scalability of the new srsRAN architecture through two demonstrations: (i) srsUE-srsENB connection establishment; (ii) srsUE handover between two srsENBs wirelessly interfaced with the same srsEPC.

Speaker Jiangqi Hu; Zhangyu Guan

Dr. Guan is an Assistant Professor with the Department of Electrical Engineering (EE) at The State University of New York at Buffalo. He received his Ph.D. in Communication and Information Systems from Shandong University in China in 2010. He was a visiting Ph.D. student with the Department of EE, SUNY Buffalo, from 2009 to 2010. He also worked there as a Postdoc from 2012 to 2014. After that, he worked as an Associate Research Scientist with the Department of ECE at Northeastern University in Boston, MA, from 2015 to 2018. Dr. Guan is the director of the Wireless Intelligent Networking and Security (WINGS) Lab at SUNY Buffalo, with research interests including programmable networks, spectrum coexistence, wireless multimedia networks, and wireless security.

Accelerating BLE Neighbor Discovery via Wi-Fi Fingerprints

Tong Li, Bowen Hu, Guanjie Tu and Jinwen Shuai (Renmin University of China, China); Jiaxin Liang (Huawei Technologies, China); Yukuan Ding (Hong Kong University of Science and Technology, Hong Kong); Ziwei Li and Ke Xu (Tsinghua University, China)

In this paper, we demonstrate the design of FiND, a novel neighbor discovery protocol that accelerates BLE neighbor discovery via Wi-Fi fingerprints without any hardware modifications. The design rationale of FiND is that the two modes of Wi-Fi and BLE show complementarity in both wireless interference and discovery pattern. When abstracting the neighbor discovery problem, this demonstration provides validation for the approach of reasoning-based presence detection in the real world.

Speaker

Speaker biography is not available.

A Multi-Agent Deep Reinforcement Learning Approach for RAN Resource Allocation in O-RAN

Farhad Rezazadeh (UPC & CTTC, Spain); Lanfranco Zanzi (NEC Laboratories Europe, Germany); Francesco Devoti (NEC Laboratories Europe GmbH, Germany); Sergio Barrachina-Muñoz (Centre Tecnològic Telecomunicacions Catalunya, Spain); Engin Zeydan (Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Spain); Xavier Costa-Perez (ICREA and i2cat & NEC Laboratories Europe, Spain); Josep Mangues-Bafalluy (Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Spain)

Artificial intelligence (AI) and Machine Learning (ML) are considered as key enablers for realizing the full potential of fifth-generation (5G) and beyond mobile networks, particularly in the context of resource management and orchestration. In this demonstration, we consider a fully-fledged 5G mobile network and develop a multi-agent deep reinforcement learning (DRL) framework for RAN resource allocation. By leveraging local monitoring information generated by a shared gNodeB instance (gNB), each DRL agent aims to optimally allocate radio resources concerning service-specific traffic demands belonging to heterogeneous running services. We perform experiments on the deployed testbed in real-time, showing that DRL-based agents can allocate radio resources fairly while improving the overall efficiency of resource utilization and minimizing the risk of over provisioning.

Speaker Sergio Barrachina-Muñoz

Sergio Barrachina-Muñoz (Barcelona, 1991) holds a PhD in Information and Communication Technologies (2021) by Universitat Pompeu Fabra (UPF), Barcelona, Spain. Previously, he received his BSc Degree in Telematics Engineering (2015) and MSc in Intelligent Interactive Systems (2016), also from UPF. Sergio joined the Wireless Networking Research Group as in 2015, where he developed his thesis on autonomous learning techniques for improving next-generation Wi-Fi networks through efficient spectrum access. Sergio is currently working as a postdoctoral researcher in the Services as Networks research unit at Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), where he is primarily focused on building 5G/6G testbeds, including cloud-native and edge computing deployments.

Enabling CBRS Experimentation through an Open SAS and SDR-based CBSD

Oren R Collaco (Commonwealth Cyber Initiative Virginia Tech, USA); Mayukh Roy Chowdhury (Virginia Tech, USA); Aloizio Pereira Da Silva (Virginia Tech, USA & Commonwealth Cyber Initiative, USA); Luiz DaSilva (Virginia Tech, USA & Trinity College Dublin, Ireland)

The increased demand for spectrum has motivated the Federal Communications Commission (FCC) to open band 48, also known as the Citizen Broadband Radio Service (CBRS) band, for shared wireless broadband use. Access and operations in the CBRS band is managed by a dynamic Spectrum Access System (SAS) that enables seamless spectrum sharing between incumbent and secondary users. In this paper, we demonstrate an enhanced version of an open source SAS, OpenSAS, with added functionality to showcase interaction between General Authorized Access (GAA) and Priority Access License (PAL) user tiers. We further showcase the use of the Google SAS Test Environment with OpenSAS and a Software-defined Radio (SDR)-based CBRS Base Station Device (CBSD) developed by our team. Our demo steps through the entire SAS-CBSD cycle which includes registration, spectrum inquiry, grant request, heartbeat request, grant relinquishment, and de-registration.

Speaker

Speaker biography is not available.

RIC-O: An Orchestrator for the Dynamic Placement of a Disaggregated RAN Intelligent Controller

Gustavo Zanatta Bruno (UNISINOS, Brazil); Vikas Krishnan Radhakrishnan (Virginia Tech, USA); Gabriel Almeida (Universidade Federal de Goiás, Brazil); Alexandre Huff (Federal Technological University of Parana, Brazil); Aloizio Pereira Da Silva (Virginia Tech, USA & Commonwealth Cyber Initiative, USA); Kleber V Cardoso (Universidade Federal de Goiás, Brazil); Luiz DaSilva (Virginia Tech, USA & Trinity College Dublin, Ireland); Cristiano Bonato Both (Unisinos University, Brazil)

In this demonstration, we present the RIC Orchestrator (RIC-O), a system that optimizes the deployment of Near Real-time RAN Intelligent Controller (Near-RT RIC) components across cloud and edge environments. RIC-O quickly and efficiently adapts to sudden changes and redeploys components as needed. We describe small-scale real-world experiments using RIC-O and a disaggregated Near-RT RIC within a Kubernetes deployment to demonstrate its effectiveness.

Speaker

Speaker biography is not available.

Remote Detection of 4G/5G UEs Vulnerable to Stealthy Call DoS

Man-Hsin Chen, Chiung-I Wu, Yin-Chi Li and Chi-Yu Li (National Yang Ming Chiao Tung University, Taiwan); Guan-Hua Tu (Michigan State Unversity, USA)

Nowadays, all the 4G/5G voice solutions are offered by the IMS (IP Multimedia Subsystem) system. They include 4G VoLTE (Voice over LTE) and 5G VoNR (Voice over New Radio), as well as a non-3GPP access solution, VoWiFi (Voice over WiFi). Since VoWiFi is implemented on mobile OS, instead of the modem with hardware security for VoLTE and VoNR, it can be a vulnerability of the IMS system and may further impair other IMS-based services. It has been exposed that due to vulnerable VoWiFi sessions, several IMS vulnerabilities are discovered and the smartphones with IMS-based call services may suffer from a stealthy call DoS attack, where the smartphones cannot make or receive any calls and no ringtone or messages are appeared on them during the attack. In this paper, we develop a detector that can remotely and concurrently detect such DoS attack for multiple UEs (User Equipments). It consists of three major components: session hijacking, SIP fabrication, and call detection. We demonstrate its effectiveness in the operational networks of two carriers from different countries by considering three different phone models with VoLTE and VoWiFi call services.

Speaker Man-Hsin Chen

Speaker biography is not available.

Demonstration of LAN-type Communication for an Industrial 5G Network

Linh-An Phan, Dirk Pesch, Utz Roedig and Cormac J. Sreenan (University College Cork, Ireland)

To facilitate the adoption of 5G in industrial networks, 3GPP introduced a new 5G feature called 5G LAN-type service in Release 16. The 5G LAN-type service aims to support similar functionalities of Local Area Networks, but on top of the 5G network. As a result, 5G LAN-type service would be expected to offer UE-to-UE communication with ultra-low latency, which is attractive for localised industrial control settings. The requirements of this new service have been specified but its design and implementation are still being studied. In this demo paper, we present a workable design to implement the 5G LAN-type service and demonstrate its benefit in terms of end-to-end (E2E) latency. Our evaluation shows that E2E latency in a 5G LAN-type service is smaller than those in Multi-access Edge Computing scenarios. The testbed provides a platform for exploring challenging aspects of 5G LAN-service design and implementation.

Speaker Linh-An Phan

Speaker biography is not available.

OREOS: Demonstrating E2E Orchestration in 5G Networks with Open-Source Components

Noé Godinho (University of Coimbra, Portugal); Paulo Duarte and Paulo Martins (Capgemini Engineering, Portugal); David Perez Abreu (University of Coimbra, Portugal & Instituto Pedro Nunes, Portugal); Raul F. D. Barbosa (Universidade de Aveiro, Portugal & Capgemini, Portugal); Bruno Miguel Fonseca Mendes (University of Aveiro, Portugal); João Fonseca (Capgemini Engineering, Portugal); Marco Silva (University of Coimbra, Portugal); Marco Araujo and João Donato Silva (Capgemini Engineering, Portugal); Karima Velasquez, Bruno Miguel Sousa and Marilia Curado (University of Coimbra, Portugal); Adriano Almeida Goes (Capgemini Engineering, Portugal)

5G aims to support ubiquitous connectivity, ultra-Reliable Low Latency (uRLLC), and massive device communication in Next Generation networks. To achieve these objectives, the Open-Radio Access Networks (O-RAN) alliance aims to decouple the Radio Access Network (RAN) architecture and allow heterogeneity. To ensure the services' requirements, it is necessary to guarantee solutions that improve the management of the network. This work proposes an End-to-End (E2E) orchestration framework for a 5G communication infrastructure with open-source components. An overview of the implemented architecture is presented and two demonstrations are shown: how RAN and Core Network metrics are retrieved using a monitoring xAPP, and how the orchestrator enforces a policy after processing and analysing the data gathered. The results show that it is possible to deploy the proposed architecture to monitor and allocate resources efficiently in near-Real Time environments. The major novelty of this work is the fact that this constitutes the first E2E 5G network system using open source tools, to the best of our knowledge. For this purpose, an interface adapter was built to interlink some of these open-source components.

Speaker

Speaker biography is not available.

400G Ethernet Packet Capture Demo Based on Network Development Kit for FPGAs

Jakub Cabal, Vladislav Válek, Martin Špinler and Daniel Kondys (CESNET, Czech Republic); Jan Korenek (Brno University of Technology & CESNET, Czech Republic)

CESNET is ready to present a packet capture demo at 400G networks. As part of its research activities, it has developed a new system for FPGA cards for fast packet reception to DPDK. Due to the programmability and performance of FPGAs, the system can be extended by using hardware acceleration. To simplify the hardware development, we created an open-source Network Development Kit (NDK) framework. Although the demo is presented only on the 400G card, which we have developed in collaboration with Reflex CES, the open-source NDK framework and fast packet capture are available on many other FPGA cards. The open-source framework is ready to use, and we would be happy if you not only use it but also contribute to its further development.

Speaker

Speaker biography is not available.

Critical Element First: Enhance C-V2X Signal Coverage using Power-Efficient Liquid Metal-Based Intelligent Reflective Surfaces

Saige J Dacuycuy (University of Hawaii at Manoa, USA); Zachary Dela Cruz (University of Hawaii, USA); Yanjun Pan (University of Arkansas, USA); Yao Zheng (University of Hawai'i at Mānoa, USA); Aaron T. Ohta (University of Hawaii, USA); Wayne A. Shiroma (University of Hawaii at Manoa, USA)

This demonstration shows the beam steering capability of a new liquid metal-based intelligent reflective surface (IRS) that operates at the 5.9 GHz frequency band to enhance signal coverage of cellular vehicular-to-everything (C-V2X) communication. The IRS unit cell design leverages the electrical actuation technique to move a liquid metal droplet within a rectangle-shaped microfluidic channel filled with sodium hydroxide (NaOH), which changes the phase and magnitude of the reflection signal, and relies on the liquid metal's high surface tension in NaOH to maintain the droplet position without further energy consumption. A power-efficient sequential control logic with priority over center IRS elements is implemented to promptly steer the reflection beam toward the desired angle before the entire IRS panel is fully configured. The merits of the design are evaluated under a 5.9GHz SISO C-V2X link implemented with a software-defined radio.

Speaker

Speaker biography is not available.

Program at a Glance