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There is a clear sense that AI can be a disruptive enabler to build a more agile and efficient future network. However, despite the constant efforts from researchers and engineers, the potential of AI is far away from being fully exploited and there's still a great gap between the current intelligence level of the network and our fancy expectations for it. Hence this panel is proposed to discuss the challenges and opportunities that we may face in "AI for 5G and beyond" exploration.
Machine learning (ML) and AI will play a key role in the development of 6G networks. Network virtualization and network softwarization solutions in 5G networks can support data-driven intelligent and automated networks to some extent and this trend will grow in 5G-advanced networks. Radio access network algorithms and radio resource management functions can exploit network intelligence to fine-tune network parameters to reach close-to-optimal performance in 5G networks. In 6G networks, network intelligence is envisioned to be end-to-end, and air interface is envisioned to be AI-native. The user equipment (UE) devices need to be smarter, environment and context-aware, and capable of running ML algorithms. With these capabilities on end devices, federated learning is envisioned to be one of the promising solutions that can solve the scalability and trust issues in distributed learning. This talk will focus on the main practical challenges in developing machine learning solutions in 5G use cases, related 3GPP standardization activities, and emphasize with a case study how the deployment of these solutions is much harder in a real network as compared to theoretical performance evaluation. Furthermore, the use of federated learning in wireless networks is motivated by providing example use case examples; and challenges in the use of federated learning solutions in 6G networks are explained.
Confidential computing based on Fully Homomorphic Encryption (FHE) is gaining attention. FHE enables arbitrary computation on encrypted data and thus enables the privacy of users' data. Ever since the first FHE scheme based on lattice was proposed by Craig Gentry in the year 2009, many FHE schemes are designed. Some of prominent FHE schemes BGV, CKKS, TFHE . In the meantime, many open source libraries for FHE schemes such as HElib SEAL, HEAAN, PALiSADE, etc. are also developed. This enabled to realize some of the applications in the area of data analytics and private AI (private inference) based on FHE. However, due to considerable computation/memory overhead, the performance of FHE schemes is slow of the order of 6 when compared to computation on plaintext data. Hence to address this, there are several research works devoted to accelerating FHE schemes. As part of this talk, we cover, optimizations in FHE for realizing privacy preserving machine learning applications in an efficient manner.
Ensuring end to end Security is the implicit requirement of any communication system. While there are several key based encryption techniques in practice today, they fail to provide foolproof security. In order to decrypt and consume the message, the encryption key is to be transferred to the receiving end over an alternative channel. It is still risky and often retrieved by a hacker with powerful and affordable computing power. Consequently, organizations such as banks and financial institutions handling sensitive information of the customers are hesitant to put the data over the channel to consume cloud based applications. This talk provides an alternative for the encryption key transfer, called homomorphic encryption wherein decryption of the data is not required before the consumption of the applications, especially the AI inferencing models, over the cloud. Homomorphic encryption however has a set of Implementation issues, solved to an extent by the upcoming quantum computing technology.
Spectrum regulation challenges grow for both unlicensed (e.g., Wi-Fi) and licensed (e.g., cellular) opportunities, particularly those created by 10's to 100's of billions of connected, communicating devices. Dynamic, cognitive solutions just begin to find field use and initiate the inevitable march towards increasingly artificially intelligent allocation of spectra and space. This talk reviews some multiuser fundamentals, their complexity of solution, and how they may find future application to magnify spectral efficiency by orders of magnitude.
This industry keynote is on Modern AI Meets Cell Phone Network Optimization. Bio: Gregory Dudek is a Professor with the School of Computer Science and a member of the McGill Research Centre for Intelligent Machines (CIM) and an Associate member of the Dept. of Electrical Engineering at McGill University. In 9/2008 he became the Director of the McGill School of Computer Science. Since 2012 he has been the Scientific Director of the NSERC Canadian Field Robotics Network (NCFRN): http://ncfrn.mcgill.ca He is the former Director of McGill's Research Center for Intelligent Machines, a 25 year old inter-faculty research facility. In 2002 he was named a William Dawson Scholar. In 2008 he was made James McGill Chair. In 2010 he was awarded the Fessenden Professorship in Science Innovation. In 2010 he was also awarded the Canadian Image Processing and Pattern Recognition Award for Research Excellence and also for Service to the Research Community. He directs the McGill Mobile Robotics Laboratory. He has been on the organizing and/or program committees of Robotics: Systems and Science, the IEEE International Conference on Robotics and Automation (ICRA), the IEEE/RSJ International Conference on Intelligent Robotics and Systems (IROS), the International Joint Conference on Artificial Intelligence (IJCAI), Computer and Robot Vision, IEEE International Conference on Mechatronics and International Conference on Hands-on Intelligent Mechatronics and Automation among other bodies. He is president of CIPPRS, the Canadian Information Processing and Pattern Recognition Society, an ICPR national affiliate. He was on leave in 2000-2001 as Visiting Associate Professor at the Department of Computer Science at Stanford University and at Xerox Palo Alto Research Center (PARC). During his sabbatical in 2007-2008 he visited the Massachusetts Institute of technology and co-founded the company Independent Robotics Inc. He obtained his PhD in computer science (computational vision) from the University of Toronto, his MSc in computer science (systems) at the University of Toronto and his BSc in computer science and physics at Queen's University. He has published over 200 research papers on subjects including visual object description and recognition, robotic navigation and map construction, distributed system design and biological perception. This includes a book entitled "Computational Principles of Mobile Robotics" co-authored with Michael Jenkin and published by Cambridge University Press. He has chaired and been otherwise involved in numerous national and international conferences and professional activities concerned with Robotics, Machine Sensing and Computer Vision. His research interests include perception for mobile robotics, navigation and position estimation, environment and shape modelling, computational vision and collaborative filtering. He grew up in Montreal and favors light food. With his children he is re-discovering model rocketry, rollerblading, and has discovered he's not good at surfing but loves it.
This academic keynote is on Perspectives On Innovations and Reality - What Next? PANELISTS: Jonathan Davidson JONATHAN DAVIDSON Cisco Bio: Jonathan was named Senior Vice President and General Manager of Cisco's Mass-Scale Infrastructure Group in March 2020. He leads an organization that builds silicon, optics, hardware, software, and systems innovations for the largest and most advanced networks in the world. Prior to this role, Jonathan was named Senior Vice President and General Manager of Cisco's Service Provider Business in August 2018. He led the team to deliver industry leading technologies for the Internet and 5G (routing systems, IOS XR software, automation, and solutions for fixed, cable, and mobile providers). Jonathan re-joined Cisco in March 2017 as Sr. Vice President and General Manager of Service Provider Networking. In that role, he drove Cisco's leadership position in next-generation routing and network automation. Prior to rejoining Cisco, Jonathan served as Executive Vice President and General Manager at Juniper Networks leading its Engineering and Product Management. In that role, he was responsible for driving strategy, development and business growth for the company's entire portfolio including routing, switching and security, as well as leading the ongoing evolution of silicon technology and the Junos operation system. Before Juniper, Jonathan held a variety of leadership positions at Cisco over the course of 15 years. During that time, he developed service provider solutions and led the enterprise routing product management team and service provider Layer 4 through Layer 7 services team. Jonathan is co-author of the best-selling book, "Voice-over IP Fundamentals," and is a frequent speaker at high-profile industry events. Active on social media, he frequently shares his observations and insights about the industry through Twitter and blogs.Ibrahim GedeonIBRAHIM GEDEON CTO, TELUS Bio: Ibrahim Gedeon is one of the global telecommunications industry’s eminent thought leaders. He has carved out an international career by combining insight and skill as an applied scientist with a lighthearted approach to leadership. As Chief Technology Officer for TELUS, a leading national telecommunications company in Canada, he is responsible for all technology development and strategy, security, service and network architecture, service delivery and operational support systems, as well as service and network convergence, and network infrastructure strategies and evolution. Under his leadership the TELUS wireless broadband network has become one of the best in the world. Ibrahim serves on the board of the Next Generation Mobile Networks Alliance, the Alliance for Telecommunications Industry Solutions and the Institute for Communication Technology Management. In addition to his industry leadership roles, he has been awarded with IEEE Communications Society’s prestigious Distinguished Industry Leader Award and elected a Fellow of the Canadian Academy of Engineering (CAE) for his significant contributions to the field of engineering. Ibrahim has also been named one of the 100 most powerful and influential people in the telecoms industry in Global Telecoms Business magazine’s GTB Power 100. Ibrahim holds a Bachelor's degree in Electrical Engineering from the American University of Beirut, a Master’s in Electronics Engineering from Carleton University and an Honourary Doctor of Laws degree from the University of British Columbia and is passionate about supporting engaged, high-performing teams.
This industry keynote is on 6G: Defining the Next Decade. Bio: Dr. Wen Tong is the Huawei Fellow, CTO, Huawei Wireless. Dr. Tong is the head of Huawei wireless research. In 2011, he was appointed the Head of Communications Technologies Labs of Huawei, currently, he spearheads and leads Huawei’s 5G wireless technologies research and development. Prior to joining Huawei in 2009, Dr. Tong was the Nortel Fellow and head of the Network Technology Labs at Nortel. He joined the Wireless Technology Labs at Bell Northern Research in 1995 in Canada. Dr. Tong was elected as a Huawei Fellow and an IEEE Fellow. He was the recipient of IEEE Communications Society Industry Innovation Award for “the leadership and contributions in development of 3G and 4G wireless systems” in 2014, and IEEE Communications Society Distingushed Industry Leader Award for “pioneering technical contributions and leadership in the mobile communications industry and innovation in 5G mobile communications technology” in 2018. He pioneered fundamental technologies from 1G to 5G wireless with more than 400 granted US patents. Dr. Tong is a Fellow of Canadian Academy of Engineering, and he also serves as Board of Director of WiFi Alliance. He is based in Ottawa, Canada.
Future wireless systems will require a paradigm shift in how they are networked, organized, configured, optimized, and recovered automatically, based on their operating situations. Emerging Internet of Things (IoT) and Cyber-Physical Systems (CPS) applications aim to bring people, data, processes, and things together, to fulfill the needs of our everyday lives. With the emergence of software defined networks, adaptive services and applications are gaining much attention since they allow automatic configuration of devices and their parameters, systems, and services to the user's context change. It is expected that upcoming Fifth Generation and Beyond (5G&B) wireless networks, known as more than an extension to 4G, will be the backbone of IoT and CPS, and will support IoT systems by expanding their coverage, reducing latency and enhancing data rate. However, there are several challenges to be addressed to provide resilient connections supporting the massive number of often resource-constrained IoT and other wireless devices. Hence, due to several unique features of emerging applications, such as low latency, low cost, low energy consumption, resilient and reliable connections, traditional communication protocols and techniques are not suitable.
In this talk, we present an integration of blockchain technology into federated learning for secure and reliable federated learning. The concept of reputation is introduced as a reliable metric for federated learning workers. Based on this metric, a reliable worker select.
This talk is an attempt to answer the question “How can intelligent machines efficiently communicate?” which is one of the main goals of the so-called “Semantic Communication”. I will present a joint work with Daniel Bennequin which shows our progresses towards a mathematical theory of semantic communication, inspired by the foundational works of Claude Shannon and Alexander Grothendieck. To communicate efficiently we need a language. This language is intimately related to the goal or task that the semantic source has to follow. The second part of the presentation will be devoted to the Carnap and Bar-Hillel language. It will be shown on this example why a notion of semantic information measure cannot be a scalar quantity but a space. We will give some intuition on the construction of such spaces. Finally we will propose both semantic source coding and semantic channel coding theorems.
It is undeniable that artificial intelligence and machine learning algorithms are at the heart of a fast-growing number of new telecommunication technologies. With our panel of experts, we will explore a variety of IP protection strategies that include copyrights, trade secrets and patents, as well as their applicability to data and AI technologies.
This panel will address technical and social trends that would motivate further evolution beyond 5G, representative use cases of 6G, and initial views about vision, requirements, and roadmap of standardization and commercialization for 6G. Considering that the mobile industry will continue the enhancement of 5G networks for about 10 years before the start of deploying 6G networks, it would also be worth discussing how to define the relationship between 5G evolution and 6G. The last decade has seen an exploding growth in mobile data rates enabled by millions of mobile apps, and there are no signs of this slowing down as we look towards 2030. As our society moves towards hyper-connectivity and full digitization by leveraging intelligent data-driven frameworks, it will continue to push the capabilities of 5G to its limits. As the 1st and 2nd phase of 5G networks are being deployed around the world and with the next phase of 5G standardization underway, discussions towards 6G are gaining significant momentum. While consensus is building towards what 6G KPIs could be, there is much left to debate on what are the actual 6G use-cases and drivers that will require these KPIs! It is anticipated that 6G wireless systems must support far-reaching applications ranging from multi-sensory extended reality, holographic communications to fully autonomous systems at scale which cannot be met by today’s 5G service classes viz., eMBB, URLLC and mMTC. 6G will be expected to deliver near-instant and unlimited connectivity without sacrificing reliability, security/trust for multiple form-factors, while working well within the constraints of device battery-life and computing power. We envisage that 6G will not be a mere push to higher frequency bands with wider bandwidths and ultra-high throughputs; rather it will leverage advances from multiple and disparate disciplines ranging from materials research to AI/ML to neuromorphic computing to blockchain/DLT and edge native architectures, to name a few. This panel is part-2 of the two-panel series in the industry forum facilitating 6G discussions, with part-1 covering 6G use-cases, requirements and roadmap (add hyperlink to part-1 panel led by Juho). In this panel, we will look to discuss how we can build from the collective learnings and experiences from commercial 5G rollouts and ongoing research to understand how they are likely to influence advances in 5G and 6G evolution, what will be the most promising technology-enablers of 6G, their impact on 6G architecture, adjacent technologies that 6G will have to rely on and how 6G can promote their emergence. This panel brings together leading experts who have helped shape the mobile ecosystem representing key players from infra, handset and chipset OEMs, operators and academia to share their views on the major technological developments that are likely to shape the evolution of next-generation wireless communication systems.
The aim of this workshop is to streamline research on affective sensing applications in communication networks. It further comes in response to a steadfastly growing trend in communication context both to facilitate cost-effective sensing, and to utilize the user’s affect to improve the network operation. These include the use of ISM-band equipment to contactlessly capture human movement, pose, breathing rate, etc., and infer affect whether in standalone or a multimodal manner, i.e., with or with video/audio feeds. Another example is the automating QoE capture to improve the networked service delivery.
Traditional machine learning tends to be centralized in nature (e.g., in the cloud). However, security and privacy concerns as well as the availability of abundant data and computational resources in wireless networks motivate moving learning algorithms deployed on mobile networks towards the network edge. This has led to the emergence of the rapidly growing area of (mobile) edge learning, which integrates two originally decoupled areas: wireless communication and machine learning. It is widely expected that the advancements in edge learning will provide a platform for implementing edge artificial intelligence (AI) in 5G-and-Beyond systems and supporting large-scale problems ranging from autonomous driving to personalized healthcare. Thus, this proposed full-day workshop will seek to bring together researchers and experts from academia, industry, and governmental agencies to discuss and promote the research and development needed to overcome the major challenges that pertain to this cutting-edge research topic.
We are happy to announce the organization of the first edition of the IEEE ICC workshop: Towards Standardized Secured IoT B5G networking - Artificial Intelligence and Blockchain (AB-SIoT). This workshop will solicit original work targeting beyond 5G (B5G) networking, focusing on research work addressing Artificial Intelligence (AI) and Blockchain, and the integration of both. To add to the practicality of the presented work and have a more interesting fruitful discussion, the workshop will include an interactive session, where experimental testbeds and practical showcases can be demonstrated. The scope of the workshop is detailed below. 5G and massive Internet of Things (IoT) are finally here. While 5G networks will serve as the broadband backbones, IoT will bombard killer applications with the inclusion of smart sensors. The essence of smart city development typically starts from the aggregation of slower data rate through LPWAN, before being sent via 5G/B5G to the server for analysis. There will be ample room for data analytics and new challenges need to be tackled. Will the data be secured during transmission? Will the data be securely recorded? How do we provide confidentiality, integrity and availability in the IoT world? The IoT world is rather new, do we have any best practices and standards on the smart sensors? It seems not quite the case at this point. When there are not sufficient regulations in the smart sensor realm, in what way should we provide the required security level agreements? What is the meaning of service level in the B5G-IoT new era? There is much room for our exploration. Research has already started on beyond 5G (B5G), which will shape future networking, especially towards 2030. Many research funding tools are targeting ideas for B5G, towards 2030 and after. For instance, in Europe, there is EU H2020 ICT-52-2020 Smart Connectivity beyond 5G. The amazing IoT development offers a smart high-level concept for integrating physical and cyber objects. In the coming decade, there will be hundreds of billions of IoT connections. It is inevitable that IoT will find applications in all walks of our lives, spanning energy management, healthcare, transportation, and fin-tech, to name a few. Nonetheless, the intrinsic uncoordinated frequency band and the ever-growing IoT market may pose various critical challenges on public safety, cybersecurity and data privacy. To facilitate IoT best practices, various international and industrial standards should be brought to the scene. These include, but are not limited to, IEEE P2668*, IEEE 1451 family, ISO 27k family, General Data Protection Regulation (GDPR), etc. (*P2668: https://standards.ieee.org/project/2668.html) 5G networks have been designed with intelligence, autonomy and flexibility in mind. Future B5G systems are expected to extend those properties even further. Hence, artificial intelligence (AI) will be in the heart of B5G networking. New foreseen applications and verticals will further push the burdens on privacy and security requirements. Blockchain is an emerging disruptive technology that was initially envisioned for crypto-currency, but since then has been widely adopted for its groundbreaking capabilities that can offer security, privacy, in addition to added reliability to networking. The future IoT B5G network is thus envisioned to widely adopt these two stepping-stone research building blocks, towards providing reliable, flexible, secured, high performance and resilient IoT networking, to fulfill high demands of current and future IoT applications and verticals. This workshop specifically targets future networks of IoT B5G, mainly embracing AI and blockchain. The workshop also solicits papers addressing new ideas, standards, best practices, and innovative applications of IoT, including industrial IoT (IIoT), which will be adopted in the future, and their new requirements. The workshop will pay special attention to efforts integrating both areas, especially those contributing to the standardization of IoT devices, their applications, and the assessment of IoT devices, by proposing methods for grading and ranking of IoT devices in line with IEEE P2668*.