ACM SIGCOMM 2021 Workshop on Flexible Networks (FlexNets'21): Artificial Intelligence Supported Network Flexibility and Agility

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Workshop program

Go to FlexNets'21 workshop program

Call for Papers

(Click here to download the PDF version)

As the next generation communication systems beyond 5G, such as 6G, are expected to address a wider range of services and applications with a wider range of dynamic environmental and service-specific requirements, these systems evolve towards an architecture supported by enhanced capabilities to adapt to such flexible environments and connectivity needs. Envisioned 6G systems are expected to see a further increase of applications with stricter and heterogeneous requirements, be adaptive to connectivity requirements through dynamic topologies, and take autonomous decisions to reconfigure the networks for efficiency and resiliency purposes. Flexible and agile networking solutions are required to deal with uncertainties and dynamic parameters. As the number of QoS-demanding applications increases, the capability of end-to-end holistic network transformation is required triggered by the dynamicity and mobility of users and their service demands as well as the radio and resource topology. The complexity introduced by these flexible characteristics needs to be addressed with more adaptive network resource sharing mechanisms among users and applications. This includes the adaptation to individual QoE/QoS needs and the dynamics of the applications and services, starting from access networks to core networks.

Ability to process the big data generated by the network, derive necessary feedbacks from the network and AI-assisted cognitive network management are key enablers for elasticity and adaptiveness to network dynamics such as topology changes due to the mobility of the end users, base stations and rearrangement of network resources (either physical or virtual network functions). A distributed, self-*, AI-assisted and deeply programmable/reconfigurable end-to-end network architecture is required to address such network dynamics.

Topics of Interest

All aspects of cognitive, flexible, dynamic, agile network architectures
Autonomous management of such networks, (real-time) zero-touch management
Autonomous network function allocation and placement
AI-assisted deeply-programmable networks, programmable data planes and nodes
Edge assistance and device-edge-cloud collaboration for elasticity, edge-AI networks
Distributed computing environments, hyper-distributed applications, integration of computing, connectivity, IoT, AI
Architectures for collaborative smart nodes with decentralised intelligence, federated machine learning in 6G
Microservice-based flexible architectures, network management, service orchestration
Open interfaces and open source solutions for smart networks
Virtual radio access technologies, programmable RAN, RANaaS
Energy-oriented network management, ultra-low-energy 6G networks
Multi-context awareness, dynamic multi-service and multi-tenancy and network slicing
Flexible backhauling/fronthauling, Integrated access/backhaul (IAB), multi-hop mesh backhauling
Runtime flexibility in services and applications, application-driven optimization
Drone-assisted agile networks, base stations on wheels or wings
Flexible and software-defined security, physical-layer security
Flexible and rapid deployment for automated and smart services
Private Beyond 5G Networks: Solutions to simplify the lifecycle, deployment, and operation

All in all, future networks must be flexible and elastic to easily introduce new services, applications and business models. Any topic related to this concept is welcome

Social Media and Web Pages

https://twitter.com/flex_nets

https://flexnets.ceng.metu.edu.tr

Submission Instructions

Submissions must be original, unpublished work, and not under consideration at another conference or journal. Submitted papers must be at most six (6) pages long, including all figures, tables, references, and appendices in two-column 10pt ACM format. Papers must include author names and affiliations for single-blind peer reviewing by the program committee. Authors of accepted submissions are expected to present and discuss their work at the workshop.

Please submit your paper via https://flexnets21.hotcrp.com.

Keynote and Cadence Talks

Keynote Talk by Gunnar Mildh, Ericsson Research, Sweden

Title: Drivers and directions for 6G network architecture

Abstract: Research on future network architecture targeting 6G/2030 time frame has started in industry and academia. The presentation will include some high level drivers and directions for future 6G network architecture covering areas such as flexibility, efficient cloud deployment, resiliency and integration of AI/ML.

Biography: Gunnar Mildh received his M. Sc. in electrical engineering from the Royal Institute of Technology (KTH), Stockholm, Sweden, in 2000. In the same year he joined Ericsson Research, Ericsson AB, Stockholm, and has since been working on standardization and concept development for GSM/EDGE, HSPA, LTE, 5G NR and 6G. His focus areas are radio network architecture and protocols. He is currently a senior expert in radio network architecture at the Research Area Networks, Ericsson Research.

Cadence Talk by David M. Gutierrez Estevez, Samsung Electronics R&D Institute, UK

Title: 3GPP Standardization of AI-based Network Automation

Abstract: This talk will provide a technical overview of the 3GPP standardization efforts on Artificial Intelligence (AI) based network automation, with a special focus on the specification of the Network Data Analytics Function (NWDAF) located within the 5G Core (5GC), whose aim is to provide an end-to-end AI and data analytics framework. The talk will cover the state of the art, namely the standardization agreements achieved during both Release 16 and Release 17, as well as the outlook for the future of Network AI in Release 18 and beyond. Research opportunities and challenges leveraging this framework will also be highlighted during the talk.

Biography: Dr. David M. Gutierrez Estevez is a Chief Engineer at Samsung Electronics R&D Institute UK. David obtained his Engineering Degree in Telecommunications (Hons.) from the Universidad de Granada, Spain, and his M.S. (2011) and Ph.D. (2014) degrees on wireless networks from the Georgia Institute of Technology in Atlanta, GA, USA, under the supervision of Prof. Ian F. Akyildiz. From September 2014 to September 2015, David worked for Huawei Technologies in Silicon Valley on the topic of cloud computing. Previously, David had been with several Fraunhofer Institutes in Germany and with Qualcomm in California for periods ranging from three to fifteen months. In 2016, David joined Samsung and led several large-scale research projects within the 5GPPP ecosystem on 5G RAN, 5G architecture and AI. Since 2019, David is a member of the Samsung global 3GPP delegation in SA2 leading the work on data analytics for network automation while involved in other network architecture aspects.