Xenofon Vasilakos, who is currently postdoctoral fellow at Eurecom graduate school and research centera, France, will give a talk on "Cognitive Network and Slice Management in Virtualized Multi-Tenant 5G Networks" on Tuesday, October 9th, at room 414 of the Trias Str. building
Fifth Generation (5G) mobile networks pose a major paradigm shift, aimed to improve efficiency and flexibility with a service-oriented architecture that delivers networks as-a-service. The underlying concept is to support multiple services and virtual networks over one or more physical network infrastructure providers, with respect to (wrt) different service definition and agreement requirements, control and management, and performance. This service-oriented 5G vision can address the vast variety of emerging resource-hungry wireless services due to the unprecedented proliferation of smartphone and Internet-of-Things (IoT) devices, via a network composition and resource sharing model that reduces both Capital Expenditure (CAPEX) and operating expenses (OPEX). The later is done by decoupling infrastructure providers (e.g., operators and data center owners), service providers (e.g., operators and verticals) and network function providers (e.g., vendors). Therefore, a 5G service can be built by combining multi-vendor physical network functions and Virtual Network Functions (VNFs), bringing network slicing to the foreground as a key enabler for the envisioned service-oriented 5G. Within this 5G context, a key concept for customizing and offering a slice in a flexible way is to automate its life-cycle management. Following a long period of remaining in obscurity, Machine Learning (ML)-based approaches have created a trend towards this direction in the literature due to breakthroughs made on computational devices (CPUs, GPUs and Tensor Processing Units (TPUs)), which qualify ML as an appropriate option. Nevertheless, Cognitive Network & Slice Management based on ML poses a series of challenges, spanning from the design process of the ML models up to their deployment and their runtime life-cycle, including their cooperation. In addition, another key challenge towards a 5G era is the ever-increasing demand for resource-hungry, content-rich services such as HD video streaming and augmented reality, which require both low latency and high reliability.
This talk will focus on three points of research within the context of Cognitive Network & Slice Management in virtualized multi-tenant 5G networks:
(a) A novel Methodology approach to Cognitive Network & Slice Management based on Machine Learning (ML) models for managing network and slice resources in a way that complies with slice Service Level Agreements (SLAs) and maximizes the revenue of the underlying physical network operator(s). The proposed methodology approach standardizes, orchestrates and automates all the necessary steps and actions for building and deploying efficient ML models as collaborative components of an integrated Cognitive Network & Slice Management system.
(b) LL-MEC, the first open-source Low-Latency Multi-access Edge Computing (MEC) platform enabling coordinated resource programmability in end-to-end slicing scenarios, mobile network monitoring, control, and programmability while retaining compatibility with 3GPP and ETSI specifications.
(c) Ongoing work on coordinated, multi-type resource allocation for E2E slicing.
Presenter's biography: Xenofon Vasilakos is a postdoctoral fellow at Eurecom graduate school and research center, the Communication Systems department. He is funded by the “Investments for the Future” LABEX scholarship programme. Currently, he is working on 5G slicing technologies with a particular focus on Multi-access Edge Computing solutions and cognition approaches inspired by Machine Learning models towards self-managed 5G mobile networks. He has acquired a Ph.D. in Informatics from the Athens University of Economics and Business (AUEB) by working on Information-Centric Networking architectures, protocols and distributed solutions for the Future Internet, with an emphasis on rendezvous networks and seamless mobility support. Before that, he obtained his M.Sc. degree in Parallel and Distributed Computer Systems in 2009 from the Vrije Universiteit Amsterdam and his B.Sc. in Informatics from AUEB in 2007. He has participated in EU funded H2020 ICT projects such as H2020-POINT and, currently, 5GPPP SliceNet and 5GPPP 5G-PICTURE. In the past, he has participated in the EU funded FP7 projects PSIRP and PURSUIT, as well as in the Greek government-funded project I-CAN on clean-slate Information-Centric Networking architectures.