Addressing the Challenges in Federating Edge Resources

This book chapter considers how Edge deployments can be brought to bear in a global context by federating them across multiple geographic regions to create a global Edge-based fabric that decentralizes data center computation. This is currently impractical, not only because of technical challenges, but is also shrouded by social, legal and geopolitical issues. In this chapter, we discuss two key challenges - networking and management in federating Edge deployments. Additionally, we consider resource and modeling challenges that will need to be addressed for a federated Edge.Comment: Book Chapter accepted to the Fog and Edge Computing: Principles and Paradigms; Editors Buyya, Sriram

Network Slicing

Network slicing is emerging as a key enabling technology to support new service needs, business cases, and the evolution of programmable networking. As an end-to-end concept involving network functions in different domains and administrations, network slicing calls for new standardization efforts, design methodologies, and deployment strategies. This chapter aims at addressing the main aspects of network slicing with relevant challenges and practical solutions

Dynamic Resource Provisioning of a Scalable E2E Network Slicing Orchestration System

Network slicing allows different applications and network services to be deployed on virtualized resources running on a common underlying physical infrastructure. Developing a scalable system for the orchestration of end-to-end (E2E) mobile network slices requires careful planning and very reliable algorithms. In this paper, we propose a novel E2E Network Slicing Orchestration System (NSOS) and a Dynamic Auto- Scaling Algorithm (DASA) for it. Our NSOS relies strongly on the foundation of a hierarchical architecture that incorporates dedicated entities per domain to manage every segment of the mobile network from the access, to the transport and core network part for a scalable orchestration of federated network slices. The DASA enables the NSOS to autonomously adapt its resources to changes in the demand for slice orchestration requests (SORs) while enforcing a given mean overall time taken by the NSOS to process any SOR. The proposed DASA includes both proactive and reactive resource provisioning techniques). The proposed resource dimensioning heuristic algorithm of the DASA is based on a queuing model for the NSOS, which consists of an open network of G/G/m queues. Finally, we validate the proper operation and evaluate the performance of our DASA solution for the NSOS by means of system-level simulations.This research work is partially supported by the European Union’s Horizon 2020 research and innovation program under the 5G!Pagoda project, the MATILDA project and the Academy of Finland 6Genesis project with grant agreement No. 723172, No. 761898 and No. 318927, respectively. It was also partially funded by the Academy of Finland Project CSN - under Grant Agreement 311654 and the Spanish Ministry of Education, Culture and Sport (FPU Grant 13/04833), and the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (TEC2016-76795-C6- 4-R)

Realising the Network Service Federation vision

In Press / En PrensaThe 5G-TRANSFORMER project proposes an NFV/SDN-based architecture to manage the end-to-end deployment of composite NFV network services, which may involve multiple administrative domains, hence, requiring network service federation capabilities. At the architectural level, this article presents the service federation functionality of the 5G-TRANSFORMER service orchestrator. It covers the gaps identified in ETSI NFV reports and specifications (e.g., IFA028). Some recommendations are also presented based on this experience, particularly on the relevance of multi-domain resource orchestration. Experimental results show that the federated service under evaluation is deployed in less than 5 minutes. Time profiling of the various processing federation-related operation shows its reduced impact in the experienced deployment time. A comparison of service deployments of increasing complexity also offers valuable insights.This work has been partially funded by the EC H2020 5G-Transformer Project (grant no. 761536), by MINECO grant TEC2017-88373-R (5G-REFINE) and Generalitat de Catalunya grant 2017 SGR 1195

End-to-end network slicing architecture and implementation for 5G micro-operator leveraging multi-domain and multi-tenancy

Abstract. Local 5G network are emerging as new form of 5G deployment targeted are service delivery for vertical specific purposes and other local users. As such, a well-defined network slicing architecture and implementation procedure is required for a local 5G network. A local 5G network also known as a 5G micro-operator network is targeted a network delivery for vertical-specific services. The aim of the micro-operator concept is to provide enough network flexibility and customization required by different vertical. Previous works on the micro-operator network have established different deployment scenarios that can exist, namely Closed, Open and Mixed Network. Thus, in order for any deployment of a micro-operator network to achieve the network flexibility, customization and privacy required by various vertical, it is essential to have a well-defined network slicing architecture and implementation procedure for local 5G networks. In this thesis, a sophisticated end-to-end network slicing architecture is proposed for different deployment scenarios of a local 5G micro-operator. The aim of the architecture is to address the unavailable description of network slicing for vertical specific network providers, leveraging multi-domain and multi tenancy. The proposed architecture incorporates a broad four-layer concept, leveraging a Multi-tenancy layer for different tenants and their end users, a descriptive Service layer, a multi-domain Slicing MANO layer and a Resource layer. A message sequence diagram is established based on the proposed architecture to describe the flow of information from when a tenant request a slice till the network slices are allocated as communication services to the various targeted user equipment. An actual implementation of network slicing is developed for specific layers of the proposed architecture. To do this, we used a softwarized network based on SDN/NFV, using OpenStack as a cloud infrastructure. On top of that, the network slicing implementation was done using the ETSI Open Source MANO. With these tools, different deployment scenarios’ implementations are achieved. Performance analysis are made based on metrics such as CPU utilization, memory utilization, rate of packet sent and packet received between different network service. These metrics are used to compare shared and non-shared slices within a single or multiple domain slice implementation, which were used as basis for classification of network slice instantiation in 5G micro-operator deployment scenarios. The results from the thesis successfully support the end-to-end network slicing architecture for various deployment scenarios of a local 5G micro-operator network, proposes a slice formation sequence from the end users to the micro-operator network for each deployment scenarios, implement different part of the architecture using different open source tools and measure the performance metrics of different deployment scenarios based on CPU or memory utilization

On the Specialization of FDRL Agents for Scalable and Distributed 6G RAN Slicing Orchestration

Network slicing enables multiple virtual networks to be instantiated and customized to meet heterogeneous use case requirements over 5G and beyond network deployments. However, most of the solutions available today face scalability issues when considering many slices, due to centralized controllers requiring a holistic view of the resource availability and consumption over different networking domains. In order to tackle this challenge, we design a hierarchical architecture to manage network slices resources in a federated manner. Driven by the rapid evolution of deep reinforcement learning (DRL) schemes and the Open RAN (O-RAN) paradigm, we propose a set of traffic-aware local decision agents (DAs) dynamically placed in the radio access network (RAN). These federated decision entities tailor their resource allocation policy according to the long-term dynamics of the underlying traffic, defining specialized clusters that enable faster training and communication overhead reduction. Indeed, aided by a traffic-aware agent selection algorithm, our proposed Federated DRL approach provides higher resource efficiency than benchmark solutions by quickly reacting to end-user mobility patterns and reducing costly interactions with centralized controllers.Comment: 15 pages, 15 Figures, accepted for publication at IEEE TV

On the specialization of FDRL agents for scalable and distributed 6G RAN slicing orchestration

©2022 IEEE. Reprinted, with permission, from Rezazadeh, F., Zanzi, L., Devoti, F. et.al. On the Specialization of FDRL Agents for Scalable and Distributed 6G RAN Slicing Orchestration. IEEE Transactions on vehicular technology (Online) October 2022Network slicing enables multiple virtual networks to be instantiated and customized to meet heterogeneous use case requirements over 5G and beyond network deployments. However, most of the solutions available today face scalability issues when considering many slices, due to centralized controllers requiring a holistic view of the resource availability and consumption over different networking domains. In order to tackle this challenge, we design a hierarchical architecture to manage network slices resources in a federated manner. Driven by the rapid evolution of deep reinforcement learning (DRL) schemes and the Open RAN (O-RAN) paradigm, we propose a set of traffic-aware local decision agents (DAs) dynamically placed in the radio access network (RAN). These federated decision entities tailor their resource allocation policy according to the long-term dynamics of the underlying traffic, defining specialized clusters that enable faster training and communication overhead reduction. Indeed, aided by a traffic-aware agent selection algorithm, our proposed Federated DRL approach provides higher resource efficiency than benchmark solutions by quickly reacting to end-user mobility patterns and reducing costly interactions with centralized controllersPeer ReviewedPreprin

End-to-end slices to orchestrate resources and services in the cloud-to-edge continuum

Fog computing, combined with traditional cloud computing, offers an inherently distributed infrastructure – referred to as the cloud-to-edge continuum – that can be used for the execution of low-latency and location-aware IoT services. The management of such an infrastructure is complex: resources in multiple domains need to be accessed by several tenants, while an adequate level of isolation and performance has to be guaranteed. This paper proposes the dynamic allocation of end-to-end slices to perform the orchestration of resources and services in such a scenario. These end-to-end slices require a unified resource management approach that encompasses both data centre and network resources. Currently, fog orchestration is mainly focused on the management of compute resources, likewise, the slicing domain is specifically centred solely on the creation of isolated network partitions. A unified resource orchestration strategy, able to integrate the selection, configuration and management of compute and network resources, as part of a single abstracted object, is missing. This work aims to minimise the silo-effect, and proposes end-to-end slices as the foundation for the comprehensive orchestration of compute resources, network resources, and services in the cloud-to-edge continuum, as well acting as the basis for a system implementation. The concept of the end-to-end slice is formally described via a graph-based model that allows for dynamic resource discovery, selection and mapping via different algorithms and optimisation goals; and a working system is presented as the way to build slices across multiple domains dynamically, based on that model. These are independently accessible objects that abstract resources of various providers – traded via a Marketplace – with compute slices, allocated using the bare-metal cloud approach, being interconnected to each other via the connectivity of network slices. Experiments, carried out on a real testbed, demonstrate three features of the end-to-end slices: resources can be selected, allocated and controlled in a softwarised fashion; tenants can instantiate distributed IoT services on those resources transparently; the performance of a service is absolutely not affected by the status of other slices that share the same resource infrastructure