A 5G mobile network architecture to support vertical industries

The telecom industry is moving from a "horizontal" service delivery model, where services are defined independent of their consumers, toward a "vertical" delivery model, where the provided services are tailored to specific industry sectors and verticals. In order to enable this transition, an end-to-end comprehensive 5G architecture is needed, with capabilities to support the use cases of the different vertical industries. A key feature of this architecture is the implementation of network slicing over a single infrastructure to provision highly heterogeneous vertical services, as well as a network slicing management system capable of handling simultaneous slices. On top of the network slicing technology, functionality needs to be devised to deploy the slices required by the different vertical players and provide them with a suitable interface to manage their slice. In this article, we design a 5G mobile network architecture to support vertical industries. The proposed architecture builds on ongoing standardization efforts at 3GPP and ETSI, and incorporates additional modules to provide enhanced MANO and control functionality as well as artificial-intelligence-based data analytics. On top of these modules, a service layer is provided to offer vertical players an easyto- use interface to manage their services.This work was supported by the H2020 5G-TOURS European project (Grant Agreement No. 856950)

5G-MoNArch use case for ETSI ENI: elastic resource management and orchestration

Proceeding of: 2018 IEEE Conference on Standards for Communications and Networking (CSCN)5G networks will grant spectacular improvements of the most relevant Key Performance Indicators (KPIs) while allowing resource multi-tenancy through network slicing. However, the other side of the coin is represented by the huge increase of the management complexity and the need for efficient algorithms for resource orchestration. Therefore, the management and orchestration of the network through Artificial Intelligence (AI) and Machine Learning (ML) algorithms is considered a promising solution, as it allows to reduce the human interaction (usually expensive and error-prone) and scale to large scenario composed by thousands of slices in heterogeneous environments. In this paper, we provide a review of the current standardization efforts in this field, mostly due to the work performed by the Experiential Network Intelligence (ENI) industry specification group (ISG) within the European Telecommunications Standards Institute (ETSI). Then, we thoroughly describe an exemplary use case on elastic network management and orchestration through learning solutions proposed by the 5GPPP project 5G-MoNArch and recently approved at ETSI ENI

On the benefits of bringing cloud-awareness to network virtual functions

Proceeding of: 2018 European Conference on Networks and Communications (EuCNC), June 18-21, Ljubljana, SloveniaWe are currently observing the softwarization of communication networks, where network functions are translated from monolithic pieces of equipment to programs running over a shared pool of computational, storage, and communication resources. As the amount of this resources might vary over time, in this paper we discuss the potential benefits of introducing resource awareness to softwarized network functions. More specifically, we focus on the case of computational elasticity, namely, the ability to endure shortages of computational resources while providing an adequate (although non-ideal) service. We discuss how to enable this ability by re-designing network functions, and illustrate the potential benefits of this approach with a numerical evaluation

Overall 5G-MoNArch architecture and implications for resource elasticity

Proceeding of: 2018 European Conference on Networks and Communications (EuCNC), June 18-21, Ljubljana, SloveniaThe fifth generation (5G) of mobile and wireless communications networks aims at addressing a diverse set of use cases, services, and applications with a particular focus on enabling new business cases via network slicing. The development of 5G has thus advanced quickly with research projects and standardization efforts resulting in the 5G baseline architecture. Nevertheless, for the realization of native end-to-end (E2E) network slicing, further features and optimizations shall still be introduced. In this paper, essential building blocks and design principles of the 5G architecture will be discussed capitalizing on the innovations that are being developed in the 5G-MoNArch project. Furthermore, building on the concept of resource elasticity introduced by 5G-MoNArch and briefly resummarized in this paper, an elasticity functional architecture is presented where the architectural implications required for each of the three dimensions of elasticity are described, namely computational, orchestration-driven, and slice-aware elasticity.This work has been performed in the framework of the H2020 project 5G-MoNArch co-funded by the EU

The path towards resource elasticity for 5G network architecture

Proceeding of: IEEE Wireless Communications and Networking Conference Workshops (WCNCW 2018)Vertical markets and industries are addressing a large diversity of heterogeneous services, use cases, and applications in 5G. It is currently common understanding that for networks to be able to satisfy those needs, a flexible, adaptable, and programmable architecture based on network slicing is required. Moreover, a softwarization and cloudification of the communications networks is already happening, where network functions (NFs) are transformed from monolithic pieces of equipment to programs running over a shared pool of computational and communication resources. However, this novel architecture paradigm requires new solutions to exploit its inherent flexibility. In this paper, we introduce the concept of resource elasticity as a key means to make an efficient use of the computational resources in 5G systems. Besides establishing a definition as well as a set of requirements and key performance indicators (KPIs), we propose mechanisms for the exploitation of elasticity in three different dimensions, namely computational elasticity in the design and scaling of NFs, orchestration-driven elasticity by flexible placement of NFs, and slice-aware elasticity via cross-slice resource provisioning mechanisms. Finally, we provide a succinct analysis of the architectural components that need to be enhanced to incorporate elasticity principles.Part of this work has been performed within the 5GMoNArch project, part of the Phase II of the 5th Generation Public Private Partnership (5G-PPP) program partially funded by the European Commission within the Horizon 2020 Framework Program

Artificial Intelligence for Elastic Management and Orchestration of 5G Networks

The emergence of 5G enables a broad set of diversified and heterogeneous services with complex and potentially conflicting demands. For networks to be able to satisfy those needs, a flexible, adaptable, and programmable architecture based on network slicing is being proposed. A softwarization and cloudification of the communications networks is required, where network functions (NFs) are being transformed from programs running on dedicated hardware platforms to programs running over a shared pool of computational and communication resources. This architectural framework allows the introduction of resource elasticity as a key means to make an efficient use of the computational resources of 5G systems, but adds challenges related to resource sharing and efficiency. In this article, we propose Artificial Intelligence (AI) as a built-in architectural feature that allows the exploitation of the resource elasticity of a 5G network. Building on the work of the recently formed Experiential Network Intelligence (ENI) industry specification group of the European Telecommunications Standards Institute (ETSI) to embed an AI engine in the network, we describe a novel taxonomy for learning mechanisms that target exploiting the elasticity of the network as well as three different resource elastic use cases leveraging AI. This work describes the basis of a use case recently approved at ETSI ENI.Part of this work has been performed within the 5G-MoNArch project (Grant Agreement No. 761445), part of the Phase II of the 5th Generation Public Private Partnership (5G-PPP) program partially funded by the European Commission within the Horizon 2020 Framework Program. This work was also supported by the the 5G-Transformer project (Grant Agreement No. 761536)

Impact of operatoŕs experience on peri-procedural outcomes with Watchman FLX: Insights from the FLX-SPA registry

Background: The Watchman FLX is a device upgrade of the Watchman 2.5 that incorporates several design enhancements intended to simplify left atrial appendage occlusion (LAAO) and improve procedural outcomes. This study compares peri-procedural results of LAAO with Watchman FLX (Boston Scientific, Marlborough, Massachusetts) in centers with varying degrees of experience with the Watchman 2.5 and Watchman FLX. Methods: Prospective, multicenter, 'real-world' registry including consecutive patients undergoing LAAO with the Watchman FLX at 26 Spanish sites (FLX-SPA registry). Implanting centers were classified according to the center's prior experience with the Watchman 2.5. A further division of centers according to whether or not they had performed ≤ 10 or > 10Watchman FLX implants was prespecified at the beginning of the study. Procedural outcomes of institutions stratified according to their experience with the Watchman 2.5 and FLX devices were compared. Results: 359 patients [mean age 75.5 (SD8.1), CHA2DS2-VASc 4.4 (SD1.4), HAS-BLED 3.8(SD0.9)] were included. Global success rate was 98.6%, successful LAAO with the first selected device size was achieved in 95.5% patients and the device was implanted at first attempt in 78.6% cases. There were only 9(2.5%) major peri-procedural complications. No differences in efficacy or safety results according to the centeŕs previous experience with Watchman 2.5 and procedural volume with Watchman FLX existed. Conclusions: The Watchman FLX attains high procedural success rates with complete LAA sealing in unselected, real-world patients, along with a low incidence of peri-procedural complications, regardless of operatoŕs experience with its previous device iteration or the number of Watchman FLX devices implanted

O que os santos podem fazer pela antropologia?

O artigo sustenta que os santos podem servir de eixo a uma abordagem mais etnográfica e radical da antropologia da religião. De praxe, essa subdisciplina está excessivamente pautada pelas concepções de apenas um tipo de nativos: teólogos, sacerdotes, especialistas. Doutrinas estabelecidas servem como referência, e a religião comum vira assim uma religião popular, subalterna ou desviante. Os santos, personagens locais que no entanto atravessam fronteiras entre credos e são por sua vez subalternos nas elaborações teológicas, podem ser vistos como atores essenciais dentro de uma rede de relações (do tipo das propostas pela actor-network theory), a unir mitos, devotos, lugares, objetos ou personagens sagrados, rituais, doutrinas e, como um limite externo, Deus. Essa rede, sugiro, deve se reivindicar como objeto prioritário dos estudos sobre religião.<br>This paper claim that saints must be at the core of a more ethnographic and radical approach to the Anthropology of Religion. Anthropology of Religion draw heavily on specialized conceptions of priests or theologians, while common religious practices are marked as popular or deviant ones. The saints, although local characters overlooked in theological discourse, overtake creed frontiers and can be seen as critical actors in a network (after the actor-network theory proposal) that links myths, believers, places, sacred things or personae, rituals, doctrine, and, as an outer edge, God. This network, I suggest, must be stressed as the main object of religion studies

Near-intrinsic energy resolution for 30-662 keV gamma rays in a high pressure xenon electroluminescent TPC

We present the design, data and results from the NEXT prototype for Double Beta and Dark Matter (NEXT-DBDM) detector, a high-pressure gaseous natural xenon electroluminescent time projection chamber (TPC) that was built at the Lawrence Berkeley National Laboratory. It is a prototype of the planned NEXT-100 136Xe neutrino-less double beta decay (0νββ) experiment with the main objectives of demonstrating near-intrinsic energy resolution at energies up to 662 keV and of optimizing the NEXT-100 detector design and operating parameters. Energy resolutions of ∼1% FWHM for 662 keV gamma rays were obtained at 10 and 15 atm and ∼5% FWHM for 30 keV fluorescence xenon X-rays. These results demonstrate that 0.5% FWHM resolutions for the 2459 keV hypothetical neutrino-less double beta decay peak are realizable. This energy resolution is a factor 7-20 better than that of the current leading 0νββ experiments using liquid xenon and thus represents a significant advancement. We present also first results from a track imaging system consisting of 64 silicon photo-multipliers recently installed in NEXT-DBDM that, along with the excellent energy resolution, demonstrates the key functionalities required for the NEXT-100 0νββ searc