New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

On Virtual Network Functions' Placement in Future Distributed Edge Cloud

International audienceNetwork Function Virtualization (NFV) is changing the way networks are managed, by providing more scalability and flexibility. However, to meet stringent real-time constraints, some network functions have to be hosted close to end users, which incites Network Operators (NOs) to install well di-mensioned data centers at the edge of the network. In this framework, the contributions of this paper are twofold. First, we proposed an analytical model for the blocking analysis in a multidimensional cloud system, which was validated using discrete events' simulations. Second, we conducted a comparative analysis of the most popular placement's strategies. The proposed model, as well as the comparative study, reveal practical insights into the performance evaluation of resource allocation and capacity planning for distributed edge cloud with limited capacities

CLOSE: A Costless Service Offloading Strategy for Distributed Edge Cloud

International audienceNew bandwidth-intensive and time-constrained services in 5G networks combined with network function virtual-ization is pushing network operators to deploy distributed cloud infrastructures at the edge of the network. Allocating resources in capacity-limited infrastructures raises new challenges, which have not really been so far considered in the cloud literature. In this context, we investigate placement and offloading strategies of constrained services. We set design principles of future distributed edge clouds in order to meet application requirements. We precisely introduce a costless distributed resource allocation algorithm, named CLOSE, which considers local information only. We compare via simulations the performance of CLOSE against those obtained by using mechanisms proposed in the literature, notably the Tricircle project within OpenStack. It turns out that the proposed distributed algorithm yields better performance while requiring less overhead

Towards a Dynamic Adaptive Placement of Virtual Network Functions under ONAP

International audienceIn the context of the Open Network Automation Platform (ONAP), we develop in this paper a resource allocation strategy for deploying Virtualized Network Functions (VNFs) on distributed data centers. For this purpose, we rely on a three-level data center hierarchy exploiting co-location facilities available within Main and Core Central Offices. We precisely propose an active VNFs' placement strategy, which dynamically offload requests on the basis of the load observed within a data center. We compare via simulations the performance of the proposed solution against mechanisms so far proposed in the literature, notably the centralized approach of the multi-site project within OpenStack, currently adopted by ONAP. It turns out that the proposed algorithm yields better performance in terms of both data center occupancy and overhead. Furthermore, it allows extending the applicability of ONAP in the context of distributed cloud, without requiring any modification

Reference architecture for slicing in LoRAWAN networks

This document describes the basic functional architecture of the Intelligentisa project. This document reviews all the elements necessary to run a LoRAWAN network and the associated functions. The objective is to integrate the functional architecture into an orchestration framework, possibly by virtualizing some fundamental functions, such as LoRAWAN network Servers (LNSs). This requires to identify basic functional blocks, in particular telemetry exploiting metrics from the substrate virtualized infrastructure as well as supported LoRAWAN networks, and orchestration functions for the deployment and the optimization of LoRAWAN networks to achieve some performance objectives. In a first step, all these issues are considered without slicing considerations and in a second step, the concept of slicing in the context of LoRAWAN networks is introduced

Reference architecture for slicing in LoRAWAN networks

This document describes the basic functional architecture of the Intelligentisa project. This document reviews all the elements necessary to run a LoRAWAN network and the associated functions. The objective is to integrate the functional architecture into an orchestration framework, possibly by virtualizing some fundamental functions, such as LoRAWAN network Servers (LNSs). This requires to identify basic functional blocks, in particular telemetry exploiting metrics from the substrate virtualized infrastructure as well as supported LoRAWAN networks, and orchestration functions for the deployment and the optimization of LoRAWAN networks to achieve some performance objectives. In a first step, all these issues are considered without slicing considerations and in a second step, the concept of slicing in the context of LoRAWAN networks is introduced

Reference architecture for slicing in LoRAWAN networks

This document describes the basic functional architecture of the Intelligentisa project. This document reviews all the elements necessary to run a LoRAWAN network and the associated functions. The objective is to integrate the functional architecture into an orchestration framework, possibly by virtualizing some fundamental functions, such as LoRAWAN network Servers (LNSs). This requires to identify basic functional blocks, in particular telemetry exploiting metrics from the substrate virtualized infrastructure as well as supported LoRAWAN networks, and orchestration functions for the deployment and the optimization of LoRAWAN networks to achieve some performance objectives. In a first step, all these issues are considered without slicing considerations and in a second step, the concept of slicing in the context of LoRAWAN networks is introduced

Reference architecture for slicing in LoRAWAN networks

This document describes the basic functional architecture of the Intelligentisa project. This document reviews all the elements necessary to run a LoRAWAN network and the associated functions. The objective is to integrate the functional architecture into an orchestration framework, possibly by virtualizing some fundamental functions, such as LoRAWAN network Servers (LNSs). This requires to identify basic functional blocks, in particular telemetry exploiting metrics from the substrate virtualized infrastructure as well as supported LoRAWAN networks, and orchestration functions for the deployment and the optimization of LoRAWAN networks to achieve some performance objectives. In a first step, all these issues are considered without slicing considerations and in a second step, the concept of slicing in the context of LoRAWAN networks is introduced