Implementation and Provisioning of Federated Networks in Hybrid Clouds (pre-print)

Federated cloud networking is needed to allow the seamless and efficient interconnection of resources distributed among different clouds. This work introduces a new cloud network federation framework for the automatic provision of Layer 2 (L2) and layer 3 (L3) virtual networks to interconnect geographically distributed cloud infrastructures in a hybrid cloud scenario. After a revision of existing encapsulation technologies to implement L2 and L3 overlay networks, the paper analyzes the main topologies that can be used to construct federated network overlays within hybrid clouds. In order to demonstrate the proposed solution and compare the different topologies, the article shows a proof-of-concept of a real federated network deployment in a hybrid cloud, which spans a local private cloud, managed with OpenNebula, and two public clouds, two different regions of mazon EC2. Results show that L2 and L3 overlay connectivity can be achieved with a minimal bandwidth overhead, lower than 10%

Image Transfer and Storage Cost Aware Brokering Strat. for Multiple Clouds

Cloud Brokering, Resource Allocation, Storage, Data Transfer, SimGrid Cloud BrokerNowadays, Clouds are used for hosting a large range of services. But between different Cloud Service Providers, the pricing model and the price of individual resources are very different. Furthermore hosting a service in one Cloud is the major cause of service outage. To increase resiliency and minimize the monetary cost of running a service, it becomes mandatory to span it between different Clouds. Moreover, due to dynamicity of both the service and Clouds, it could be required to migrate a service at run time. Accordingly, this ability must be integrated into the multi-Cloud resource manager, i.e. the Cloud broker. But, when migrating a VM to a new Cloud Service Provider, the VM disk image must be migrated too. Accordingly, data storage and transfer must be taken into account when choosing if and where an application will be migrated. In this paper, we extend a cost-optimization algorithm to take into account storage costs to approximate the optimal placement of a service. The data storage management consists in taking two decisions: where to upload an image, and keep it on-line during the experiment lifetime or delete it when unused. Although the default approach can be to upload an image on demand and delete it when it is no more used, we demonstrate that by adopting other policies the user can achieve better economical results.De nos jours, les Clouds sont utilisés pour héberger un grand ensemble de services. Mais entre les différents fournisseurs de service Cloud, les modéles de prix et le prix de chaque ressource sont très différents. De plus, héberger un service dans un unique Cloud est une des causes principales d'interruption de service. Pour améliorer la résistance et diminuer le coût monétaire d'une application, il devient obligatoire de la distribuer dans plusieurs Clouds. En outre, à cause de la dynamicité de l'application et des Clouds, il peut être nécessaire de migrer l'application pendant l'exécution. Par conséquence, cette capacité doit être intégrée dans le gestionnaire de ressources multi-Cloud i.e. le Cloud Broker. Mais, quand une VM migre vers un nouveau fournisseur de service Cloud, l'image disque de la VM doit être migrée également. Par conséquence, le stockage et transfert de donnée doivent être pris en compte quand il est choisi si une application doit migrer et où. Dans ce papier, nous étendons un algorithme d'optimisation de coût pour prendre en compte le coût du stockage afin d'approximer le placement optimal d'une application. La gestion du stockage de donnée consiste à devoir prendre 2 décisions: où l'image doit être envoyée et doit-elle être conservée ou supprimée quand elle n'est plus utilisée. Même si l'approche par défaut peut être d'envoyer l'image à la demande et la supprimer quand elle n'est plus utilisée, nous démontrons qu'en adoptant d'autres politiques l'utilisateur peut réussir à atteindre de meilleurs résultats économiques

Interoperable Federated Cloud Networking

The BEACON framework enables the provision of federated cloud infrastructures, with special emphasis on inter-cloud networking and security issues, to support the automated deployment of applications and services across different clouds and datacenters. BEACON is distributed as open source (see http://github.com/BeaconFramework) and some enhancements are being contributed to the OpenNebula and OpenStack cloud management platforms

Cross-Site Virtual Network in Cloud and Fog Computing

The interconnection of the different geographically dispersed cloud and fog infrastructures is a key issue for the development of the fog technology. Although most existing cloud providers and platforms offer some kind of connectivity services to allow the interconnection with external networks, these services exhibit many limitations and they are not suitable for fog computing environments. In this work we present a hybrid fog and cloud interconnection framework, which allows the automatic provision of cross-site virtual networks to interconnect geographically distributed cloud and fog infrastructures. This framework provides a scalable and multi-tenant solution, and a simple and generic interface for instantiating, configuring and deploying Layer 2 and Layer 3 overlay networks across heterogeneous fog and cloud platforms, with abstraction from the underlying cloud/fog technologies and network virtualization technologies

Disk Image Storage, Distribution and Caching for Edge Cloud Infrastructures

Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaFALSEMinisterio de Ciencia e Innovación (MICINN)Comunidad de Madridunpu

On Demand/Agile Deployment of Edge Cloud Infrastructures for Federated Learning

Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaFALSEMinisterio de Ciencia e Innovación (MICINN)Comunidad de Madridunpu

Opportunistic Deployment of Distributed Edge Clouds for Latency-critical Applications

The growing number of latency-critical applications are posing novel challenges for network operators, cloud/hosting companies, and application providers. Edge Computing is the strongest candidate for providing low-latency responses, but it is not yet clear what edge infrastructures will be like. This paper introduces a new platform for enabling an edge infrastructure according to a disaggregated distributed cloud architecture and an opportunistic model based on bare-metal providers. Results from a multi-server online gaming application deployed in a real geo-distributed edge infrastructure show the feasibility, performance and cost efficiency of the solution

Latency and resource consumption analysis for serverless edge analytics

The serverless computing model, implemented by Function as a Service (FaaS) platforms, can offer several advantages for the deployment of data analytics solutions in IoT environments, such as agile and on-demand resource provisioning, automatic scaling, high elasticity, infrastructure management abstraction, and a fine-grained cost model. Nonetheless, in case of applications with strict latency requirements, the cold start problem in FaaS platforms can represent an important drawback. The most common techniques to alleviate this problem, mainly based on instance pre-warming and instance reusing mechanisms, are usually not well adapted to different application profiles and, in general, can entail an extra expense of resources. In this work, we analyze the effect of instance pre-warming and instance reusing on both, application latency (response time) and resource consumption, for a typical data analytics use case (a machine learning application for image classification) with different input data patterns. Furthermore, we propose to extend the classical centralized cloud-based serverless FaaS platform to a two-tier distributed edge-cloud platform to bring the platform closer to the data source and reduce network latencies

BEACON: A Cloud Network Federation Framework

This paper presents the BEACON Framework, which will enable the provision and management of cross-site virtual networks for federated cloud infrastructures in order to support the automated deployment of applications and services across different clouds and datacenters. The proposed framework will support different federation architectures, going from tightly coupled (datacenter federation) to loosely coupled (cloud federation and multi-cloud orchestration) architectures, and will enable the creation of Layer 2 and Layer 3 overlay networks to interconnect remote resources located at different cloud sites. A high level description of the main components of the BEACON framework is also introduced

Agenda de investigación: Smart cities y seguridad en Andalucía

Este documento forma parte del proyecto de investigación "Tecnología y control social: Fundamentos de la gobernanza democrática de la seguridad en Andalucía" PAIDI 2020-PI00941La gobernanza de la seguridad en las Smart cities supone un gran reto a nivel de diseño, planificación y gestión. El número de investigadores y grupos de investigación andaluces en esta temática es aún escaso, lo que puede dificultar avanzar de manera significativa y lograr un impacto científico y una competitividad y transferencia internacional de conocimiento. Por eso uno de los objetivos de este proyecto era establecer una agenda de investigación que permitiera identificar hacia la comunidad de investigadores aquellos temas de mayor relevancia con vistas a focalizar los recursos y generar sinergias entre ellos. Además, el futuro próximo de la gestión de la seguridad en las Smart cities requerirá, sin lugar a dudas, un trabajo multidisciplinar que aglutine a investigadores de diferentes campos, así como a la industria y al sector público, lo que debería favorecer que se lancen iniciativas coherentes y se establezcan líneas de investigación sólidas.Proyecto cofinanciado en un 80% por la Unión Europea, en el marco del Programa Operativo FEDER Andalucía 2014-2020 «Crecimiento inteligente: una economía basada en el conocimiento y la innovación». Proyecto financiado por la Consejería de Transformación Económica, Industria, Conocimiento y Universidades. Código P20-00941Informe de 8 páginas fruto de un taller realizado el 6 de marzo de 202