Objectif
Currently cloud infrastructures are mostly homogeneous -- composed of a large number of machines of the same type -- centrally managed and made available to the end user using the three standard delivery models: Infrastructure-as-a-service (IaaS), Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS). As clouds increase in size and as machines of different types are added to the infrastructure in order to maximise performance and power efficiency, heterogeneous clouds are being created. However, exploiting different architectures such as graphics processing units, many integrated cores and data flow engines, poses significant challenges.To efficiently access heterogeneous resources and, at the same time, to exploit these resources to reduce application development effort, to make optimisations easier and to simplify service deployment requires a reevaluation of our approach to service delivery.
The evolving complexity of the cloud ecosystem will eventually render traditional cloud management techniques ineffectual. Self-organisation and self-management are powerful techniques for managing complexity. Some of our initial simulation results using self organisation and self optimisation indicate that these can be used as the basis of a new cloud management and delivery model capable of efficiently dealing with issues that arise at scale. Our preliminary work has centred on promoting access to power efficient heterogeneous resources by shifting the deployment and optimization effort from the consumer to the software stack running on the cloud infrastructure. With CloudLightning, we propose to extend this work and to build a cloud management and delivery infrastructure based on these principles.
Given the prohibitive expense associated with empirical experimentation on hyperscale cloud infrastructures, data gathered on our testbed will be used to simulate this infrastructure and to evaluate the self organisation approach in that context.
Champ scientifique (EuroSciVoc)
CORDIS classe les projets avec EuroSciVoc, une taxonomie multilingue des domaines scientifiques, grâce à un processus semi-automatique basé sur des techniques TLN.
CORDIS classe les projets avec EuroSciVoc, une taxonomie multilingue des domaines scientifiques, grâce à un processus semi-automatique basé sur des techniques TLN.
- sciences naturellessciences biologiquesgénétique
- sciences naturellesinformatique et science de l'informationlogiciel
- sciences naturellesinformatique et science de l'informationscience des donnéesmégadonnées
- ingénierie et technologiegénie électrique, génie électronique, génie de l’informationingénierie électroniquematériel informatiquesupercalculateur
- sciences naturellesinformatique et science de l'informationintelligence artificielleapprentissage automatique
Vous devez vous identifier ou vous inscrire pour utiliser cette fonction
Mots‑clés
Programme(s)
Régime de financement
RIA - Research and Innovation actionCoordinateur
T12 YN60 Cork
Irlande