PANACEA
Proactive Autonomic Management of Cloud Resources
| Coordinatore | CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE
Organization address
address: avenue Edouard BELIN 16 contact info |
| Nazionalità Coordinatore | France [FR] |
| Totale costo | 3˙172˙422 € |
| EC contributo | 2˙130˙000 € |
| Programma | FP7-ICT
Specific Programme "Cooperation": Information and communication technologies |
| Code Call | FP7-ICT-2013-10 |
| Funding Scheme | CP |
| Anno di inizio | 2013 |
| Periodo (anno-mese-giorno) | 2013-10-01 - 2016-03-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE
Organization address
address: avenue Edouard BELIN 16 contact info |
FR (TOULOUSE) | coordinator | 0.00 |
| 2 |
ATOS CONSULTING CANARIAS SA UNIPERSONAL
Organization address
address: CALLE PASEO TOMAS MORALES 85, PLANTA 1 contact info |
ES (LAS PALMAS DE GRAN CANARIA) | participant | 0.00 |
| 3 |
ATOS SPAIN SA
Organization address
address: Calle de Albarracin 25 contact info |
ES (Madrid) | participant | 0.00 |
| 4 |
IBM ISRAEL - SCIENCE AND TECHNOLOGY LTD
Organization address
address: 94 DERECH EM-HAMOSHAVOT contact info |
IL (PETACH TIKVA) | participant | 0.00 |
| 5 |
IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE
Organization address
address: Exhibition Road, South Kensington Campus contact info |
UK (LONDON) | participant | 0.00 |
| 6 |
INTERNATIONAL RESEARCH INSTITUTE FOR AUTONOMIC NETWORK COMPUTING (IRIANC) EV
Organization address
address: MENRADSSTRASSE 2 contact info |
DE (MUNCHEN) | participant | 0.00 |
| 7 |
QOS DESIGN SARL
Organization address
address: AVENUE MARCEL DORET 6 contact info |
FR (TOULOUSE) | participant | 0.00 |
| 8 |
UNIVERSIDAD COMPLUTENSE DE MADRID
Organization address
address: AVENIDA DE SENECA 2 contact info |
ES (MADRID) | participant | 0.00 |
Mappa
Word cloud
Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.
Obiettivo del progetto (Objective)
The main objective of the project 'PANACEA' is to provide Proactive Autonomic Management of Cloud Resources as a remedy to the exponentially growing complexity.nIf you look at the system resources (Internet) at the bottom of the stack, that system resource can be servers, storage, data centres, and network resources, the concept is then to build a level of virtualization of those resources so that any given event is not tied to one box necessarily or to one storage disk. Once you get that kind of leverage, you can build the set of functions that relate to autonomic self-* properties: configuring, healing, optimizing and protecting. The design that you have to have holistically has to deal with the fact that components are going to fail. The aim of a Cloud Computing platform is to support redundant, self-recovering, highly scalable programming models that allow workloads to recover from many inevitable hardware/software failures and monitoring resource use in real time for providing physical and virtual servers, on which the applications can run.nIt will propose innovative solutions for autonomic management of cloud resources, which will be based on a set of advanced Machine Learning Techniques and virtualization. A Machine Learning (ML) framework will be created for a proactive autonomic management of cloud resources. It will allow predicting the failure time of software, or user applications running on Virtual Machines (VM) and the violation of expected response time of services.nTo deal with the vast number of possible resources to monitor, our main approach will consider the use of mobile agents, which will move on the cloud, interacting with other agents, reading computing and network sensors, and making autonomous decisions on what to measure, when to report and to whom. Distributed Machine Learning, based on Reinforcement Learning and Neural Networks, will be used to enforce 'self-organizing paths'.