Vers une meilleure utilisation des énergies renouvelables : application à des bâtiments scientifiques

Les travaux de cette thèse portent sur l'optimisation des flux énergétiques et informatiques dans un réseau intelligent ayant pour but d'alimenter un centre de calcul via des énergies renouvelables. Dans cette thèse sont traités les problèmes liés à la mise en commun des informations de types énergétique et informatique dans une contrainte de réactivité forte à travers la création d'une architecture pour un réseau intelligent. La modélisation d'un tel réseau doit permettre la prise de décision de manière dynamique et autonome. L'objectif de cette modélisation, via un réseau intelligent, est l'optimisation des ressources renouvelables afin de diminuer l'empreinte écologique.The work of this thesis deals with the optimization of energy and computer flows in an intelligent network aiming to supply a data center via renewable energies. In this thesis are treated the problems related to the pooling of energy and computer information in a strong reactivity constraint through the creation of an architecture for an intelligent network. The modeling of such a network must allow the decision making in a dynamic and autonomous way. The objective of this modeling, via an intelligent network, is the optimization of renewable resources in order to reduce the ecological footprint

Towards a better use of renewable energies : application to scientific buildings

Les travaux de cette thèse portent sur l'optimisation des flux énergétiques et informatiques dans un réseau intelligent ayant pour but d'alimenter un centre de calcul via des énergies renouvelables. Dans cette thèse sont traités les problèmes liés à la mise en commun des informations de types énergétique et informatique dans une contrainte de réactivité forte à travers la création d'une architecture pour un réseau intelligent. La modélisation d'un tel réseau doit permettre la prise de décision de manière dynamique et autonome. L'objectif de cette modélisation, via un réseau intelligent, est l'optimisation des ressources renouvelables afin de diminuer l'empreinte écologique.The work of this thesis deals with the optimization of energy and computer flows in an intelligent network aiming to supply a data center via renewable energies. In this thesis are treated the problems related to the pooling of energy and computer information in a strong reactivity constraint through the creation of an architecture for an intelligent network. The modeling of such a network must allow the decision making in a dynamic and autonomous way. The objective of this modeling, via an intelligent network, is the optimization of renewable resources in order to reduce the ecological footprint

Vers une meilleure utilisation des énergies renouvelables : application à des bâtiments scientifiques

The work of this thesis deals with the optimization of energy and computer flows in an intelligent network aiming to supply a data center via renewable energies. In this thesis are treated the problems related to the pooling of energy and computer information in a strong reactivity constraint through the creation of an architecture for an intelligent network. The modeling of such a network must allow the decision making in a dynamic and autonomous way. The objective of this modeling, via an intelligent network, is the optimization of renewable resources in order to reduce the ecological footprint.Les travaux de cette thèse portent sur l'optimisation des flux énergétiques et informatiques dans un réseau intelligent ayant pour but d'alimenter un centre de calcul via des énergies renouvelables. Dans cette thèse sont traités les problèmes liés à la mise en commun des informations de types énergétique et informatique dans une contrainte de réactivité forte à travers la création d'une architecture pour un réseau intelligent. La modélisation d'un tel réseau doit permettre la prise de décision de manière dynamique et autonome. L'objectif de cette modélisation, via un réseau intelligent, est l'optimisation des ressources renouvelables afin de diminuer l'empreinte écologique

Modeling and Generating large-scale Google-like Workload

International audienceOne of the key element needed to test most large-scale scheduling algorithms is a testing infrastructure. Large scale is of upmost importance as failures and complex behaviors are common occurrences only at such scale. In order to test the reaction of a system to failures or extreme behaviors, it is necessary to be able to create large scale environments. Such an infrastructure must be reproducible so that several work are able to compare themselves but also capable of diversity as otherwise it would risk to lead to particular subcases. In this article, we propose a generic adaptable and reusable model of large scale workload. The original schema comes from the Google Cluster Workload Traces which is a perfect representative of large scale production workload. Contrary to most model analysis of such traces, we propose along with our model a reference implementation in order for other studies using our results to produce comparable experiments

Txupito - An Interactor Component Model for Ambient HCI

International audienceIn this paper, we describe the Txupito interactor model. Nowadays, application contents are accessible on a wide variety of devices such as laptops, tablets and smartphones but the heterogeneity of such devices does not help programmers to elaborate ambient interactive applications adapted to each device. Indeed, users do not interact in the same way on a tablet, a laptop or a smartphone. Furthermore the design of cooperative HCI (Human Computer Interface) remains a very complex task especially in an ambient and heterogeneous environment. In this paper, we propose a multimodal mobile interactor model, called Txupito, and a set of composition operators as a way to achieve interactions with hardware in a distributed and cooperative way

Green energy efficient scheduling management

International audienceThe analysis of the energy efficiency in Cloud Computing infrastructures has become an important research domain as the utilization rate of the various on-demand services is daily higher and higher and its management is now considered as a main objective. Today, to tackle this challenging issue, Cloud providers integrate renewable energy sources to feed their infrastructure. Energy saving is part often an integral many companies goal. Unlike the classic supply of grid energy, the production of green energy is unstable and depends on nature of the weather or wind. It introduces new challenges as pervasive jobs to reduce a server consumption. In this article, studies based on the use and the storage of photovoltaic energy are exposed. We detail our design of a scheduler which uses solar energy production to make an off-line decision. This enables us to schedule virtual machines into a datacenter via different algorithms which consumes the least amount of brown energy as possible. We based our analysis through an existing workload from Google. We describe and study this workload to create one corresponding to our need. We also proposed to evaluate the storage size of a smartgrid related to the solar panel size. It is an analysis of the reliance between both storage (battery) and renewable energy production (solar panel) components sizing