The goal of the GRECO project is to develop a reference resource manager for cloud of things


Find out more about the goals and objectives of the GRECO project here


Learn about the project’s consortium here


Our latest news are available here










In a nutshell

Qarnot computing is a young company incorporated in 2010 in Paris, France. Qarnot designed and operates the Q.rad, the first computing heater using embedded computers as a heat source. Totally silent, connected to the Internet, it performs remotely complex operations for computing companies and institutions. The heat produced by workload processing provides free and efficient heating for homes, public buildings and offices. Qarnot drastically reduces cloud High-performance computing (HPC) environmental footprint in an economically efficient manner.

Qarnot recently unveiled a new version of the Q.rad during CES ’17 in Las Vegas, fully equipped with sensors (presence, sound, air quality…) to propose ambient intelligence integrated within the building.

Project role

In GRECO project, Qarnot is providing its distributed computing for experimentation and actual smart building use cases and cloud of things. Qarnot will also contribute to scheduling activities.

Project’s responsible

Yanik NGOKO, PhD Research Engineer







In a nutshell

Grenoble Informatics Laboratory (LIG) is one of the largest laboratories in Computer Science in France. It is structured as a Joint Research Center (French Unité Mixte de Recherche – UMR).

500 members of LIG (faculty, full-time researchers, PhD students, administrative and technical staff) are distributed over three sites in Grenoble and its suburbs: the Saint Martin d’Hères Campus, Minatec, and the Montbonnot Campus.

The mission of LIG is to contribute to the development of fundamental aspects of Computer Science (models, languages, methodologies, algorithms) and address conceptual, technological, and societal challenges. Increasing diversity and dynamism of data, services, interaction devices, and use cases influence the evolution of software and systems so they need to guarantee the essential properties such as reliability, performance, autonomy, and adaptability.

Project role

LIG’s scientific role in the GRECO project will focus on ambient and pervasive IT, combining sustainable objectives.

Two LIG’s teams will be involved in the GRECO project, DATAMOVE dedicated to efficient scheduling in large computing infrastructure, AMA (dAta analysis, Modeling and mAchine learning) dedicated to machine learning and information modeling for complex data.

Project’s responsible

Denis TRYSTRAM, Professor








In a nutshell

ASCOLA addresses the general problem of structuring and evolving software by developing concepts, languages, implementations and tools for building software architectures based on components and aspects. Its long term goal is the development of new abstractions for the programming of software architectures, their representation in terms of expressive programming languages and their correct and efficient implementation.

Research and implementation are strongly linked to validate our results in the context of significant applications in the domains of enterprise information systems, service-oriented architectures (middleware, business components), cluster and grid programming, as well as pervasive systems.

Project role

ASCOLA’s role in the project is targeting the implementation and the use of a new paradigm for large scale infrastructure management, especially regarding data storage.

Project’s responsible

Adrien LEBRE, researcher





Related projects

Beyond the Clouds – Revise OpenStack to satisfy Fog/Edge computing requirements, IPL Discovery (http://beyondtheclouds.github.io)




Billion of connected devices are announced in 2020. This could cause a major revolution in ambient intelligence if we can formulate appropriate architectures to process the massive data that will be produced or required by these devices.



The manager should act at the IaaS, PaaS and SaaS layer of the cloud. One of the principal challenges here will consist in handling the execution context of the environment in which the cloud of things operate. Indeed, unlike classical resource managers, connected devices imply to consider new types of networks, execution supports, sensors and new constraints like human interactions. The great mobility and variability of these contexts complexify the modelling of the quality of service. To face this challenge, we intend to innovate in designing scheduling and data management systems that will use machine learning techniques to automatically adapt their behaviour to the execution context. Adaptation here requires a modelling of the recurrent cloud of things usages, the modelling of the physical cloud architecture, as well dynamically.



Scientific Impact

From a scientific point of view, the GRECO project establishes the theoretical and practical foundations for the formulation of distributed resource management systems for clouds of things and, more broadly, distributed clouds at the edge of the network (Fog / Edge Computing).

Indeed, the integration of connected devices generates new industrial practices and processes, it is therefore necessary to propose actual solutions to this new generation of applications.

In addition, the increase in local data production due to such cloud of things will impose to work on disruptive scheduling techniques. Indeed, data access is network dependant (latency, bandwidth, etc.) that might imply reorganizing the distributed storage. The scheduling is also constrained by memory, computing power, network to ensure quality of service also for these distributed clouds of things.

Economic impact

From economical point of view, the GRECO project will open up new economic opportunities regarding smart environments and ambient intelligence. The Internet of Things disrupts smart building / cities,

factories by integrating these connected elements into traditional processes. The GRECO project aims to offer a solution that takes into account the applications and services needs at the edge of the networks, to propose smart use of local and centralized clouds.

Local clouds could provide an answer to confidentiality issues for personal data processing, and also to resilience and the responsiveness of the applications. With a distributed resource manager, it would be possible to organize intelligent and autonomous environments without going through the centralized data centers. This opens up opportunities for companies that operate cloud of things or in the design of stand-alone distributed environments.

Project breakdown structure

T0: Project Management

Tasks coordination and interaction management with funding agency ANR.

T1: Modelling Clouds of Things

The purpose of this task is to propose generic models to conceptualize (statically and dynamically) the architecture of clouds of things, and the diversity of applications that can be processed at the edge. Regarding cloud of things, static modelling needs to include sensors, interfaces, storage nodes, motherboards, networks, actuators, etc. Dynamically, we plan to map communications and the modes of interactions between connected objects.

T2: Task scheduling system

Based on the models proposed in task T1, the goal is to formulate the algorithms for tasks scheduling. The scheduling algorithms must be designed to be auto adaptive to quality of service uncertainty as well as the performance constraints specific to cloud of things (IT power, memory capacity, interactions etc.). The scheduling algorithms will be validated by emulating intelligent environments on the Qarnot radiator platform.

T3: Distributed storage management system

In this task, we will investigate a distributed storage system capable of managing uncertainties related of cloud of things infrastructure (bandwidth variability, storage localisation and access, etc.) to propose more efficient data management techniques. These mechanisms will be evaluated by emulation with Grid’5000 platform and then in real conditions on Qarnot infrastructure which will serve as a test platform. Secondly, we propose to implement new interfaces to access these mechanisms through a dedicated resource manager proposed as an API.

T4: Cloud of Things Resource Manager

This task will consist first in integrating the results of the previous tasks to build a cloud of things resource manager. It will also be necessary at this stage to develop a rules engine for cloud of things application. Integration will be assessed through smart building and ambient intelligence emulations. Emulations will integrate the actual environments where in-situ learning will be done in order to calibrate on the following functions: presence detection, presence classification, noise classification, prediction of ambient air quality, prediction of room temperature.

Organisation chart

The project is structured as follow :


ANR funding

The project has been funded by French National Research Agency (ANR, Agence Nationale de la Recherche) through PRCE 2016 call for proposals. The project reference is ANR-16- CE25-0016, GRECO is planned over 42 months starting on April 2017.


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Events & News

ICFEC’2017 – 1st IEEE International Conference on Fog and Edge Computing – May 14th, 2017

Bastien Confais, Adrien Lèbre and Benoît Parrein An Object Store Service for a Fog/Edge Computing Infrastructure based on IPFS and Scale-out NAS Fog and Edge Computing infrastructure have been proposed to address the latency issue of the current Cloud Computing platforms. While a couple of works illustrated the advantages of these infrastructures in particular for …

EURO-PAR 2017 – 23rd International European Conference On Parallel And Distributed Computing – Santiago de Compostela, Spain, August 28th to September 1st, 2017

Euro-Par is an annual series of international conferences dedicated to the promotion and advancement of all aspects of parallel and distributed computing. Euro-Par covers a wide spectrum of topics from algorithms and theory to software technology and hardware-related issues, with application areas ranging from scientific to mobile and cloud computing. Euro-Par provides a forum for …

ACM/IEEE Symposium on Edge Computing – San Jose, CA, October 12-14, 2017

« Edge computing » is a new paradigm in which the resources of a small data center are placed at the edge of the Internet, in close proximity to mobile devices, sensors, and end users, and the emerging Internet of Things. Terms such as « cloudlets, » « micro data centers, » and « fog » have been used in the literature to …


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