Contributing to Atos innovation strategy with Cloud and Edge Computing

Computing is becoming increasingly pervasive in all aspects of our live, as "connected things" become more "intelligent things" bringing the need of fully networked computing systems capable of delivering advanced behaviours and interacting with their surroundings. Soon sensors, robots, drones, routers, servers and cars will only be seen as particular forms of infrastructure elements. This way, computing will no longer be constricted to specific devices but will be virtually embedded and pervasive to everything, enabling an unprecedented computing continuum. 

Cloud computing initially emerged in the space in which we transitioned from an era in which underlying computing resources were both scarce and expensive, to an era in which the same resources started to be cheap and abundant, enabling the democratisation of computing and providing the illusion of infinite computing. Today we are observing new forms of Cloud Computing, such as Edge and Fog, starting to break the Data Centre barriers so to provide novel forms of computing embracing power and data resources increasingly available everywhere. The new forms of Cloud are making the Cloud concept evolve a more distributed approach in order to lead to better performance and enabling wider diversity of application and services, complementarily to existing multi-cloud and hybrid cloud models.


Gains in complexity of the connected “intelligent things” will pose specific requirements to Cloud Computing evolution. The self-contained and self-sustaining nature of these resources combined with their size and energy harvesting constrains will require of novel computing and communication architectures.

Developing cloud computing technology compatible with the management of hardware heterogeneity will call for finding ways to optimally endeavour heterogeneous special purpose processing units without losing the advantages of abstraction in utility based models such as development of sharing schemes and heterogeneity-aware scheduling at resource and platform levels.

The advent of fully distributed collaborative Cloud environments is another source of disruption in order to fully exploit computational power of “intelligent things”. These environments are initially taking for in the evolution of Ad-hoc Clouds enabling smart collaboration among mobile devices. Further evolution of this concept will enable the creation of dynamic ecosystems, meshes or swarms of “Intelligent Things”. These will allow the creation of dynamic eco-systems encompassing “intelligent things”, cyber-physical devices, edge and clouds, each of these adding to the collective capability and insight under the term Swarm Computing.

The main goal of this lab is to contribute to Atos research and innovation strategy with regards to Cloud, Edge and Swarm computing developments, models and architectures. 

Main Activities: 
  • Advanced capabilities for IaaS, PaaS and SaaS: Accounting and monitoring; Autonomic resource management; SLA management; Multi-cloud environments IaaS, PaaS and SaaS; Experimental Facilities in Cloud; and Eco-efficiency in Clouds and Data Centres
  • Service Management and Engineering: Advanced Service Architectures and SaaS; Cloud Service Composition, aggregation and orchestration; Service, Application and Data Marketplaces; Trust & Reputation Service Management; and License Management
  • Edge computing: Heterogeneous / Things virtualisation management; Ad-hoc Cloud management; Application offloading; Local Cloud Management; Data Management; and Service Orchestration


  • Cloud Hybrid models: Interoperation, Portability, Federation and Brokerage
  • SLAs, Trust and License Management for Cloud environments
  • Integration of edge and mobile devices into decentralized Cloud architectures for IoT services
  • Energy efficiency in heterogeneous computing environments, Cloud computing and Data centers
  • Big Data Storage and scalability in Big Data processing
  • Cloud-based Experimental facilities
  • Autonomic and self-healing capabilities for Cloud management
  • Cloud Service composition, aggregation and orchestration
  • Cloud Marketplaces, Vertical markets, Added-value services and Applications
  • Cloud Standardization and Compliance
  • Scalability based on predictive models and including heterogeneous resources
  • Heterogeneous and autonomic resource management
Current Research Topics and Findings: 
  • Cloud Service Integration / Multi-Cloud: Improved mechanisms for QoS and SLA Managementz; Scalability; Multi-tenancy / Isolation; Cloud Migration; Application deployment Automation; Improved Cloud Monitoring; Interoperability and Multi-Cloud Provisioning; Cloud Networking; Economy, Cost, Trust and Reputation models; Cloud-marketplaces; and Eco-efficiency
  • Edge (Fog) Computing: Management and heterogeneity; Across Edge execution orchestration; Interoperability and standardization; Off-loading optimization; Edge computing communication topology automation; and Support for heterogeneous and geographically distributed systems
  • DeW Computing: Edge / Fog Service Management; Admission Control; Data abstractions and movement; and Edge Workload management
  • Development areas for Computing Continuum: Swarm management; Cyber-physical Cloud/Edge computing; and Cloud/Edge Robotics



Adaptive gateways for diverse multiple environments
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Modular hardware and software gateway for IoT with support for protocol interoperability, device and data management, apps execution, and external Cloud communication.


Cloud brokerage across borders for mobile users and applications
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Development of an integrated Brokerage Platform targeting federated clouds in order to support dynamic needs of mobile applications and users.


Business and IT-Cloud Alignment using a Smart Socket
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Introduction of the BPaaS concept thanks to smart alignment techniques, packages BPaaS as “extended Cloudlets” autonomously deployable and including adaptive rules to appropriately react in a multi-cloud environment.


Data-intensive applications improvement by moving data and computation in mixed cloud/fog environments
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SDK and an execution environment to overcome the barriers that hamper the adoption of Cloud Computing and increase the adoption of Fog computing.


Integrating distributed data infrastructures for global exploitation
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Development of an innovative cloud platform for the scientific community based on open source software and providing access without restrictions to a diversity of e-Infrastructures.


Towards an open, secure, decentralized and coordinated Fog-to-Cloud management ecosystem
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Design an open, secure, decentralized, multi-stakeholder management framework, with novel programming models, privacy and security, data storage, service creation, brokerage solutions, SLA policies, and resource orchestration methods.


Heterogeneous secure multilevel remote acceleration service for low-power integrated systems and devices
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Development of an efficient heterogeneous cloud computing infrastructure, which can be used to seamlessly offload CPU-based and GPU-based tasks of applications running on low-power as well as more powerful devices over a heterogeneous network.


Symbiosis of smart objects across IoT environments
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Fostering a simplified IoT application and service development process over interworking IoT platforms.


Transparent heterogeneous hardware architecture deployment for energy gain in operation
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Control of underlying heterogeneous hardware architectures, configurations and software systems while providing tools to optimize various dimensions of software design and operations.