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.
- 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
- 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