Cloud adoption is increasing across all types of organisations. IDC predicts “cloud IT infrastructure spending will reach $53.1B billion by 2019” while identifying that “Over 70% of heavy cloud users are thinking in terms of a "hybrid" cloud strategy”. 451 Research’s Market Monitor forecasts that “the market for cloud computing, including PaaS, IaaS and infrastructure software as a service will achieve $44.2bB by 2020”. Gartner anticipates that “By 2020, over 50% of all new applications developed on PaaS will be IoT-centric”.
Two trends are emerging in this context, on which the NG Cloud Lab’s vision focus its attention.
First, a disruptive approach emerged due to the specific needs of IoT applications enabled by combining network with typical cloud principles in order to create decentralized and disperse cloud platforms, coined under the term “Edge Computing”.
Secondly, a more evolutionary trend focusing on multi-cloud hybrid models. New technological developments together with advances in standardization efforts and, in general, a more cloud computing cloud market, create the necessary ground for making these a reality in the coming years.
Investigation on these is this lab’s main mission, building upon more than ten years of experience performing insightful research in cloud technologies, distributed systems and service engineering.
The main goal of this lab is to contribute to Atos research and innovation strategy with regards to Cloud and Edge computing developments, models and architectures.
The Lab's main research areas are Cloud Service Integration, the so-called Multi-Cloud, and Edge Computing. It addition to this, our work includes research in the intersection among these – nowadays tagged as Dew Computing by some authors- and research topics cross-cutting these lines as application field of the Computing Continuum vision. You can find detailed information about the Lab's Computing Continuum vision, and the specific research topics identified for future work in these research areas here.
1-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
- Eco-efficiency in Clouds and Data Centres
2-Service Management and Engineering: Advanced Service Architectures and SaaS
- Cloud Service Composition, aggregation and orchestration
- Service, Application and Data Marketplaces
- Trust & Reputation Service Management
- License Management
- Heterogeneous / Things virtualisation management
- Ad-hoc Cloud management
- Application offloading
- Local Cloud Management( Processors accelerations, QoS and traditional Cloud interoperability)
- Data Management
- 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
1-Cloud Service Integration / Multi-Cloud
- Improved mechanisms for QoS and SLA Managementz
- Multi-tenancy / Isolation
- Cloud Migration
- Application deployment Automation
- Improved Cloud Monitoring
- Interoperability and Multi-Cloud Provisioning
- Cloud Networking
- Economy, Cost, Trust and Reputation models
2-Edge (Fog) Computing
- Edge (Fog) Management and heterogeneity
- Across Edge execution orchestration
- Interoperability and standardization
- Off-loading optimization
- Edge computing communication topology automation
- Support for heterogeneous and geographically distributed systems
3-DeW Computing: Where the Edge meets the Cloud
- Edge / Fog Service Management
- Admission Control
- Data abstractions and movement in Cloud and Edge computing
- Edge Workload management
4-Development areas for Computing Continuum, Mavericks Cloud Research
- Swarm management among IoE, Edge and Cloud Computing
- Cyber-physical Cloud/Edge computing
- Cloud Robotics
Modular hardware and software gateway for IoT with support for protocol interoperability, device and data management, IoT apps execution, and external Cloud communication.
Provision of novel methods and tools to support software developers aiming to optimize energy efficiency and minimize the carbon footprint resulting from designing, developing, deploying, and running software in Clouds.
Development of an integrated Brokerage Platform targeting federated clouds in order to support dynamic needs of mobile applications and users.
Introduction of the BPaaS concept that fulfills business process needs thanks to smart alignment techniques, packages BPaaS as “extended Cloudlets” autonomously deployable and including adaptive rules to appropriately react in a multi-cloud environment.
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 (public or commercial, GRID/Cloud/HPC).
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.
Solutions to enable seamless adaptive multi-cloud management of complex applications, by supporting distribution, monitoring and migration of application modules over multiple heterogeneous (PaaS) clouds.
Fostering a simplified IoT application and service development process over interworking IoT platforms.
Control of underlying heterogeneous hardware architectures, configurations and software systems while providing tools to optimize various dimensions of software design and operations.