DICE Project

Developing Data-Intensive Applications with Iterative Qualitative Enhancements

Started in 1 February 2015, for 36 months

Official site: dice-h2020.eu

DICE will offer a novel UML profile and tools that will help software designers reasoning about reliability, safety and efficiency of Big Data applications. The DICE methodology will cover quality assessment, architecture enhancement, continuous testing and agile delivery, relying on principles of the emerging DevOps paradigm.

In order to support the development of high-quality data-intensive applications, DICE aims at:

Tackling skill shortage and steep learning curves in quality-driven development and Big Data technologies through open source development tools, models, and methods Shortening the time to market for data-intensive applications that meet quality requirements, thus reducing costs for independent software vendors, while increasing value for end users Reducing the number and the severity of quality-related incidents by iteratively learning application runtime behavior, feeding back the information to the developers

Partners:

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CloudLightning Project

A self-organising, self-managing heterogeneous Cloud

Started in 1 February 2015, for 36 months

Official site: cloudlightning.eu

The CloudLightning project aims to create a self-organising and self-managing heterogeneous cloud.

Our objective in creating this system is to remove the burden of low-level service provisioning, optimization and orchestration from the cloud consumer and to vest them in the collective response of the individual resource elements comprising the cloud infrastructure. A related objective is to locate decisions pertaining to resource usage with the individual resource components, where optimal decisions can be made. Currently, successful service delivery relies heavily on the over-provisioning of resources. Our goal is to address this inefficient use of resources and consequently to deliver savings to the cloud provider and the cloud consumer in terms of reduced power consumption and improved service delivery, with hyperscale systems particularly in mind.

Partners:

• University College Cork (Ireland),
• Dublin City University (Ireland),
• Norwegian University of Science and Technology (Norvegia),
• Institute e-Austria Timisoara (Romania),
• Centre for Research and Technologies Hellas (Greece),
• Maxeler Technologies (UK),
• Intel Research and Innovation Ireland Limited (Ireland),
• Democritus University of Thrace (Greece)

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MANeUver Project

MANagement agency for cloUd Resources

Principal Investigator: Mădălina Eraşcu

Host Institution: Institute e-Austria Timisoara

Funding Agency: UEFISCDI – Romanian National Authority for Scientific Research and Innovation(PN-III-P2-2.1-PED-2016-0550)

Duration: September 2017 – December 2018

Project Overview

Cloud computing offers attractive options to migrate corporate applications without the software personnel (End Users – EUs) needing to manage any physical resources. While this “ease” is appealing, several issue arise:

Which Cloud Providers (CPs) offer the best infrastructure at a fair budget?
I am no Cloud expert then what are the characteristics of the infrastructure which best fit my application?
To answer these questions one must solve a resource management problem, that is, the allocation of computing, storage, networking and (indirectly) cost resources to a set of applications such that the performance objectives of the application, CPs and EUs are jointly fulfilled. Efficient resource use is typically achieved through virtualization technologies, which facilitate statistical multiplexing of resources across the three parties. There are many approaches which answer separately these questions but there is no comprehensive and easily usable solution for these issues. MANeUveR solves this problem by integrating the following components:
A Provider Acquisition Module, through a Web crawler, will periodically update a database with infrastructure details, in particular virtual machines (VMs) offers (CPUs number, memory, storage, price, operating system, number of IP addresses, transfer rate, etc.) from various CPs.
An Application Description Module will provide the EU the capability to describe and store the VMs characteristics and application constraints in order to be consulted other times and to obtain a profile of the application.
A Recommendation Module will provide a (sub)optimal solution for application deployment in the CP infrastructure regarding the number of VMs needed for deployment and their characteristics.
Using a secure-billing e-mail service and secured web container applications, MANeUveR will demonstrate its effectiveness in real life. The tool will be based on an open-source core to motivate its wide adoption.

Official Website: https://merascu.github.io/links/MANeUveR.html

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FraDyS Project

Theoretical and Numerical Analysis of Fractional-Order Dynamical Systems and Applications

Principal Investigator: Conf. Dr. Habil. Eva Kaslik

Host Institution: Institute e-Austria Timisoara (IeAT)

Funding Agency: UEFISCDI – Romanian National Authority for Scientific Research and Innovation (PN-II-RU-TE-2014-4-0270)

Duration: October 1, 2015 – September 30, 2017

Project Overview:

The main goal of this project is to study qualitative properties of fractional-order dynamical systems such as asymptotic stability and instability, occurrence of bifurcation phenomena and chaotic behaviour, and existence of almost periodic solutions. Moreover, this project also aims to develop reliable sequential and parallel algorithms for the accurate numerical estimation of the solutions of fractional-order dynamical systems with or without delays over large time intervals. The obtained results will be applied to the theoretical and numerical investigation of fractional-order models of neuronal activity and to fractional-order dynamical network models.

Official website: http://fradys.projects.ieat.ro/

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DICE+ Project

Supplement for the activities of the H2020 project DICE

Funding source: Romanian PN-III-P3-3.6 Programme

Code: PN-III-P3-3.6-H2020-2016-0007

Period: August 2016 – January 2018

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CloudLightning+ Project

Supplement for the activities of the H2020 project CloudLightning

Funding source: Romanian PN-III-P3-3.6 Programme

Code: PN-III-P3-3.6-H2020-2016-0005

Period: August 2016 – January 2018

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