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Multi-cloud Execution-ware for Large-scale Optimized Data-Intensive Computing

Total Cost €


EC-Contrib. €






Project "MELODIC" data sheet

The following table provides information about the project.


Organization address
address: PROBLEMVEIEN 5-7
city: OSLO
postcode: 313

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Norway [NO]
 Project website
 Total cost 4˙890˙223 €
 EC max contribution 4˙890˙223 € (100%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2016-1
 Funding Scheme RIA
 Starting year 2016
 Duration (year-month-day) from 2016-12-01   to  2020-01-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITETET I OSLO NO (OSLO) coordinator 653˙911.00
3    SIMULA RESEARCH LABORATORY AS NO (FORNEBU) participant 885˙470.00
4    UNIVERSITAET ULM DE (ULM) participant 717˙677.00
5    CAS SOFTWARE AG DE (KARLSRUHE) participant 621˙875.00
7    CE-TRAFFIC AS CZ (PRAHA) participant 473˙553.00


 Project objective

MELODIC will enable data-intensive applications to run within defined security, cost, and performance boundaries seamlessly on geographically distributed and federated cloud infrastructures. Serving the user’s needs and constraints, MELODIC will realise the potential of Cloud computing for big data and data-intensive applications by transparently taking advantage of distinct characteristics of available private and public clouds, dynamically optimise resource utilisation, consider data locality, conform to the user’s privacy needs and service requirements, and counter vendor lock-in.

These benefits are achieved by integrating and extending the results and the open source platforms available from three major European Cloud projects with the Hadoop and Spark big data frameworks: The PaaSage platform will be used for intelligent and autonomic cross-cloud deployment and is extended with data aware modelling and deployment configuration reasoning; the CACTOS platform is extended with support for Hadoop and Spark in cross-Cloud application deployment and management; and the PaaSword platform will ensure unified data security and cross-Cloud privacy.

MELODIC will integrate with the existing open source development teams for these platforms and the contributions will be released back to the used platforms as open source. The integrated MELODIC platform will be maintained and exploited by a professional software house, and tested in several demanding real world applications: scalable Customer Relationship Management, real-time optimised traffic routing, and fast and scalable processing of genomic data.


List of deliverables.
System specification document Documents, reports 2020-01-20 15:57:27
Updates to OSS frameworks Documents, reports 2020-01-20 15:57:27
Evaluation Framework and Use Case Planning Documents, reports 2020-01-20 15:57:27
Dissemination and communication plan Documents, reports 2020-01-20 15:57:27
Metadata schema management Other 2020-01-20 15:57:27
Integration release and initial test environment Other 2020-01-20 15:57:27
Continuous integration platform & guidelines Documents, reports 2020-01-20 15:57:27
Integration & testing requirements Documents, reports 2020-01-20 15:57:27
Report on data placement and migration methodologies Documents, reports 2020-01-20 15:57:27
Quality Assurance Guide Documents, reports 2020-01-20 15:57:27
Metadata schema Documents, reports 2020-01-20 15:57:27
Architecture and initial feature definitions Documents, reports 2020-01-20 15:57:27
Provider agnostic interface definition & mapping cycle Documents, reports 2020-01-20 15:57:27
Integration and adaptation strategy Documents, reports 2020-01-20 15:57:27
Explanation and education materials Documents, reports 2020-01-20 15:57:27
Test strategy and environment Documents, reports 2020-01-20 15:57:27
IDE-plugin for data-aware design and development of multi-cloud data-intensive applications Other 2020-01-20 15:57:27

Take a look to the deliverables list in detail:  detailed list of MELODIC deliverables.


year authors and title journal last update
List of publications.
2019 Kyriakos Kritikos, Chrysostomos Zeginis, Joaquin Iranzo, Roman Sosa Gonzalez, Daniel Seybold, Frank Griesinger, Jörg Domaschka
Multi-cloud provisioning of business processes
published pages: , ISSN: 2192-113X, DOI: 10.1186/s13677-019-0143-x
Journal of Cloud Computing 8/1 2020-04-01
2019 Jörg Domaschka and Daniel Seybold
Towards Understanding the Performance of Distributed Database Management Systems in Volatile Environments
published pages: , ISSN: , DOI:
10th Symposium on Software Performance 2019, 4.-6. November 2019, Würzburg, Germany 2020-04-01
2019 Somnath Mazumdar, Daniel Seybold, Kyriakos Kritikos, Yiannis Verginadis
A survey on data storage and placement methodologies for Cloud-Big Data ecosystem
published pages: , ISSN: 2196-1115, DOI: 10.1186/s40537-019-0178-3
Journal of Big Data 6/1 2020-01-20
2019 D Seybold, S Volpert, S Wesner, A Bauer, N Herbst, J Domaschka;
Kaa: Evaluating Elasticity of Cloud-hosted DBMS;
published pages: , ISSN: , DOI:
2017 Geir Horn, Ernst G. Gran
Modelling Application Data for Analysis
published pages: , ISSN: , DOI:
2018 Feroz Zahid, Amir Taherkordi, Ernst Gunnar Gran, Tor Skeie, Bjorn Dag Johnsen
A Self-Adaptive Network for HPC Clouds: Architecture, Framework, and Implementation
published pages: 1-1, ISSN: 1045-9219, DOI: 10.1109/TPDS.2018.2842224
IEEE Transactions on Parallel and Distributed Systems 2020-01-20
2017 Daniel Seybold, Jörg Domaschka
Is Distributed Database Evaluation Cloud-Ready?
published pages: 100-108, ISSN: , DOI: 10.1007/978-3-319-67162-8_12
New Trends in Databases and Information Systems: ADBIS 2017 Short Papers and Workshops, AMSD, BigNovelTI, DAS, SW4CH, DC, Nicosia, Cyprus, September 24–27, 2017, Proceedings 2020-01-20
Big Data Applications on Multi-Clouds: An Introduction to the MELODIC Project
published pages: , ISSN: , DOI:
2018 Amir Taherkordi, Feroz Zahid, Yiannis Verginadis, Geir Horn
Future Cloud Systems Design: Challenges and Research Directions
published pages: 1-1, ISSN: 2169-3536, DOI: 10.1109/ACCESS.2018.2883149
IEEE Access 2020-01-20

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