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DICE

Title
Developing Data-Intensive Cloud Applications with Iterative Quality Enhancements
Funding
EC | H2020 | RIA
Call
H2020-ICT-2014-1
Contract (GA) number
644869
Start Date
2015/02/01
End Date
2018/01/31
Open Access mandate
yes
Data Pilot
yes
Organizations
FLEX, FLEXIOPS, UniZar, ATC, NETF, XLAB, PRODEVELOP, POLITECNICO DI MILANO, Imperial, IEAT
More information
Detailed project information (CORDIS)

 

  • Palladio Optimization Suite: QoS optimization for component-based Cloud applications

    Ciavotta, Michele; Ardagna, Michele; Koziolek, Anne (2016)
    Projects: EC | DICE (644869)

    Formal verification of storm topologies through D-VerT

    Marconi, Francesco; Bersani, Marcello M.; Rossi, Matteo (2017)
    Projects: EC | DICE (644869)

    Automated parameterization of performance models from measurements

    Casale, G; Spinner, S; Wang, W (2016)
    Projects: EC | DICE (644869)
    Estimating parameters of performance models from empiri- cal measurements is a critical task, which often has a major in uence on the predictive accuracy of a model. This tuto- rial presents the problem of parameter estimation in queue- ing systems and queueing networks. The focus is on reliable estimation of the arrival rates of the requests and of the ser- vice demands they place at the servers. The tutorial covers common estimation techniques such as regression methods, maximum-likeliho...

    Towards a UML profile for data intensive applications

    Gómez, Abel; Merseguer, José; Di Nitto, Elisabetta; Tamburri, Damian A. (2016)
    Projects: EC | DICE (644869)

    A methodology for model-based verification of safety contracts and performance requirements

    Gomez-Martinez, E.; Rodriguez, R. J.; Benac-Earle, C.; Etxeberria, L.; Illarramendi, M. (2016)
    Projects: EC | DICE (644869)

    Towards DevOps for Privacy-by-Design in Data-Intensive Applications

    Guerriero, Michele; Tamburri, Damian A.; Ridene, Youssef; Marconi, Francesco; Bersani, Marcello M.; Artac, Matej (2017)
    Projects: EC | DICE (644869)

    Compact Markov-modulated models for multiclass trace fitting

    Casale, Giuliano; Sansottera, Andrea; Cremonesi, Paolo (2016)
    Projects: EC | DICE (644869)
    Markov-modulated Poisson processes (MMPPs) are stochastic models for fitting empirical traces for simulation, workload characterization and queueing analysis purposes. In this paper, we develop the first counting process fitting algorithm for the marked MMPP (M3PP), a generalization of the MMPP for modeling traces with events of multiple types. We initially explain how to fit two-state M3PPs to empirical traces of counts. We then propose a novel form of composition, called interposition, whic...

    A systematic approach for performance evaluation using process mining: the POSIDONIA operations case study

    Bernardi, Simona; Requeno, José Ignacio; Joubert, Christophe; Romeu, Alberto (2016)
    Projects: EC | DICE (644869)

    Performance Analysis of Apache Storm Applications Using Stochastic Petri Nets

    Requeno, Jose-Ignacio; Merseguer, Jose; Bernardi, Simona (2017)
    Projects: EC | DICE (644869)
  • On The Timed Analysis Of Big-Data Applications - Experimental Data

    Francesco Marconi; Giovanni Quattrocchi; Luciano Baresi; Marcello M. Bersani; Matteo Rossi (2018)
    Publisher: Zenodo
    Projects: EC | DICE (644869)
    This archive includes experimental data associated to the paper: On the Timed Analysis of Big-Data Applications. Accepted in Proceedings of Nasa Formal Methods (NFM 2018).  Marconi, F., Quattrocchi, G., Baresi, L., Bersani, M.M., Rossi, M.. 2018 Specifically, it includes detailed data regarding the verification tasks reported in Section 4 (Implementation and Validation of the Model). In reference to Table 1 of the paper, the archive is organized in the following way: t...

    Accelerating Performance Inference Over Closed Systems By Asymptotic Methods

    Giuliano Casale (2017)
    Publisher: Zenodo
    Projects: EC | DICE (644869)
    This archive includes the research data associated to the paper: Giuliano Casale. Accelerating Performance Inference over Closed Systems by Asymptotic Methods. Proc. ACM Meas. Anal. Comput. Syst., 1(1), 2017. The paper is accepted for presentation at ACM SIGMETRICS 2017. The research data requires MATLAB 2015a or later. Four datasets are included, each corresponding to a section of the paper: - sec5.3.1: Small and medium models without infinite server nodes (Section 5.3.1) - sec...

    Pax: Partition-Aware Autoscaling For The Cassandra Nosql Database

    Salvatore Dipietro; Rajkumar Buyya; Giuliano Casale (2018)
    Publisher: Zenodo
    Projects: EC | DICE (644869)
    Apache Cassandra has emerged as one of the most widely adopted NoSQL databases. However, there is still a limited understanding on how to optimally operate Cassandra in the cloud using autoscaling methods, by which resources can be scaled up or down to reduce operational costs and meet service-level objectives (SLOs). To address this limitation, we present PAX, a partition-aware elastic resource management system for Apache Cassandra. PAX uses low-overhead query sampling and knowledge of ...

    An Uncertainty-Aware Approach To Optimal Configuration Of Stream Processing Systems

    Jamshidi, Pooyan; Casale, Giuliano (2016)
    Publisher: Zenodo
    Projects: EC | DICE (644869)
    The datasets in this release support the results presented in the paper P. Jamshidi, G. Casale, "An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing Systems", accepted for presentation at MASCOTS 2016. An open access to the paper is available at https://arxiv.org/abs/1606.06543 Also open source code is available at https://github.com/dice-project/DICE-Configuration-BO4CO The archive contains 10 comma separated datasets representing perfo...

    Accelerating Performance Inference Over Closed Systems By Asymptotic Methods

    Giuliano Casale (2017)
    Publisher: Zenodo
    Projects: EC | DICE (644869)
    This archive includes the research data associated to the paper: Giuliano Casale. Accelerating Performance Inference over Closed Systems by Asymptotic Methods. Proc. ACM Meas. Anal. Comput. Syst., 1(1), 2017. The paper is accepted for presentation at ACM SIGMETRICS 2017. The research data requires MATLAB 2015a or later. Four datasets are included, each corresponding to a section of the paper: - sec5.3.1: Small and medium models without infinite server nodes (Section 5.3.1) - sec...

    Dice Geofencing Dataset

    Ismael Torres; Christophe Joubert (2018)
    Publisher: Zenodo
    Projects: EC | DICE (644869)
    This folder contains the data used to validate the DICE simulation tool in the Posidonia Operations demonstrator on geofencing carried out in the DICE Project (dice.h2020.eu).  

    Formal Verification Of Storm Topologies Through D-Vert

    Francesco Marconi; Marcello Maria Bersani; Matteo Rossi (2017)
    Publisher: Zenodo
    Projects: EC | DICE (644869)
    This archive includes the research data associated to the paper: Formal verification of storm topologies through D-VerT. In Proceedings of the Symposium on Applied Computing (SAC '17). Francesco Marconi, Marcello M. Bersani, and Matteo Rossi. 2017. ACM, New York, NY, USA, 1168-1174. DOI: https://doi.org/10.1145/3019612.3019769 Specifically it includes the UML models shown in the paper (Figures 7 and 8), the corresponding instances of the Temporal logic models automaticall...

    Validation Of Atc Newsasset Performance Model

    José Ignacio Requeno Jarabo; José Merseguer; Simona Bernardi; Diego Perez-Palacin; Giorgos Giotis; Vasilis Papanikolaou (2017)
    Publisher: Zenodo
    Projects: EC | DICE (644869)
    This file corresponds to the validation results of the performance model used for studying the NewsAsset application, branded by ATC.

    An Uncertainty-Aware Approach To Optimal Configuration Of Stream Processing Systems

    Jamshidi, Pooyan; Casale, Giuliano (2016)
    Publisher: Zenodo
    Projects: EC | DICE (644869)
    The datasets in this release support the results presented in the paper P. Jamshidi, G. Casale, "An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing Systems", accepted for presentation at MASCOTS 2016. An open access to the paper is available at https://arxiv.org/abs/1606.06543 Also open source code is available at https://github.com/dice-project/DICE-Configuration-BO4CO The archive contains 10 comma separated datasets representing perfo...

    Quality Assessment In Devops: Automated Analysis Of A Tax Fraud Detection System

    Perez-Palacin, Diego; Ridene, Youssef; Merseguer, Jose (2017)
    Publisher: Zenodo
    Projects: EC | DICE (644869)
    This work has received funding from the European Union's Horizon 2020 research and innovation framework programme under grant agreement No. 644869 (DICE), the Spanish Government (Ministerio de Economía y Competitividad) under project No. TIN2013- 46238-C4-1-R and The Aragonese Goverment Ref. T27 – DIStributed COmputation (DISCO) research group.
  • Scientific Results

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    PUBLICATIONS BY ACCESS MODE

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    Publications in Repositories

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