Industrial-Driven Big Data as a Self-Service Solution

Livrables

Big-Data-as-a-Self-Service Test and Integration Report v2

This deliverable is a 2nd version of the Big-Data-as-a-Self-Service Test and Integration report [T5.2, T5.3, T5.4].

This report will document the I-BiDaaS integrated end-to-end solution for collecting, aggregating, pre-processing and transforming real-time streaming raw data (structured, unstructured, noisy and possibly incomplete) into structured messages of a common, unified, format [T2.2].

Experiments implementation - initial version

This is a initial report on the I-BiDaaS experiments implementation [T6.1, T6.2, T6.3].

The Data Fabrication Platform (DFP, Interim version)

This deliverable will describe the I-BIDaaS automated methodology for fabrication of synthetic and realistic data sets [T2.3].

The Data Fabrication Platform (DFP, Final Version)

This deliverable will describe the I-BIDaaS automated methodology for fabrication of synthetic and realistic data sets [T2.3].

Federated Resource Management for Data Analytics v2

This deliverable is the 2nd version of the report on the I-BiDaaS Federated Resource Management for Data Analytics [T5.1, T5.2].

Batch Processing Analytics module implementation final report

This is the final report in the I-BiDaaS Batch Processing Analytics module implementation [T3.1, T3.2, T3.3, T3.4].

Streaming analytics and predictions

This deliverable will report on the streaming analytics and predictions for I-BiDaaS [T4.1, 4.2, T4.3].

I-BiDaaS visualization and monitoring framework, and a multi-purpose interface

This deliverable will contain the implementation of the interactive visualization and monitoring toolkit for I-BiDaaS [T2.4].

Assessment report and impact analysis

This deliverable will contain an assessment report and impact analysis for I-BiDaaS [T6.4].

Batch Processing Analytics module implementation as part of I-BiDaaS solution

This deliverable will report in the Batch Processing Analytics module implementation as part of I-BiDaaS solution [T3.1, T3.2, T3.3, T3.4].

Federated Resource Management for Data Analytics v3

This deliverable is the final version of the report on the I-BiDaaS Federated Resource Management for Data Analytics [T5.1, T5.2].

Third report on Dissemination strategy and activities

This deliverable is the third year report on the I-BiDaaS Dissemination strategy and activities [T7.2].

Experiments implementation

This deliverable will report on the implementation of the I-BiDaaS experiments [T6.1, T6.2, T6.3].

Positioning of I-BiDaaS

This deliverable will report on the detailed functionality of the I-BiDaaS platform, according to the user’s needs, the state-of-the-art in distributed data and process mining, predictive analytics and real-time complex event processing over extremely large numbers of high volume streams that are produced in project’s industrial domains [T1.1, T1.2, T1.3, T1.4].

Second report on Dissemination strategy and activities

This deliverable is the second year report on the I-BiDaaS Dissemination strategy and activities [T7.2].

First report on Dissemination strategy and activities

This deliverable is the fist year report on the I-BiDaaS Dissemination strategy and activities [T7.2].

Federated Resource Management for Data Analytics v1

This deliverable is the 1st version of the report on the I-BiDaaS Federated Resource Management for Data Analytics [T5.1, T5.2].

Big-Data-as-a-Self-Service Test and Integration Report

This deliverable is a 1st version of the Big-Data-as-a-Self-Service Test and Integration report [T5.2, T5.3, T5.4].

Distributed event-processing engine

This deliverable will report on the I-BiDaaS Distributed event-processing engine [T4.1, 4.2].

Big-Data-as-a-Self-Service Test and Integration Report v3

This deliverable is the final version of the Big-Data-as-a-Self-Service Test and Integration report [T5.2, T5.3, T5.4].

Universal Messaging Bus (Interim Version)

Batch Processing Analytics module implementation

This deliverable will report on the I-BiDaaS Batch Processing Analytics module implementation [T3.1, T3.2, T3.3, T3.4].

Project website

This deliverable the I-BiDaaS Website [T7.2]

Publications

Big Data Analytics in the Manufacturing Sector: Guidelines and Lessons Learned through the Centro Ricerche FIAT (CRF) Case

Auteurs: Andreas Alexopoulos; Yolanda Becerra; Omer Boehm; George Bravos; Vassilis Chatzigiannakis; Cesare Cugnasco; Giorgos Demetriou; Iliada Eleftheriou; Spiros Fotis; Gianmarco Genchi; Sotiris Ioannidis; Dusan Jakovetic; Leonidas Kallipolitis; Vlatka Katusic; Evangelia Kavakli; Despina Kopanaki; Christoforos Leventis; Miquel Martínez; Julien Mascolo; Nemanja Milosevic; Enric Pages; Gerald Ristow; Herna
Publié dans: Technologies and Applications for Big Data Value, Numéro 16, 2021
Éditeur: Springer Nature Switzerland AG
DOI: 10.5281/zenodo.4540169

Big Data Analytics in the Banking Sector: Guidelines and Lessons Learned from the CaixaBank Case

Auteurs: Andreas Alexopoulos; Yolanda Becerra; Omer Boehm; George Bravos; Vasilis Chatzigiannakis; Cesare Cugnasco; Giorgos Demetriou; Iliada Eleftheriou; Lidija Fodor; Spiros Fotis; Sotiris Ioannidis; Dusan Jakovetic; Leonidas Kallipolitis; Vlatka Katusic; Evangelia Kavakli; Despina Kopanaki; Christoforos Leventis; Mario Maawad Marcos; Ramon Martin de Pozuelo; Miquel Martínez; Nemanja Milosevic; Enric Pa
Publié dans: Technologies and Applications for Big Data Value, Numéro 5, 2021
Éditeur: Springer Nature Switzerland AG
DOI: 10.5281/zenodo.4540175

Challenges in Resource Provisioning for the Execution of Data Wrangling Workflows on the Cloud: A Case Study

Auteurs: Abdullah Khalid A. Almasaud, Agresh Bharadwaj, Sandra Sampaio, Rizos Sakellariou
Publié dans: Database and Expert Systems Applications - 31st International Conference, DEXA 2020, Bratislava, Slovakia, September 14–17, 2020, Proceedings, Part II, Numéro 12392, 2020, Page(s) 66-75, ISBN 978-3-030-59050-5
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-030-59051-2_5

Parallel Differentially Private K-Means Implementation Using COMPSs Framework

Auteurs: Sukpisit, Sukgamon; Skrbic, Srdjan; Jakovetic, Dusan
Publié dans: 10th International Conference on Information Society and Technology (ICIST 2020), Numéro 13, 2020, Page(s) 222-225
Éditeur: Springer
DOI: 10.5281/zenodo.4314276

Pythia: Scheduling of Concurrent Network Packet Processing Applications on Heterogeneous Devices

Auteurs: Giannis Giakoumakis, Eva Papadogiannaki, Giorgos Vasiliadis, Sotiris Ioannidis
Publié dans: 2020 6th IEEE Conference on Network Softwarization (NetSoft), 2020, Page(s) 145-149, ISBN 978-1-7281-5684-2
Éditeur: IEEE
DOI: 10.1109/NetSoft48620.2020.9165447

Towards a Multi-Perspective Methodology for Big Data Requirements

Auteurs: Evangelia Kavakli; Rizos Sakellariou,; Iliada Eleftheriou; Julien Etienne Mascolo
Publié dans: 2020 IEEE International Conference on Big Data (IEEE BigData 2020), Numéro 13, 2020
Éditeur: IEEE
DOI: 10.5281/zenodo.4317758

High performance encrypted network traffic inspection using hardware accelerators

Auteurs: Eva Papadogiannaki; Giorgos Vasiliadis; Sotiris Ioannidis
Publié dans: The 14th International Conference on emerging Networking EXperiments and Technologies (CoNEXT 2018), Numéro 5, 2018
Éditeur: ACM
DOI: 10.5281/zenodo.2635460

Please Forget Where I Was Last Summer: The Privacy Risks of Public Location (Meta)Data

Auteurs: Kostas Drakonakis, Panagiotis Ilia, Sotiris Ioannidis, Jason Polakis
Publié dans: Proceedings 2019 Network and Distributed System Security Symposium, Numéro Network and Distributed Systems Security (NDSS) Symposium 2019, 2019, ISBN 1-891562-55-X
Éditeur: Internet Society
DOI: 10.14722/ndss.2019.23151

Efficient Scheduling for Concurrently Executed Network Packet Processing Applications on Heterogeneous Hardware Architectures

Auteurs: Giannis Giakoumakis; Eva Papadogiannaki; Giorgos Vasiliadis; Sotiris Ioannidis
Publié dans: The 14th International Conference on emerging Networking EXperiments and Technologies (CoNEXT 2018), Numéro 8, 2018
Éditeur: ACM
DOI: 10.5281/zenodo.2635468

Towards Specification of a Software Architecture for Cross-Sectoral Big Data Applications

Auteurs: Arapakis, Ioannis; Becerra, Yolanda; Boehm, Omer; Bravos, George; Chatzigiannakis, Vassilis; Cugnasco, Cesare; Demetriou, Giorgos; Eleftheriou, Iliada; Mascolo, Julien; Fodor, Lidija; Ioannidis, Sotiris; Jakovetic, Dusan; Kallipolitis, Leonidas; Kavakli, Evangelia; Kopanaki, Despina; Kourtellis, Nicolas; Marcos, Mario Maawad; Martin de Pozuelo, Ramon; Milosevic, Nemanja; Morandi, Giuditta; Pages M
Publié dans: 2019 IEEE World Congress on Services, Numéro 7, 2019
Éditeur: IEEE
DOI: 10.5281/zenodo.3333486

There goes Wally: Anonymously sharing your location gives you away

Auteurs: Apostolos Pyrgelis, Nicolas Kourtellis, Ilias Leontiadis, Joan Serra, Claudio Soriente
Publié dans: 2018 IEEE International Conference on Big Data (Big Data), 2018, Page(s) 1218-1227, ISBN 978-1-5386-5035-6
Éditeur: IEEE
DOI: 10.1109/bigdata.2018.8622184

Spectral-like gradient method for distributed optimization

Auteurs: Jakovetic, Dusan; Krejic, Natasa; Krklec Jerinkic, Natasa
Publié dans: IEEE EUROCON 2019, Numéro 3, 2019
Éditeur: IEEE
DOI: 10.5281/zenodo.3333533

Distributed Trust-Region Method With First Order Models

Auteurs: Armacki, Aleksandar; Jakovetic, Dusan; Krejic, Natasa; Krklec Jerinkic, Natasa
Publié dans: EUROCON 2019, Numéro 1, 2019
Éditeur: IEEE
DOI: 10.5281/zenodo.3333539

A Simple Convolutional Generative Network for Next Item Recommendation

Auteurs: Fajie Yuan, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose, Xiangnan He
Publié dans: Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining - WSDM '19, 2019, Page(s) 582-590, ISBN 9781-450359405
Éditeur: ACM Press
DOI: 10.1145/3289600.3290975

NON-ASYMPTOTIC RATES FOR COMMUNICATION EFFICIENT DISTRIBUTED ZEROTH ORDER STRONGLY CONVEX OPTIMIZATION

Auteurs: Anit Kumar Sahu, Dusan Jakovetic, Dragana Bajovic, Soummya Kar
Publié dans: 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2018, Page(s) 628-632, ISBN 978-1-7281-1295-4
Éditeur: IEEE
DOI: 10.1109/globalsip.2018.8646406

Distributed Zeroth Order Optimization Over Random Networks: A Kiefer-Wolfowitz Stochastic Approximation Approach

Auteurs: Anit Kumar Sahu, Dusan Jakovetic, Dragana Bajovic, Soummya Kar
Publié dans: 2018 IEEE Conference on Decision and Control (CDC), 2018, Page(s) 4951-4958, ISBN 978-1-5386-1395-5
Éditeur: IEEE
DOI: 10.1109/cdc.2018.8619044

Convergence Rates for Distributed Stochastic Optimization Over Random Networks

Auteurs: Dusan Jakovetic, Dragana Bajovic, Anit Kumar Sahu, Soummya Kar
Publié dans: 2018 IEEE Conference on Decision and Control (CDC), 2018, Page(s) 4238-4245, ISBN 978-1-5386-1395-5
Éditeur: IEEE
DOI: 10.1109/cdc.2018.8619228

An Architecture and Stochastic Method for Database Container Placement in the Edge-Fog-Cloud Continuum

Auteurs: Kochovski Petar; Sakellariou Rizos; Bajec Marko; Drobintsev Pavel; Stankovski Vlado
Publié dans: 33rd IEEE International Parallel & Distributed Processing Symposium (IPDPS 2019), Numéro 5, 2019
Éditeur: IEEE
DOI: 10.5281/zenodo.2548463

Towards a Methodology for Evaluating Big Data Platforms

Auteurs: Evangelia Kavakli, Rizos Sakellariou, Vlado Stankovski
Publié dans: 2019 IEEE World Congress on Services (SERVICES), 2019, Page(s) 380-381, ISBN 978-1-7281-3851-0
Éditeur: IEEE
DOI: 10.1109/services.2019.00113

GPU-accelerated encrypted network traffic inspection

Auteurs: Eva Papadogiannaki, Sotiris Ioannidis
Publié dans: ACM Celebration of Women in Computing: womENcourage 2019 (womENcourage 2019), 2019
Éditeur: ACM
DOI: 10.5281/zenodo.3472929

TrustAV - Practical and Privacy Preserving Malware Analysis in the Cloud

Auteurs: Dimitris Deyannis, Eva Papadogiannaki, Giorgos Kalivianakis, Giorgos Vasiliadis, Sotiris Ioannidis
Publié dans: Proceedings of the Tenth ACM Conference on Data and Application Security and Privacy, 2020, Page(s) 39-48, ISBN 9781450371070
Éditeur: ACM
DOI: 10.1145/3374664.3375748

The OTree: Multidimensional Indexing with efficient data Sampling for HPC

Auteurs: Cesare Cugnasco, Hadrien Calmet, Pol Santamaria, Raul Sirvent, Ane Beatriz Eguzkitza, Guillaume Houzeaux, Yolanda Becerra, Jordi Torres, Jesus Labarta
Publié dans: 2019 IEEE International Conference on Big Data (Big Data), 2019, Page(s) 433-440, ISBN 978-1-7281-0858-2
Éditeur: IEEE
DOI: 10.1109/bigdata47090.2019.9006121

Head(er)Hunter: Fast Intrusion Detection using Packet Metadata Signatures

Auteurs: Eva Papadogiannaki, Dimitris Deyannis, Sotiris Ioannidis
Publié dans: 2020 IEEE 25th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), 2020, Page(s) 1-6, ISBN 978-1-7281-6339-0
Éditeur: IEEE
DOI: 10.1109/camad50429.2020.9209308

A framework for multidimensional indexes on distributed and highly-available data stores

Auteurs: Cesare Cugnasco, Yolanda Becerra, Jordi Torres
Publié dans: 2019
Éditeur: Universitat Politècnica de Catalunya

Communication efficient distributed weighted non-linear least squares estimation

Auteurs: Anit Kumar Sahu, Dusan Jakovetic, Dragana Bajovic, Soummya Kar
Publié dans: EURASIP Journal on Advances in Signal Processing, Numéro 2018/1, 2018, Page(s) 1-15, ISSN 1687-6180
Éditeur: Springer
DOI: 10.1186/s13634-018-0586-0

Distributed second order methods with increasing number of working nodes

Auteurs: Natasa Krklec Jerinkic, Dusan Jakovetic, Natasa Krejic, Dragana Bajovic
Publié dans: IEEE Transactions on Automatic Control, 2019, Page(s) 1-1, ISSN 0018-9286
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tac.2019.2922191

Acceleration of Intrusion Detection in Encrypted Network Traffic Using Heterogeneous Hardware

Auteurs: Eva Papadogiannaki, Sotiris Ioannidis
Publié dans: Sensors, Numéro 21/4, 2021, Page(s) 1140, ISSN 1424-8220
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/s21041140

Exact spectral-like gradient method for distributed optimization

Auteurs: Dušan Jakovetić, Nataša Krejić, Nataša Krklec Jerinkić
Publié dans: Computational Optimization and Applications, Numéro 74/3, 2019, Page(s) 703-728, ISSN 0926-6003
Éditeur: Kluwer Academic Publishers
DOI: 10.1007/s10589-019-00131-8

I-BiDaaS: Industrial-Driven Big Data as a Self-Service Solution

Auteurs: Giorgos Vasiliadis; Dusan Jakovetic; Ilias Spais; Sotiris Ioannidis
Publié dans: 7th European Conference on Service-Oriented and Cloud Computing – EU Project Space track (ESOCC 2018), Numéro 1, 2019
Éditeur: Springer
DOI: 10.5281/zenodo.3355416

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