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On the Integration of AI/ML-based scaling operations in the 5Growth platform

J. Baranda, J. Mangues-Bafalluy, Engin Zeydan, L. Vettori, R. Martinez, Xi Li, A. Garcia-Saavedra, C.F. Chiasserini, C. Casetti, K. Tomakh, O. Kolodiazhnyi, C. J. Bernardos
2020 2020 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN)  
data gathering and model execution.  ...  The automated assurance of vertical service level agreements (SLA) is a challenge in 5G networks.  ...  For this work, we created an offline training application that generates a random forest classifier model (via the .fit() function of Spark API).  ... 
doi:10.1109/nfv-sdn50289.2020.9289863 fatcat:iwmrth32nre4re3hu52ac5zdh4

Building Near-Real-Time Processing Pipelines with the Spark-MPI Platform [article]

Nikolay Malitsky, Aashish Chaudhary, Sebastien Jourdain, Matt Cowan, Patrick O'Leary, Marcus Hanwell, Kerstin Kleese Van Dam
2018 arXiv   pre-print
Recently, this demand was addressed by the Spark-MPI approach connecting the Spark data-intensive platform with the MPI high-performance framework.  ...  Spark-MPI further extended the Spark ecosystem with the MPI applications using the Process Management Interface.  ...  The direct deployment of the SHARP program on the Spark Streaming platform however was prevented by Spark computational model constrains.  ... 
arXiv:1805.04886v1 fatcat:3tdybjzdt5bordjpvwjvqpj5fa

Big Data Techniques, Systems, Applications, and Platforms: Case Studies from Academia

Atanas Radenski, Todor Gurov, Kalinka Kaloyanova, Nikolay Kirov, Maria Nisheva, Peter Stanchev, Eugenia Stoimenova
2016 Proceedings of the 2016 Federated Conference on Computer Science and Information Systems  
Big data is a broad term with numerous dimensions, most notably: big data characteristics, techniques, software systems, application domains, computing platforms, and big data milieu (industry, government  ...  In this paper we briefly introduce fundamental big data characteristics and then present seven case studies of big data techniques, systems, applications, and platforms, as seen from academic perspective  ...  in Spark for performance gains.  ... 
doi:10.15439/2016f91 dblp:conf/fedcsis/RadenskiGKKNSS16 fatcat:22ekovjsajd5hhilzczvzoay7m

A Review on Latest Technologies in Big Data Analysis

Castro S, Pushpalakshmi R
2018 International Journal of Engineering & Technology  
Thus, the recent researches have focused on the analysis of big data.  ...  Thus, this study presents a platform to investigate big data at various levels.  ...  Strom and Splunk are the few models of largescale data streaming platforms.  ... 
doi:10.14419/ijet.v7i3.1.16806 fatcat:fvxtqfgysrhtbiakgnvowceyhm

An IoT based Machine Learning Technique for Efficient Online Load Forecasting

B. Madhuravani, Srujan Atluri, Hema Valpadasu
2021 Revista GEINTEC  
The architecture and a new approach to the combination of the key classifiers intended for IoT network attacks are being developed.  ...  To improve the preparation and assessment pace, it is suggested to use the data processing and multi-threaded mode offered by Spark.  ...  Next phase needs parallel aggregation and data gathering on such nodes. Spark is a computational platform for resilient and concurrent distributed data sets (RDDs).  ... 
doi:10.47059/revistageintec.v11i2.1686 fatcat:fsibs3gs75bclny5w5g6erhqea

Climbing the Software Assurance Ladder - Practical Formal Verification for Reliable Software

Yannick Moy
2019 Electronic Communications of the EASST  
Experience of both long-term and new users helped us define adoption and usage guidelines for SPARK based on five levels of increasing assurance that map well with industrial needs in practice.  ...  Formal verification with SPARK has been used for years to get as close as possible to zero-defect software.  ...  We would like to thank the anonymous referees for their useful remarks, as well as our colleagues at AdaCore, Altran and Thales for their reviews on earlier drafts of this article. Bibliography  ... 
doi:10.14279/tuj.eceasst.76.1069 dblp:journals/eceasst/Moy18 fatcat:sz6t37y4nfg37dylrkrnv22z34

A mini-review of machine learning in big data analytics: Applications, challenges, and prospects

Isaac Kofi Nti, Juanita Ahia Quarcoo, Justice Aning, Godfred Kusi Fosu
2022 Big Data Mining and Analytics  
However, the high number of free BDA tools, platforms, and data mining tools makes it challenging to select the appropriate one for the right task.  ...  The related applications fields, challenges, and most importantly the openings for future research, are detailed.  ...  Thus, leading to several challenges in putting up high-performance models for DB frameworks.  ... 
doi:10.26599/bdma.2021.9020028 dblp:journals/bigdatama/NtiQAF22 fatcat:pktq32nmevhlrofkvmlctc7zwu

Evaluation and Analysis of Distributed Graph-Parallel Processing Frameworks

Yue Zhao, Kenji Yoshigoe, Mengjun Xie, Suijian Zhou, Remzi Seker, Jiang Bian
2014 Journal of Cyber Security and Mobility  
We applied basic performance metrics measuring speed, resource utilization, and scalability to answer a basic question of which graph-parallel processing platform is better suited for what applications  ...  Further, out of the evaluated graphparallel computing platforms, PowerGraph consistently exhibits better performance than others.  ...  One of the reasons for the high CPU load is that the ingress time for Spark is much shorter than those for other platforms.  ... 
doi:10.13052/jcsm2245-1439.333 fatcat:r2xiozmuvvaz7o2gpbfqhu4mye

Big Data solutions in cloud environment

Maciej Pondel, Jolanta Pondel
2016 Position Papers of the 2016 Federated Conference on Computer Science and Information Systems  
Current business faces new challenges that require modern and adjusted IT models.  ...  Figure 2 presents IaaS Quadrant.  Platform as a Service (PaaS) is a cloud computing model that delivers applications over the Internet.  ...  Spark provides a simple and expressive programming model that supports a wide range of applications, including ETL, machine learning, stream processing, and graph computation. IV.  ... 
doi:10.15439/2016f584 dblp:conf/fedcsis/PondelP16 fatcat:fsfh3qa7jfantizfwpkmwn5saq

PerTract: Model Extraction and Specification of Big Data Systems for Performance Prediction by the Example of Apache Spark and Hadoop

Johannes Kroß, Helmut Krcmar
2019 Big Data and Cognitive Computing  
By adapting DSL instances, our approach enables engineers to predict the performance of applications for different scenarios such as changing data input and resources.  ...  First, a system-and tool-agnostic domain-specific language (DSL) allows the modeling of performance-relevant factors of big data applications, computing resources, and data workload.  ...  The framework applies multiple benchmarks on source platforms and a regression-based model to relate the performance of source and the target platforms. Zhang et al.  ... 
doi:10.3390/bdcc3030047 fatcat:dnbi74dnqbfd3ci6djrbhxmgje

Interactive Big Data Analytics Platform for Healthcare and Clinical Services

Dillon Chrimes
2018 Global Journal of Engineering Sciences  
The next step of the testing of the BDA platform will be to distribute and index the data to ten billion patient data rows across the database nodes, and then test the performance using the established  ...  The design of the implemented BDA platform (utilizing WestGrid's supercomputing clusters) is available to researchers and sponsored members.  ...  Jupyter on Spark offered high performance stacks not only over our platform but also in unison to run all queries simultaneously for a variety of reporting for providers and health professionals.  ... 
doi:10.33552/gjes.2018.01.000502 fatcat:biiz2qnx4vckrcrmv4gcn5ydru

Special Issue on Big Data and Digital Transformation

José Luís Pereira, Orlando Belo, Pascal Ravesteijn
2018 Journal of Grid Computing  
In this article, using the Apache Spark (a widely known platform for carrying out distributed operations on Big Data), a Spark-Based Mining Framework (SBMF) is proposed to classify imbalanced Big Data.  ...  The results shown significant performance improvements. In the fifth article, "A Dynamic Spark-Based Classification Framework for Imbalanced Big Data", authors Nahla B.  ... 
doi:10.1007/s10723-018-9469-8 fatcat:27xdzc2uinbr3g54gqnzcjnc2y


Mingming Zhang, Tianyu Wo, Tao Xie, Xuelian Lin, Yaxiao Liu
2017 Proceedings of the VLDB Endowment  
Such characteristics pose challenges for developing real-time applications based on such data.  ...  Multiple services are provided based on the collected data. CarStream has been deployed and maintained for three years in industrial usage, collecting over 40 terabytes of driving data.  ...  We would like to thank UCAR Inc for the collaboration and the data that are used in this paper.  ... 
doi:10.14778/3137765.3137781 fatcat:2xwo3tgxajgefni5lik267ul2i

End-to-End Intent-Based Networking

Luis Velasco, Marco Signorelli, Oscar Gonzalez De Dios, Chrysa Papagianni, Roberto Bifulco, Juan Jose Vegas Olmos, Simon Pryor, Gino Carrozzo, Julius Schulz-Zander, Mehdi Bennis, Ricardo Martinez, Filippo Cugini (+4 others)
2021 IEEE Communications Magazine  
The IBN framework is aware of its state and context to autonomously take proactive actions for service assurance.  ...  The resulting framework supports application-level resilience and intelligence through replication and elasticity. An illustrative intelligent application use case is presented.  ...  To support foreseen B5G application scenarios, the computing platform (Fig. 3 ) needs to be deployed as a one-stop white box at edge; this is flexibly and fully interconnected to the cloud for conducting  ... 
doi:10.1109/mcom.101.2100141 fatcat:aps7zt3xanea7aztuzkgnrl7ei

Intelligent Event Broker: A Complex Event Processing System in Big Data Contexts

Carina Andrade, José Correia, Carlos Costa, Maribel Yasmina Santos
2019 Americas Conference on Information Systems  
In Big Data contexts, many batch and streaming oriented technologies have emerged to deal with the high valuable sources of events, such as Internet of Things (IoT) platforms, the Web, several types of  ...  Machine Learning (ML) have raised the need for innovative architectures capable of processing events in a streamlined, scalable, analytical, and integrated way.  ...  The specific Consumers are the ones used in Spark Applications, one for each business goal (or group of goals).  ... 
dblp:conf/amcis/AndradeC0S19 fatcat:ph5zolmf4jbbdhdt3jyh2cnlmq
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