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Katerina Doka, Nikolaos Papailiou, Dimitrios Tsoumakos, Christos Mantas, Nectarios Koziris
2015 Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data - SIGMOD '15  
To this end, we demonstrate IReS, the Intelligent Resource Scheduler for complex analytics workflows executed over multi-engine environments.  ...  Big data analytics tools are steadily gaining ground at becoming indispensable to businesses worldwide.  ...  Nikolaos Papailiou has received funding from IKY fellowships of excellence for postgraduate studies in Greece -SIEMENS program.  ... 
doi:10.1145/2723372.2735377 dblp:conf/sigmod/DokaPTMK15 fatcat:5dyeik3d45esje2mbqmwravm4q

Mix 'n' match multi-engine analytics

Katerina Doka, Nikolaos Papailiou, Victor Giannakouris, Dimitrios Tsoumakos, Nectarios Koziris
2016 2016 IEEE International Conference on Big Data (Big Data)  
As a remedy, we present IReS, the Intelligent Resource Scheduler for complex analytics workflows executed over multi-engine environments.  ...  Current platforms fail to efficiently cope with the data and task heterogeneity of modern analytics workflows due to their adhesion to a single data and/or compute model.  ...  To that end, we present IReS, an open-source Intelligent Multi-Engine Resource Scheduler that integrates multiple execution engines and datastores into the optimizing, planning and execution of complex  ... 
doi:10.1109/bigdata.2016.7840605 dblp:conf/bigdataconf/DokaPGTK16 fatcat:nimpr3poqfhapgxssfoulvva6u

Video Big Data Analytics in the Cloud: Research Issues and Challenges [article]

Aftab Alam, Shah Khalid, Muhammad Numan Khan, Tariq Habib Afridi, Irfan Ullah, Young-Koo Lee
2020 arXiv   pre-print
This study proposes a service-oriented layered reference architecture for intelligent video big data analytics in the cloud.  ...  The current technology and market trends demand an efficient framework for video big data analytics.  ...  IVA on Video Big data: Big data analytics engines are the general-purpose engine and are not mainly designed for big video analytics.  ... 
arXiv:2011.02694v1 fatcat:gbshlwsli5bxtnvnbpcdzvnzca


Ionel Gog, Malte Schwarzkopf, Natacha Crooks, Matthew P. Grosvenor, Allen Clement, Steven Hand
2015 Proceedings of the Tenth European Conference on Computer Systems - EuroSys '15  
Many systems for the parallel processing of big data are available today. Yet, few users can tell by intuition which system, or combination of systems, is "best" for a given workflow.  ...  Our prototype maps workflows expressed in four highlevel query languages to seven different popular data processing systems.  ...  Intelligent system combination: Musketeer can combine different execution engines within a workflow, and doing so outperforms fixed, single system mappings for a cross-community PageRank workflow. 4 .  ... 
doi:10.1145/2741948.2741968 dblp:conf/eurosys/GogSCGCH15 fatcat:j67jem3ohzef7pwh2ymldjwehy

Cloud, Edge, and Mobile Computing for Smart Cities [chapter]

Qian Liu, Juan Gu, Jingchao Yang, Yun Li, Dexuan Sha, Mengchao Xu, Ishan Shams, Manzhu Yu, Chaowei Yang
2021 The Urban Book Series  
Edge computing allows data produced by in-situ devices to be processed and analyzed at the edge of the network, reducing the data traffic to the central repository and processing engine (data center or  ...  Mobile computing brings portability and social interactivity for citizens to report instantaneous information for better knowledge integration.  ...  of resources' scheduling, and double the resources' payload.  ... 
doi:10.1007/978-981-15-8983-6_41 fatcat:thaaxsdzzfgfzjmjos7zbsjrqq

Table of Contents

2018 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)  
Paper Title 216 Intelligent Reverse Dictionary Based On Clustering 217 A Proposed Technique For Conversion Of Unstructured Agro-Data To Semi-Structured Or Structured Data 218 Blast Using Big  ...  6 De-duplication Approach with Enhance Security for Integrity 7 Workflow Scheduling in Cloud Computing Environment with Classification Ordinal Optimization Using SVM 8 Deploying Scalable Services  ... 
doi:10.1109/iccubea.2018.8697655 fatcat:jvjgmcrh3fhxtkf4kyydawnkiq

Big Data in the construction industry: A review of present status, opportunities, and future trends

Muhammad Bilal, Lukumon O. Oyedele, Junaid Qadir, Kamran Munir, Saheed O. Ajayi, Olugbenga O. Akinade, Hakeem A. Owolabi, Hafiz A. Alaka, Maruf Pasha
2016 Advanced Engineering Informatics  
Please find attached the full manuscript for review and publication in the Advanced Engineering Informatics.  ...  The overall aim of this study is to understand state of the construction industry for the adoption Big Data technologies.  ...  BIG DATA ENGINEERING (BDE) 21 Big Data Engineering (BDE) provide infrastructure to sup- 22 port Big Data Analytics (BDA).  ... 
doi:10.1016/j.aei.2016.07.001 fatcat:pcvyy46qrzggfnsieaskihnb3q

Cloud manufacturing as a sustainable process manufacturing route

Oliver Fisher, Nicholas Watson, Laura Porcu, Darren Bacon, Martin Rigley, Rachel L. Gomes
2018 Journal of manufacturing systems  
The current focus has been on using CM for waste minimisation; however, process manufacturing offers waste as a resource (valorisation opportunities from diversifying co-products, reuse, recycle and energy  ...  Cloud manufacturing offers a solution, as it is capable of making intelligent decisions to provide the most sustainable and robust manufacturing route available.  ...  This is particularly beneficial to SMEs who may not have the resources for data analytics within the enterprise.  ... 
doi:10.1016/j.jmsy.2018.03.005 fatcat:7dwcm64nabbmforomgcsol72nq

A Survey of Machine Learning for Computer Architecture and Systems [article]

Nan Wu, Yuan Xie
2021 arXiv   pre-print
and workload (resource allocation and management, data center management, and security), compiler, and design automation.  ...  For ML-based modelling, we discuss existing studies based on their target level of system, ranging from the circuit level to the architecture/system level.  ...  Some studies pay attention to workflow management and general hardware resource assignment. SmartFlux [56] focuses on the workflow of data-intensive and continuous processing.  ... 
arXiv:2102.07952v1 fatcat:vzj776a6abesljetqobakoc3dq

A Survey on Industry 4.0 for the Oil and Gas Industry: Upstream Sector

Olakunle Elijah, Pang Ai Ling, Sharul Kamal Abdul Rahim, Tan Kim Geok, Agus Arsad, Evizal Abdul Kadir, Muslim Abdurrahman, Radzuan Junin, Augustine Agi, Mohammad Yasin Abdulfatah
2021 IEEE Access  
INDEX TERMS Artificial intelligence (AI), cyber-physical systems, digital-twin, framework, oil and gas (O&G), industry revolution 4.0 (IR 4.0), industry 4.0 (I4.0), internet of things (IoT), simulation  ...  The market volatility in the oil and gas (O&G) sector, the dwindling demand for oil due to the impact of COVID-19, and the push for alternative greener energy are driving the need for innovation and digitization  ...  In this section, the concept of big data analytics and the use of AI tools for data analysis is presented.  ... 
doi:10.1109/access.2021.3121302 fatcat:5ohmnlkrfjattcj6xdt4m2dwuq

What's the big deal about big data?

Nick Cercone, F'IEEE
2015 Big Data & Information Analytics  
These theme areas are certainly not inclusive, rather indicative of the wide variety to which Big Data now occupies decision analytics.  ...  This position paper is based on a major cooperative research and development proposal to form a Big Data Research, Analytics, and Information Network (BRAIN).  ...  The support of Canada's Natural Sciences and Engineering Research Council (NSERC) and the Ontario Centres of Excellence is gratefully 70 NICK CERCONE, F'IEEE acknowledged for their encouragement and funding  ... 
doi:10.3934/bdia.2016.1.31 fatcat:wtdsmvgvvrfbjjui3v2cc56gbm

Human Centric Digital Transformation and Operator 4.0 for the Oil and Gas Industry

Thumeera R. Wanasinghe, Trung Trinh, Trung Nguyen, Raymond G. Gosine, Lesley Anne James, Peter Warrian
2021 IEEE Access  
Newfoundland and Labrador (PRNL), Atlantic Canada Opportunities Agency (ACOA), Mitacs, University of Toronto's Munk School of Global Affairs and Public Policy, and Memorial University of Newfoundland for  ...  Digital twins analyze data using a range of big data analytics and artificial intelligence-based tools and models.  ...  User interfaces for the cloud system is the recent trend for big data analytics [214] , [215] .  ... 
doi:10.1109/access.2021.3103680 fatcat:cvrnf4tnirdznncmtgdmlmgrhu

A new data science research program: evaluation, metrology, standards, and community outreach

Bonnie J. Dorr, Craig S. Greenberg, Peter Fontana, Mark Przybocki, Marion Le Bras, Cathryn Ploehn, Oleg Aulov, Martial Michel, E. Jim Golden, Wo Chang
2016 International Journal of Data Science and Analytics  
This article examines foundational issues in data science including current challenges, basic research questions, and expected advances, as the basis for a new data science research program (DSRP) and  ...  Toward that end, each year the DSE will consist of multiple research tracks and will This article extends a paper that was presented at IEEE Data Science and Advanced Analytics conference in the fall of  ...  on Big Data Analytics, IEEE's International Conference on Cloud and Big Data Computing, and International Conference on Data Science and Advanced Analytics.  ... 
doi:10.1007/s41060-016-0016-z dblp:journals/ijdsa/DorrGFPBPAMGC16 fatcat:ngrq7wupyfbs5ozna4sgthcjma

NIST-Big DATA Framework-1 [article]

Yiwei Zhu, San Zhang
2020 Zenodo  
This is the first chapter of the NIST-Big DATA Framework  ...  The NBD-PWG has adopted the following definition 533 of Big Data engineering. 534 Big Data engineering is the discipline for engineering scalable systems for data-535 intensive processing. 536 Big Data  ...  , and analysis. 205 Big Data engineering is the discipline for engineering scalable systems for data-intensive processing. 206 The Big Data Paradigm consists of the distribution of data systems across  ... 
doi:10.5281/zenodo.4007657 fatcat:u7rl3naanvdmrl5bceikhyy4mm

D1.1 - State of the Art Analysis

Danilo Ardagna
2021 Zenodo  
), providing resource efficiency, performance, data privacy, and security guarantees.  ...  , partition and operate Artificial Intelligence (AI) applications among the current plethora of cloud-based solutions and AI-based sensor devices (i.e., devices with intelligence and data processing capabilities  ...  the development of intelligent apps • Azure Synapse Analytics, a service made for Big Data analysis • Azure Machine Learning, end-to-end scalable platform with experimentation and model management • Azure  ... 
doi:10.5281/zenodo.6372377 fatcat:f6ldfuwivbcltew4smiiwphfty
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