Systematic mapping for big data stream processing frameworks

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2016

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Institute of Electrical and Electronics Engineers Inc.

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Software Engineering
(2005)
Department of Software Engineering was founded in 2005 as the first department in Ankara in Software Engineering. The recent developments in current technologies such as Artificial Intelligence, Machine Learning, Big Data, and Blockchains, have placed Software Engineering among the top professions of today, and the future. The academic and research activities in the department are pursued with qualified faculty at Undergraduate, Graduate and Doctorate Degree levels. Our University is one of the two universities offering a Doctorate-level program in this field. In addition to focusing on the basic phases of software (analysis, design, development, testing) and relevant methodologies in detail, our department offers education in various areas of expertise, such as Object-oriented Analysis and Design, Human-Computer Interaction, Software Quality Assurance, Software Requirement Engineering, Software Design and Architecture, Software Project Management, Software Testing and Model-Driven Software Development. The curriculum of our Department is catered to graduate individuals who are prepared to take part in any phase of software development of large-scale software in line with the requirements of the software sector. Department of Software Engineering is accredited by MÜDEK (Association for Evaluation and Accreditation of Engineering Programs) until September 30th, 2021, and has been granted the EUR-ACE label that is valid in Europe. This label provides our graduates with a vital head-start to be admitted to graduate-level programs, and into working environments in European Union countries. The Big Data and Cloud Computing Laboratory, as well as MobiLab where mobile applications are developed, SimLAB, the simulation laboratory for Medical Computing, and software education laboratories of the department are equipped with various software tools and hardware to enable our students to use state-of-the-art software technologies. Our graduates are employed in software and R&D companies (Technoparks), national/international institutions developing or utilizing software technologies (such as banks, healthcare institutions, the Information Technologies departments of private and public institutions, telecommunication companies, TÜİK, SPK, BDDK, EPDK, RK, or universities), and research institutions such TÜBİTAK.
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Computer Engineering
(1998)
The Atılım University Department of Computer Engineering was founded in 1998. The department curriculum is prepared in a way that meets the demands for knowledge and skills after graduation, and is subject to periodical reviews and updates in line with international standards. Our Department offers education in many fields of expertise, such as software development, hardware systems, data structures, computer networks, artificial intelligence, machine learning, image processing, natural language processing, object based design, information security, and cloud computing. The education offered by our department is based on practical approaches, with modern laboratories, projects and internship programs. The undergraduate program at our department was accredited in 2014 by the Association of Evaluation and Accreditation of Engineering Programs (MÜDEK) and was granted the label EUR-ACE, valid through Europe. In addition to the undergraduate program, our department offers thesis or non-thesis graduate degree programs (MS).

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Abstract

There has been lots of discussions about the choice of a stream processing framework (SPF) for Big Data. Each of the SPFs has different cutting edge technologies in their steps of processing the data in motion that gives them a better advantage over the others. Even though, the cutting edge technologies used in each stream processing framework might better them, it is still hard to say which framework bests the rest under different scenarios and conditions. In this study, we aim to show trends and differences about several SPFs for Big Data by using the Systematic Mapping (SM) approach. To achieve our objectives, we raise 6 research questions (RQs), in which 91 studies that conducted between 2010 and 2015 were evaluated. We present the trends by classifying the research on SPFs with respect to the proposed RQs which can help researchers to obtain an overview of the field. © 2016 IEEE.

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Keywords

Big Data, Flink, InfoSphere, S4, Spark, Storm, Streaming

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2

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Source

2016 11th International Conference on Digital Information Management, ICDIM 2016 -- 2016 11th International Conference on Digital Information Management, ICDIM 2016 -- 19 September 2016 through 21 September 2016 -- Porto -- 126084

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Issue

Start Page

31

End Page

36

URI

https://doi.org/10.1109/ICDIM.2016.7829760
 https://hdl.handle.net/20.500.14411/3793

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Scopus