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Challenges in high performance big data frameworks

Papadopoulos, Alessandro Vittorio LU and Maggio, Martina LU (2018) 16th International Conference on High Performance Computing and Simulation, HPCS 2018 p.153-156
Abstract

Nowadays, we live in a society with billions of devices that are interconnected and interact together to improve the quality of our lives. The management and processing of information and knowledge have by now become our main resources, and the fundamental factors of economic and social development, and it is achieved through Big Data Frameworks (BDFs). The amount of such data is becoming larger every day, and this calls for scalable and reliable BDFs, that can process such data also with real-Time requirements. For example, the data collected by an autonomous car should be processed, combined, and interpreted as fast as possible in order to guarantee a safe interaction with the surrounding environment, and of the passengers. This paper... (More)

Nowadays, we live in a society with billions of devices that are interconnected and interact together to improve the quality of our lives. The management and processing of information and knowledge have by now become our main resources, and the fundamental factors of economic and social development, and it is achieved through Big Data Frameworks (BDFs). The amount of such data is becoming larger every day, and this calls for scalable and reliable BDFs, that can process such data also with real-Time requirements. For example, the data collected by an autonomous car should be processed, combined, and interpreted as fast as possible in order to guarantee a safe interaction with the surrounding environment, and of the passengers. This paper analyses the main limitations of current BDFs while providing some key challenges for increasing their flexibility. In particular, we focus on performance aspects, envisioning adaptation as a viable way to automate and improve performance in Big Data Applications.

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Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Autonomic computing, Big data, Self-Adaptive systems
host publication
Proceedings - 2018 International Conference on High Performance Computing and Simulation, HPCS 2018
editor
Zine-Dine, Khalid and Smari, Waleed W.
article number
8514344
pages
4 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
16th International Conference on High Performance Computing and Simulation, HPCS 2018
conference location
Orleans, France
conference dates
2018-07-16 - 2018-07-20
external identifiers
  • scopus:85057371047
ISBN
9781538678787
DOI
10.1109/HPCS.2018.00039
language
English
LU publication?
yes
id
312a88d4-e764-4caf-b8d0-3eb5729560fb
date added to LUP
2018-12-10 10:03:48
date last changed
2022-05-03 08:35:28
@inproceedings{312a88d4-e764-4caf-b8d0-3eb5729560fb,
  abstract     = {{<p>Nowadays, we live in a society with billions of devices that are interconnected and interact together to improve the quality of our lives. The management and processing of information and knowledge have by now become our main resources, and the fundamental factors of economic and social development, and it is achieved through Big Data Frameworks (BDFs). The amount of such data is becoming larger every day, and this calls for scalable and reliable BDFs, that can process such data also with real-Time requirements. For example, the data collected by an autonomous car should be processed, combined, and interpreted as fast as possible in order to guarantee a safe interaction with the surrounding environment, and of the passengers. This paper analyses the main limitations of current BDFs while providing some key challenges for increasing their flexibility. In particular, we focus on performance aspects, envisioning adaptation as a viable way to automate and improve performance in Big Data Applications.</p>}},
  author       = {{Papadopoulos, Alessandro Vittorio and Maggio, Martina}},
  booktitle    = {{Proceedings - 2018 International Conference on High Performance Computing and Simulation, HPCS 2018}},
  editor       = {{Zine-Dine, Khalid and Smari, Waleed W.}},
  isbn         = {{9781538678787}},
  keywords     = {{Autonomic computing; Big data; Self-Adaptive systems}},
  language     = {{eng}},
  pages        = {{153--156}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Challenges in high performance big data frameworks}},
  url          = {{http://dx.doi.org/10.1109/HPCS.2018.00039}},
  doi          = {{10.1109/HPCS.2018.00039}},
  year         = {{2018}},
}