loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Andreas Tsagkaropoulos 1 ; Nikos Papageorgiou 1 ; Dimitris Apostolou 2 ; Yiannis Verginadis 1 and Gregoris Mentzas 1

Affiliations: 1 National Technical University of Athens (NTUA), Greece ; 2 National Technical University of Athens (NTUA) and University of Piraeus, Greece

Keyword(s): Cloud Adaptivity, Fog Computing.

Abstract: Mainstream cloud technologies are challenged by real-time, big data processing requirements or emerging applications. This paper surveys recent research efforts on advancing cloud computing virtual infrastructures and real-time big data technologies in order to provide dynamically scalable and distributed architectures over federated clouds. We examine new methods for developing cloud systems operating in a real-time, big data environment that can sense the context of the application environment and can adapt the infrastructure accordingly. We describe research topics linked to the challenge of adaptivity such as situation awareness, context detection, service-level objectives, and the capability to predict extraordinary situations requiring remedying action. We also describe research directions for realising adaptivity in cloud computing and we present a conceptual framework that represents research directions and shows interrelations.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.139.235.177

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Tsagkaropoulos, A.; Papageorgiou, N.; Apostolou, D.; Verginadis, Y. and Mentzas, G. (2018). Challenges and Research Directions in Big Data-driven Cloud Adaptivity. In Proceedings of the 8th International Conference on Cloud Computing and Services Science - CLOSER; ISBN 978-989-758-295-0; ISSN 2184-5042, SciTePress, pages 190-200. DOI: 10.5220/0006761901900200

@conference{closer18,
author={Andreas Tsagkaropoulos. and Nikos Papageorgiou. and Dimitris Apostolou. and Yiannis Verginadis. and Gregoris Mentzas.},
title={Challenges and Research Directions in Big Data-driven Cloud Adaptivity},
booktitle={Proceedings of the 8th International Conference on Cloud Computing and Services Science - CLOSER},
year={2018},
pages={190-200},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006761901900200},
isbn={978-989-758-295-0},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Cloud Computing and Services Science - CLOSER
TI - Challenges and Research Directions in Big Data-driven Cloud Adaptivity
SN - 978-989-758-295-0
IS - 2184-5042
AU - Tsagkaropoulos, A.
AU - Papageorgiou, N.
AU - Apostolou, D.
AU - Verginadis, Y.
AU - Mentzas, G.
PY - 2018
SP - 190
EP - 200
DO - 10.5220/0006761901900200
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic