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SLA management for big data analytical applications in clouds: a taxonomy study

Citation

Zeng, X and Garg, S and Barika, M and Zomaya, AY and Wang, L and Villari, M and Chen, D and Ranjan, R, SLA management for big data analytical applications in clouds: a taxonomy study, ACM Computing Surveys, 53, (3) Article 46. ISSN 0360-0300 (2020) [Refereed Article]

Copyright Statement

2020 Association for Computing Machinery

DOI: doi:10.1145/3383464

Abstract

Recent years have witnessed the booming of big data analytical applications (BDAAs). This trend provides unrivaled opportunities to reveal the latent patterns and correlations embedded in the data, and thus productive decisions may be made. This was previously a grand challenge due to the notoriously high dimensionality and scale of big data, whereas the quality of service offered by providers is the first priority. As BDAAs are routinely deployed on Clouds with great complexities and uncertainties, it is a critical task to manage the service level agreements (SLAs) so that a high quality of service can then be guaranteed. This study performs a systematic literature review of the state of the art of SLA-specific management for Cloud-hosted BDAAs. The review surveys the challenges and contemporary approaches along this direction centering on SLA. A research taxonomy is proposed to formulate the results of the systematic literature review. A new conceptual SLA model is defined and a multi-dimensional categorization scheme is proposed on its basis to apply the SLA metrics for an in-depth understanding of managing SLAs and the motivation of trends for future research.

Item Details

Item Type:Refereed Article
Keywords:general and reference, surveys and overviews, information systems, data analytics, online analytical processing, computer systems organization, cloud computing, big data, analytics application, service level agreement, service layer, SLA metrics, SLA
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Cloud computing
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Computer systems
UTAS Author:Garg, S (Dr Saurabh Garg)
UTAS Author:Barika, M (Mr Mutaz Barika)
ID Code:142782
Year Published:2020
Web of Science® Times Cited:1
Deposited By:Information and Communication Technology
Deposited On:2021-02-11
Last Modified:2021-04-28
Downloads:0

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