University of Tasmania
Browse

File(s) under permanent embargo

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

journal contribution
posted on 2023-05-20, 20:55 authored by Zeng, X, Saurabh GargSaurabh Garg, Barika, M, Zomaya, AY, Wang, L, Villari, M, Chen, D, Ranjan, R
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.

History

Publication title

ACM Computing Surveys

Volume

53

Article number

46

Number

46

Pagination

1-40

ISSN

0360-0300

Department/School

School of Information and Communication Technology

Publisher

Assoc Computing Machinery

Place of publication

1515 Broadway, New York, USA, Ny, 10036

Rights statement

© 2020 Association for Computing Machinery

Repository Status

  • Restricted

Socio-economic Objectives

Computer systems