article

Adaptation in cloud resource configuration: a survey

Authors:

Abdul R. Hummaida,

Norman W. Paton,

Rizos SakellariouAuthors Info & Claims

Journal of Cloud Computing: Advances, Systems and Applications, Volume 5, Issue 1

Article No.: 57, Pages 1 - 16

https://doi.org/10.1186/s13677-016-0057-9

Published: 01 December 2016 Publication History

Abstract

With increased demand for computing resources at a lower cost by end-users, cloud infrastructure providers need to find ways to protect their revenue. To achieve this, infrastructure providers aim to increase revenue and lower operational costs. A promising approach to addressing these challenges is to modify the assignment of resources to workloads. This can be used, for example, to consolidate existing workloads; the new capability can be used to serve new requests or alternatively unused resources may be turned off to reduce power consumption. The goal of this paper is to highlight features, approaches and findings in the literature, in order to identify open challenges and facilitate future developments. We present a definition of cloud systems adaptation, a classification of the key features and a survey of adapting compute and storage configuration. Based on our analysis, we identify three open research challenges: characterising the workload type, accurate online profiling of workloads, and building highly scalable adaptation mechanisms.

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cover image Journal of Cloud Computing: Advances, Systems and Applications

Journal of Cloud Computing: Advances, Systems and Applications Volume 5, Issue 1

December 2016

283 pages

ISSN:2192-113X

EISSN:2192-113X

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Copyright © Copyright © 2016 The Author(s).

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Hindawi Limited

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Published: 01 December 2016

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https://dl.acm.org/doi/10.1007/978-981-99-7339-2_26
Wang ZZhu SLi JJiang WRamakrishnan KZheng YYan MZhang XLiu AGavrilovska AAltınbüken DBinnig C(2022)DeepScalingProceedings of the 13th Symposium on Cloud Computing10.1145/3542929.3563469(16-30)Online publication date: 7-Nov-2022
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https://dl.acm.org/doi/10.1007/s10723-022-09603-4
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