Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/28857
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: Towards workload-aware cloud resource provisioning using a multi-controller fuzzy switching approach
Author(s): Ullah, Amjad
Li, Jingpeng
Hussain, Amir
Keywords: cloud elasticity
control theory
multi-controller
fuzzy logic
auto-scaling
dynamic resource provisioning
feedback controllers
multi-model
elasticity rules
Issue Date: 31-Dec-2018
Date Deposited: 26-Feb-2019
Citation: Ullah A, Li J & Hussain A (2018) Towards workload-aware cloud resource provisioning using a multi-controller fuzzy switching approach. International Journal of High Performance Computing and Networking, 12 (1), pp. 13-25. https://doi.org/10.1504/IJHPCN.2018.093838
Abstract: Elasticity enables cloud customers to enrich their applications to dynamically adjust underlying cloud resources. Over the past, a plethora of techniques have been introduced to implement elasticity. Control theory is one such technique that offers a systematic method to design feedback controllers to perform elasticity. Many of the available such approaches utilise the single system model. However, for cloud applications that are subject to time varying workload conditions (e.g., e-commerce applications), it becomes difficult for such approaches to perform effectively at all times to achieve the desired performance goals. This paper exploits the novel use of a recently developed multi-controller based approach, where each controller is designed specifically for different operating conditions. Moreover, the use of fuzzy logic is exploited for the selection of a suitable controller at runtime. Initial results in comparison with the conventional feedback control approach demonstrate better achievement of the performance goals.
DOI Link: 10.1504/IJHPCN.2018.093838
Rights: This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Publisher policy allows this work to be made available in this repository. Published in International Journal of High Performance Computing and Networking, 2018 Vol.12 No.1 by Inderscience. The original publication is available at: https://doi.org/10.1504/IJHPCN.2018.093838

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