Title: Towards workload-aware cloud resource provisioning using a multi-controller fuzzy switching approach

Authors: Amjad Ullah; Jingpeng Li; Amir Hussain

Addresses: Division of Computer Science and Mathematics, University of Stirling, Stirling, UK ' Division of Computer Science and Mathematics, University of Stirling, Stirling, UK ' Division of Computer Science and Mathematics, University of Stirling, Stirling, UK

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.

Keywords: cloud elasticity; control theory; multi-controller; fuzzy logic; auto-scaling; dynamic resource provisioning; feedback controllers; multi-model; elasticity rules.

DOI: 10.1504/IJHPCN.2018.093838

International Journal of High Performance Computing and Networking, 2018 Vol.12 No.1, pp.13 - 25

Available online: 27 Jul 2018 *

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