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Surrogate-Assisted Online Optimisation of Cloud IaaS Configurations

Research output: Chapter in Book/Report/Conference proceedingConference paper

Original languageEnglish
Title of host publicationCloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on
PublisherInstitute of Electrical and Electronics Engineers ( IEEE )
Number of pages8
ISBN (Print)9781479940943
Publication statusPublished - 2014
Event2014 IEEE 6th International Conference on Cloud Computing Technology and Science (CloudCom 2014) - , Singapore
Duration: 15 Dec 201418 Dec 2014


Conference2014 IEEE 6th International Conference on Cloud Computing Technology and Science (CloudCom 2014)

King's Authors


Elasticity refers to the auto-scaling ability of clouds towards optimally matching their resources to actual demand conditions. An important problem facing the infrastructure and service providers is how to optimise their resource configurations online, to elastically serve time-varying demands. Most scaling methodologies provide resource reconfiguration decisions to maintain quality properties under environment changes. However, issues related to the timeliness of such reconfiguration decisions are often neglected. In this paper, we present a methodology for online optimisation of cloud configurations. We first employ a search-based approach to extract near-optimal configurations considering conflicting performance and business quality attributes. Towards reducing the burden of time-consuming evaluations of configurations' quality, we develop surrogate models to predict their quality based on history observations. Finally, we evaluate our technique using Cloud Sim-based cloud simulation. Our experimental results show that the use of surrogates can produce high quality configurations with lead time of seconds and prediction error within 6%.

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