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A model for optimising the deployment of cloud-hosted application components for guaranteeing multitenancy isolation.

Ochei, Laud Charles; Ejiofor, Christopher Ifeanyichukwu

Authors

Laud Charles Ochei

Christopher Ifeanyichukwu Ejiofor



Abstract

Tenants associated with a cloud-hosted application seek to reduce running costs and minimize resource consumption by sharing components and resources. However, despite the benefits, sharing resources can affect tenant’s access and overall performance if one tenant abruptly experiences a significant workload, particularly if the application fails to accommodate this sudden increase in workload. In cases where a there is a higher or varying degree of isolation between components, this issue can become severe. This paper aims to present novel solutions for deploying components of a cloud-hosted application with the purpose of guaranteeing the required degree of multitenancy isolation through a mathematical optimization model and metaheuristic algorithm. Research conducted through this paper demonstrates that, when compared, optimal solutions achieved through the model had low variability levels and percent deviation. This paper additionally provides areas of application of our optimization model as well as challenges and recommendations for deploying components associated with varying degrees of isolation.

Journal Article Type Article
Publication Date Apr 30, 2018
Journal Advances in Science, Technology and Engineering Systems Journal
Print ISSN 2415-6698
Peer Reviewed Peer Reviewed
Volume 3
Issue 2
Pages 174-183
Institution Citation OCHEI, L.C. and EJIOFOR, C.I. 2018. A model for optimising the deployment of cloud-hosted application components for guaranteeing multitenancy isolation. Advances in science, technology and engineering systems journal [online], 3(2), pages 174-183. Available from: https://doi.org/10.25046/aj030220
DOI https://doi.org/10.25046/aj030220
Keywords Cloud-hosted application; Multitenancy; Degree of isolation; Simulated annealing; Metaheuristic; Optimization model; Component; Cloud deployment

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