Please use this identifier to cite or link to this item:
Title: QoS-based ranking and selection of SaaS applications using heterogeneous similarity metrics
Authors: Daramola, Olawande 
Keywords: Cloud service selection, E-marketplace, QoS, SaaS, Similarity metrics
Issue Date: 2018
Publisher: Springer Link
Source: Ezenwoke, A., Daramola, O. & Adigun, M. 2018. QoS-based ranking and selection of SaaS applications using heterogeneous similarity metrics. Journal of Cloud Computing, 7(1): 1-12. []
Journal: Journal of Cloud Computing 
Abstract: The plethora of cloud application services (Apps) in the cloud business apps e-marketplace often leads to service choice overload. Meanwhile, existing SaaS e-marketplaces employ keyword-based inputs that do not consider both the quantitative and qualitative quality of service (QoS) attributes that characterise cloud-based services. Also, existing QoS-based cloud service ranking approaches rank cloud application services are based on the assumption that the services are characterised by quantitative QoS attributes alone, and have employed quantitative-based similarity metrics for ranking. However, the dimensions of cloud service QoS requirements are heterogeneous in nature, comprising both quantitative and qualitative QoS attributes, hence a cloud service ranking approach that embrace core heterogeneous QoS dimensions is essential in order to engender more objective cloud selection. In this paper, we propose the use of heterogeneous similarity metrics (HSM) that combines quantitative and qualitative dimensions for QoS-based ranking of cloud-based services. By using a synthetically generated cloud services dataset, we evaluated the ranking performance of five HSM using Kendall tau rank coefficient and precision as accuracy metrics benchmarked with one HSM. The results show significant rank order correlation of Heterogeneous Euclidean- Eskin Metric, Heterogeneous Euclidean-Overlap Metric, and Heterogeneous Value Difference Metric with human similarity judgment, compared to other metrics used in the study. Our results confirm the applicability of HSM for QoS ranking of cloud services in cloud service e-marketplace with respect to users’ heterogeneous QoS requirements.
ISSN: 2192-113X (Online)
Appears in Collections:FID - Journal Articles (not DHET subsidised)

Files in This Item:
File Description SizeFormat 
JClouds_Azu_Daramola.pdf872.24 kBAdobe PDFView/Open
Show full item record

Page view(s)

checked on Feb 9, 2021


checked on Feb 9, 2021

Google ScholarTM



Items in Digital Knowledge are protected by copyright, with all rights reserved, unless otherwise indicated.