Efficient QoS-Aware Service Recommendation for Multi-Tenant Service-Based Systems in Cloud

Publication Type:
Journal Article
IEEE Transactions on Services Computing, 2020, 13, (6), pp. 1045-1058
Issue Date:
Filename Description Size
08063936.pdfPublished version1.25 MB
Adobe PDF
Full metadata record
© 2008-2012 IEEE. The popularity of cloud computing has fueled the growth in multi-Tenant service-based systems (SBSs) that are composed of selected cloud services. In the cloud environment, a multi-Tenant SBS simultaneously serves multiple tenants that usually have differentiated QoS requirements. This unique characteristic further complicates the problems of QoS-Aware service selection at build-Time and system adaptation at runtime, and renders conventional approaches obsolete and inefficient. In the dynamic and volatile cloud environment, the efficiency of building and adapting a multi-Tenant SBS is of paramount importance. In this paper, we present two service recommendation approaches for multi-Tenant SBSs, one for build-Time and one for runtime, based on K-Means clustering and Locality-Sensitive Hashing (LSH) techniques respectively, aiming at finding appropriate services efficiently. Extensive experimental results demonstrate that our approaches can facilitate fast multi-Tenant SBS construction and rapid system adaptation.
Please use this identifier to cite or link to this item: