Presentation 2011-11-24
An OVM-based Variation Model for Multitenant SaaS and Its Evaluation
Mikio Aoyama, Takashi Katsu, Nozomi Kurono,
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Abstract(in English) SaaS (Software as a Service), a top layer of Cloud computing, provides diverse applications with low cost and high reliability and maintainability. To meet such requirements, many SaaSes introduce single-instance/multi-tenant model. Metadata-drive architecture is a key to realize the different requirements across multi-tenants where metadata defines the different requirements to each tenant while keeping source code and its instance single. However, ever increasing requirements to SaaS makes it complicated to metadata and the development SaaS with metadata. This article proposes an OVM (Orthogonal Variability Model) for representing variability of multitenant applications of SaaS, and a method to generate the OVM from metadata API based on MVC concept. Application to salesforce.com reveals the effectiveness of the proposed model and method.
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Keyword(in English) Cloud Computing / SaaS / Metadata / Metadata-Driven Architecture / OVM / Variability / Product-Line
Paper # AI2011-29
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Conference Information
Committee AI
Conference Date 2011/11/17(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) An OVM-based Variation Model for Multitenant SaaS and Its Evaluation
Sub Title (in English)
Keyword(1) Cloud Computing
Keyword(2) SaaS
Keyword(3) Metadata
Keyword(4) Metadata-Driven Architecture
Keyword(5) OVM
Keyword(6) Variability
Keyword(7) Product-Line
1st Author's Name Mikio Aoyama
1st Author's Affiliation Department of Software Engineering, Nanzan University()
2nd Author's Name Takashi Katsu
2nd Author's Affiliation Graduate School of Mathematical Sciences and Infomation Engineering, Nanzan University
3rd Author's Name Nozomi Kurono
3rd Author's Affiliation Department of Software Engineering, Nanzan University
Date 2011-11-24
Paper # AI2011-29
Volume (vol) vol.111
Number (no) 316
Page pp.pp.-
#Pages 6
Date of Issue