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Pattern‐based multi‐cloud architecture migration
Author(s) -
Jamshidi Pooyan,
Pahl Claus,
Mendonça Nabor C.
Publication year - 2017
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.2442
Subject(s) - cloud computing , computer science , architecture , process migration , process (computing) , selection (genetic algorithm) , reference architecture , task (project management) , distributed computing , software architecture , software , artificial intelligence , geography , engineering , systems engineering , operating system , archaeology
Summary Many organizations migrate on‐premise software applications to the cloud. However, current coarse‐grained cloud migration solutions have made such migrations a non transparent task, an endeavor based on trial‐and‐error. This paper presents Variability‐based, Pattern‐driven Architecture Migration ( V ‐ P A M ), a migration method based on (i) a catalogue of fine‐grained service‐based cloud architecture migration patterns that target multi‐cloud, (ii) a situational migration process framework to guide pattern selection and composition, and (iii) a variability model to structure system migration into a coherent framework. The proposed migration patterns are based on empirical evidence from several migration projects, best practice for cloud architectures and a systematic literature review of existing research. Variability‐based, Pattern‐driven Architecture Migration allows an organization to (i) select appropriate migration patterns, (ii) compose them to define a migration plan, and (iii) extend them based on the identification of new patterns in new contexts. The patterns are at the core of our solution, embedded into a process model, with their selection governed by a variability model. Copyright © 2016 John Wiley & Sons, Ltd.