TY - GEN
T1 - Searching for optimal configurations within large-scale models
T2 - 35th International Conference on Conceptual Modelling, ER 2016 held in conjunction with Workshops on AHA, MoBiD, MORE-BI, MReBA, QMMQ, SCME and WM2SP, 2016
AU - Ochoa, L.
AU - González-Rojas, O.
AU - Verano, M.
AU - Castro, H.
PY - 2016
Y1 - 2016
N2 - © Springer International Publishing AG 2016.Feature modeling is a widely accepted variability modeling technique for supporting decision-making scenarios, by representing decisions as features. However, there are scenarios where domain concepts have multiple implementation alternatives that have to be analyzed from large-scale data sources. Therefore, a manual selection of an optimal solution from within the alternatives space or even the complete representation of the domain is an unsuitable task. To solve this issue, we created a feature modeling metamodel and two specific processes to represent domain and implementation alternative models, and to search for optimal solutions whilst considering a set of optimization objectives. We applied this approach to a cloud computing case study and obtained an optimal provider configuration for deploying a JEE application.
AB - © Springer International Publishing AG 2016.Feature modeling is a widely accepted variability modeling technique for supporting decision-making scenarios, by representing decisions as features. However, there are scenarios where domain concepts have multiple implementation alternatives that have to be analyzed from large-scale data sources. Therefore, a manual selection of an optimal solution from within the alternatives space or even the complete representation of the domain is an unsuitable task. To solve this issue, we created a feature modeling metamodel and two specific processes to represent domain and implementation alternative models, and to search for optimal solutions whilst considering a set of optimization objectives. We applied this approach to a cloud computing case study and obtained an optimal provider configuration for deploying a JEE application.
UR - https://www.scopus.com/pages/publications/84995967785
UR - https://www.scopus.com/pages/publications/84995967785#tab=citedBy
U2 - 10.1007/978-3-319-47717-6_6
DO - 10.1007/978-3-319-47717-6_6
M3 - Conference contribution
SN - 9783319477169
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 65
EP - 75
BT - Advances in Conceptual Modeling - ER 2016 Workshops, AHA, MoBiD, MORE-BI, MReBA, QMMQ, SCME, and WM2SP, Proceedings
A2 - Link, S.
A2 - Trujillo, J.C.
PB - Springer Verlag
Y2 - 14 November 2016 through 17 November 2016
ER -