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Virtual Network Embedding: Reducing the Search Space by Model Transformation Techniques

Tomaszek, Stefan and Leblebici, Erhan and Wang, Lin and Schürr, Andy (2018):
Virtual Network Embedding: Reducing the Search Space by Model Transformation Techniques.
Springer, In: Proceedings of the 11th International Conference on Theory and Practice of Model Transformation (ICMT'18), In: Lecture Notes in Computer Science, 10888, DOI: 10.1007/978-3-319-93317-7_2,
[Online-Edition: https://doi.org/10.1007/978-3-319-93317-7_2],
[Conference or Workshop Item]

Item Type: Conference or Workshop Item
Erschienen: 2018
Creators: Tomaszek, Stefan and Leblebici, Erhan and Wang, Lin and Schürr, Andy
Title: Virtual Network Embedding: Reducing the Search Space by Model Transformation Techniques
Language: English
Series Name: Lecture Notes in Computer Science
Volume: 10888
Publisher: Springer
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering > Real-Time Systems
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering
DFG-Collaborative Research Centres (incl. Transregio)
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > A: Construction Methodology
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > A: Construction Methodology > Subproject A1: Modelling
Event Title: Proceedings of the 11th International Conference on Theory and Practice of Model Transformation (ICMT'18)
Date Deposited: 02 Jul 2018 07:32
DOI: 10.1007/978-3-319-93317-7_2
Official URL: https://doi.org/10.1007/978-3-319-93317-7_2
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