@inproceedings{259cd251e419422597c6392d90de7f8e,
title = "COLAP: A predictive framework for service function chain placement in a multi-cloud environment",
abstract = "Network function virtualization (NFV) over multi-cloud promises network service providers amazing flexibility in service deployment and optimizing cost. Telecommunications applications are, however, sensitive to performance indicators, especially latency, which tend to get degraded by both the virtualization and the multiple cloud requirement for widely distributed coverage. In this work we propose an efficient framework that uses the novel concept of random cloud selection combined with a support vector regression based predictive model for cost optimized latency aware placement (COLAP) of service function chains. Extensive empirical analysis has been carried out with training datasets generated using a queuing-theoretic model. The results show good generalization performance of the predictive algorithm. The proposed framework can place thousands of virtual network functions in less than a minute and has high acceptance ratio.",
keywords = "latency, machine learning, multi-cloud computing, network function virtualization, placement, service function chain, support vector regression, virtual network function",
author = "Lav Gupta and M. Samaka and Raj Jain and Aiman Erbad and Deval Bhamare and Chris Metz",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 7th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2017 ; Conference date: 09-01-2017 Through 11-01-2017",
year = "2017",
month = mar,
day = "1",
doi = "10.1109/CCWC.2017.7868377",
language = "English",
series = "2017 IEEE 7th Annual Computing and Communication Workshop and Conference, CCWC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Saha, \{Himadri Nath\} and Satyajit Chakrabarti",
booktitle = "2017 IEEE 7th Annual Computing and Communication Workshop and Conference, CCWC 2017",
address = "United States",
}