2020
Rafael de Jesus Martins, Cristiano Bonato Both, Juliano Araujo Wickboldt, Lisandro Zambenedetti Granville
Virtual Network Functions Migration Cost: from Identification to Prediction Journal Article
In: Elsevier Computer Networks, 181 , pp. 107429, 2020, ISSN: 1389-1286.
Abstract Links BibTeX Tags: Container Management & Orchestration Network Orchestration Network Virtualization & Slicing
@article{journal/cn/Martins20,
title = {Virtual Network Functions Migration Cost: from Identification to Prediction},
author = {Rafael de Jesus Martins and Cristiano Bonato Both and Juliano Araujo Wickboldt and Lisandro Zambenedetti Granville},
url = {http://www.sciencedirect.com/science/article/pii/S138912862031118X},
doi = {10.1016/j.comnet.2020.107429},
issn = {1389-1286},
year = {2020},
date = {2020-11-09},
urldate = {2020-11-09},
journal = {Elsevier Computer Networks},
volume = {181},
pages = {107429},
abstract = {The advent of the function virtualization concept, especially that of network functions, leads to important benefits for future networks. Although the orchestration of virtualized functions presents gains for network operators and clients alike, the overhead for moving functions has not been thoroughly explored so far, especially considering functions virtualized by using container technologies. In this work, we investigate orchestration costs associated with the migration of containerized virtual functions. To this end, we first perform a systematic literature review on state-of-the-art virtual function migration costs, electing time and data transferred as so. We then use a well-known container platform (LXD) to perform several orchestration experiments in a controlled environment. By analyzing the container migration process in smaller complementary steps, and designing experiments to evaluate them individually, a pattern for migration costs is observed. Linear regression is then used to derive a prediction model for the necessary time and data transferring for performing a container migration. To assess the predictor’s accuracy, we present a cloud computing use case where the predictor is deployed. Results indicate that predictions can be accurate within reasonable range, and therefore orchestration algorithms may be improved by accounting for similar prediction models when determining the migration of one or more virtualized functions.},
keywords = {Container Management & Orchestration, Network Orchestration, Network Virtualization & Slicing},
pubstate = {published},
tppubtype = {article}
}
The advent of the function virtualization concept, especially that of network functions, leads to important benefits for future networks. Although the orchestration of virtualized functions presents gains for network operators and clients alike, the overhead for moving functions has not been thoroughly explored so far, especially considering functions virtualized by using container technologies. In this work, we investigate orchestration costs associated with the migration of containerized virtual functions. To this end, we first perform a systematic literature review on state-of-the-art virtual function migration costs, electing time and data transferred as so. We then use a well-known container platform (LXD) to perform several orchestration experiments in a controlled environment. By analyzing the container migration process in smaller complementary steps, and designing experiments to evaluate them individually, a pattern for migration costs is observed. Linear regression is then used to derive a prediction model for the necessary time and data transferring for performing a container migration. To assess the predictor’s accuracy, we present a cloud computing use case where the predictor is deployed. Results indicate that predictions can be accurate within reasonable range, and therefore orchestration algorithms may be improved by accounting for similar prediction models when determining the migration of one or more virtualized functions.
Henrique Cesar Carvalho de Resende, Matias Artur Klafke Schimuneck, Cristiano Bonato Both, Juliano Araujo Wickboldt, Johann M. Márquez-Barja
COPA: Experimenter-level Container Orchestration for Networking Testbeds Journal Article
In: IEEE Access, 8 , pp. 201781-201798, 2020, ISSN: 2169-3536.
Abstract Links BibTeX Tags: 5G Cloud Computing Container Management & Orchestration Fog & Edge Computing Network Orchestration Network Virtualization & Slicing
@article{journal/access/Resende20,
title = {COPA: Experimenter-level Container Orchestration for Networking Testbeds},
author = {Henrique Cesar Carvalho de Resende and Matias Artur Klafke Schimuneck and Cristiano Bonato Both and Juliano Araujo Wickboldt and Johann M. Márquez-Barja},
url = {https://ieeexplore.ieee.org/document/9247110},
doi = {10.1109/ACCESS.2020.3035619},
issn = {2169-3536},
year = {2020},
date = {2020-11-03},
urldate = {2020-11-03},
journal = {IEEE Access},
volume = {8},
pages = {201781-201798},
abstract = {As Cloud Computing (CC) branched areas such as Multi-access Edge Computing (MEC) and Fog computing are still on growing research interest. The creation of new tools to improve quality and speed the experimentation in such areas is a general interest. In this article, we propose COPA, an experimenter-level container orchestration tool for networking testbeds. This tool provides a friendly interface for the experimenter test container orchestration algorithms which can start, stop, copy, and even migrate a container from one host to another. COPA also includes network/resources monitoring to feed the experimenter’s orchestration algorithm so that it can make decisions based on real-time environment information. Furthermore, the experimenter can automatize the experiment scenario setup and deployment by pre-configuring in COPA. This tool helps the experimenter in testing different scenarios and quickly changing experiment parameters. Considering these features, COPA aims to provide an experimentation architecture to deploy and test container orchestration algorithms. Furthermore, we provide a case study explaining how COPA can be a key tool in the MEC and Network Function Virtualization (NFV) experimentation environments. This tool was already deployed in Federated Union of Telecommunications Research Facilities for an EU-Brazil Open Laboratory (FUTEBOL) testbeds as part of the control framework and was well validated by the project reviewers and partners.},
keywords = {5G, Cloud Computing, Container Management & Orchestration, Fog & Edge Computing, Network Orchestration, Network Virtualization & Slicing},
pubstate = {published},
tppubtype = {article}
}
As Cloud Computing (CC) branched areas such as Multi-access Edge Computing (MEC) and Fog computing are still on growing research interest. The creation of new tools to improve quality and speed the experimentation in such areas is a general interest. In this article, we propose COPA, an experimenter-level container orchestration tool for networking testbeds. This tool provides a friendly interface for the experimenter test container orchestration algorithms which can start, stop, copy, and even migrate a container from one host to another. COPA also includes network/resources monitoring to feed the experimenter’s orchestration algorithm so that it can make decisions based on real-time environment information. Furthermore, the experimenter can automatize the experiment scenario setup and deployment by pre-configuring in COPA. This tool helps the experimenter in testing different scenarios and quickly changing experiment parameters. Considering these features, COPA aims to provide an experimentation architecture to deploy and test container orchestration algorithms. Furthermore, we provide a case study explaining how COPA can be a key tool in the MEC and Network Function Virtualization (NFV) experimentation environments. This tool was already deployed in Federated Union of Telecommunications Research Facilities for an EU-Brazil Open Laboratory (FUTEBOL) testbeds as part of the control framework and was well validated by the project reviewers and partners.