Abstract
| Original language | Undefined |
|---|---|
| Title of host publication | Proceedings of the 4th International Conference on Cloud Networking, CloudNet 2015 |
| Place of Publication | Danvers, MA, USA |
| Publisher | IEEE |
| Pages | 132-138 |
| Number of pages | 7 |
| ISBN (Print) | 978-1-4673-9501-4 |
| DOIs | |
| Publication status | Published - 6 Oct 2015 |
Publication series
| Name | |
|---|---|
| Publisher | IEEE |
Keywords
- EWI-26340
- IR-98280
- METIS-314979
Cite this
}
Mobility and Bandwidth Prediction as a Service in Virtualized LTE Systems. / Karimzadeh Motallebi Azar, Morteza ; Zhao, Zhongliang; Hendriks, Luuk; de Oliveira Schmidt, R.; la Fleur, Sebastiaan; van den Berg, Hans Leo; Pras, Aiko; Braun, Torsten; Julian Corici, Marius.
Proceedings of the 4th International Conference on Cloud Networking, CloudNet 2015. Danvers, MA, USA : IEEE, 2015. p. 132-138.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Mobility and Bandwidth Prediction as a Service in Virtualized LTE Systems
AU - Karimzadeh Motallebi Azar, Morteza
AU - Zhao, Zhongliang
AU - Hendriks, Luuk
AU - de Oliveira Schmidt, R.
AU - la Fleur, Sebastiaan
AU - van den Berg, Hans Leo
AU - Pras, Aiko
AU - Braun, Torsten
AU - Julian Corici, Marius
N1 - 10.1109/CloudNet.2015.7335295
PY - 2015/10/6
Y1 - 2015/10/6
N2 - Recently telecommunication industry benefits from infrastructure sharing, one of the most fundamental enablers of cloud computing, leading to emergence of the Mobile Virtual Network Operator (MVNO) concept. The most momentous intents by this approach are the support of on-demand provisioning and elasticity of virtualized mobile network components, based on data traffic load. To realize it, during operation and management procedures, the virtualized services need be triggered in order to scale-up/down or scale-out/in an service instance. In this paper we propose an architecture called MOBaaS (Mobility and Bandwidth Availability Prediction as a Service), comprising two algorithms in order to predict user(s) mobility and network link bandwidth availability, that can be implemented in cloud based mobile network structure and can be used as a support service by any other virtualized mobile network service. MOBaaS can provide prediction information in order to generate required triggers for on-demand deploying, provisioning, disposing of virtualized network components. This information can be used for self-adaptation procedures and optimal network function configuration during run-time operation, as well. Through the preliminary experiments with the prototype implementation on the OpenStack platform, we evaluated and confirmed the feasibility and the effectiveness of the prediction algorithms and the proposed architecture.
AB - Recently telecommunication industry benefits from infrastructure sharing, one of the most fundamental enablers of cloud computing, leading to emergence of the Mobile Virtual Network Operator (MVNO) concept. The most momentous intents by this approach are the support of on-demand provisioning and elasticity of virtualized mobile network components, based on data traffic load. To realize it, during operation and management procedures, the virtualized services need be triggered in order to scale-up/down or scale-out/in an service instance. In this paper we propose an architecture called MOBaaS (Mobility and Bandwidth Availability Prediction as a Service), comprising two algorithms in order to predict user(s) mobility and network link bandwidth availability, that can be implemented in cloud based mobile network structure and can be used as a support service by any other virtualized mobile network service. MOBaaS can provide prediction information in order to generate required triggers for on-demand deploying, provisioning, disposing of virtualized network components. This information can be used for self-adaptation procedures and optimal network function configuration during run-time operation, as well. Through the preliminary experiments with the prototype implementation on the OpenStack platform, we evaluated and confirmed the feasibility and the effectiveness of the prediction algorithms and the proposed architecture.
KW - EWI-26340
KW - IR-98280
KW - METIS-314979
U2 - 10.1109/CloudNet.2015.7335295
DO - 10.1109/CloudNet.2015.7335295
M3 - Conference contribution
SN - 978-1-4673-9501-4
SP - 132
EP - 138
BT - Proceedings of the 4th International Conference on Cloud Networking, CloudNet 2015
PB - IEEE
CY - Danvers, MA, USA
ER -