DocumentCode
3696563
Title
Mobility and bandwidth prediction as a service in virtualized LTE systems
Author
Morteza Karimzadeh;Zhongliang Zhao;Luuk Hendriks;Ricardo de O. Schmidt;Sebastiaan la Fleur;Hans van den Berg;Aiko Pras;Torsten Braun;Marius Julian Corici
Author_Institution
University of Twente
fYear
2015
Firstpage
132
Lastpage
138
Abstract
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.
Keywords
"Bandwidth","Cloud computing","Mobile communication","Prediction algorithms","Mobile computing","History","Computer architecture"
Publisher
ieee
Conference_Titel
Cloud Networking (CloudNet), 2015 IEEE 4th International Conference on
Type
conf
DOI
10.1109/CloudNet.2015.7335295
Filename
7335295
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