Application Specific Slicing for MVNO through Software-Defined Data Plane Enhancing SDN

Akihiro NAKAO; Ping DU; Takamitsu IWAI

doi:10.1587/transcom.E98.B.2111

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Application Specific Slicing for MVNO through Software-Defined Data Plane Enhancing SDN

Akihiro NAKAO, Ping DU, Takamitsu IWAI

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In this paper, we apply the concept of software-defined data plane to defining new services for Mobile Virtual Network Operators (MVNOs). Although there are a large number of MVNOs proliferating all over the world and most of them provide low bandwidth at low price, we propose a new business model for MVNOs and empower them with capability of tailoring fine-grained subscription plans that can meet users' demands. For example, abundant bandwidth can be allocated for some specific applications, while the rest of the applications are limited to low bandwidth. For this purpose, we have recently proposed the concept of application and/or device specific slicing that classifies application and/or device specific traffic into slices and applies fine-grained quality of services (QoS), introducing various applications of our proposed system [9]. This paper reports the prototype implementation of such proposal in the real MVNO connecting customized smartphones so that we can identify applications from the given traffic with 100% accuracy. In addition, we propose a new method of identifying applications from the traffic of unmodified smartphones by machine learning using the training data collected from the customized smartphones. We show that a simple machine learning technique such as random forest achives about 80% of accuracy in applicaton identification.

Publication: IEICE TRANSACTIONS on Communications Vol.E98-B No.11 pp.2111-2120

Publication Date: 2015/11/01

Publicized

Online ISSN: 1745-1345

DOI: 10.1587/transcom.E98.B.2111

Type of Manuscript: Special Section INVITED PAPER (Special Section on Network Systems for Virtualized Environment)

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Authors

Akihiro NAKAO
  The University of Tokyo
Ping DU
  The University of Tokyo
Takamitsu IWAI
  The University of Tokyo

Keyword

Software-Defined Networking (SDN), Network Functions Virtualisation (NFV), network virtualization

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Akihiro NAKAO, Ping DU, Takamitsu IWAI, "Application Specific Slicing for MVNO through Software-Defined Data Plane Enhancing SDN" in IEICE TRANSACTIONS on Communications, vol. E98-B, no. 11, pp. 2111-2120, November 2015, doi: 10.1587/transcom.E98.B.2111.
Abstract: In this paper, we apply the concept of software-defined data plane to defining new services for Mobile Virtual Network Operators (MVNOs). Although there are a large number of MVNOs proliferating all over the world and most of them provide low bandwidth at low price, we propose a new business model for MVNOs and empower them with capability of tailoring fine-grained subscription plans that can meet users' demands. For example, abundant bandwidth can be allocated for some specific applications, while the rest of the applications are limited to low bandwidth. For this purpose, we have recently proposed the concept of application and/or device specific slicing that classifies application and/or device specific traffic into slices and applies fine-grained quality of services (QoS), introducing various applications of our proposed system [9]. This paper reports the prototype implementation of such proposal in the real MVNO connecting customized smartphones so that we can identify applications from the given traffic with 100% accuracy. In addition, we propose a new method of identifying applications from the traffic of unmodified smartphones by machine learning using the training data collected from the customized smartphones. We show that a simple machine learning technique such as random forest achives about 80% of accuracy in applicaton identification.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.E98.B.2111/_p

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@ARTICLE{e98-b_11_2111,
author={Akihiro NAKAO, Ping DU, Takamitsu IWAI, },
journal={IEICE TRANSACTIONS on Communications},
title={Application Specific Slicing for MVNO through Software-Defined Data Plane Enhancing SDN},
year={2015},
volume={E98-B},
number={11},
pages={2111-2120},
abstract={In this paper, we apply the concept of software-defined data plane to defining new services for Mobile Virtual Network Operators (MVNOs). Although there are a large number of MVNOs proliferating all over the world and most of them provide low bandwidth at low price, we propose a new business model for MVNOs and empower them with capability of tailoring fine-grained subscription plans that can meet users' demands. For example, abundant bandwidth can be allocated for some specific applications, while the rest of the applications are limited to low bandwidth. For this purpose, we have recently proposed the concept of application and/or device specific slicing that classifies application and/or device specific traffic into slices and applies fine-grained quality of services (QoS), introducing various applications of our proposed system [9]. This paper reports the prototype implementation of such proposal in the real MVNO connecting customized smartphones so that we can identify applications from the given traffic with 100% accuracy. In addition, we propose a new method of identifying applications from the traffic of unmodified smartphones by machine learning using the training data collected from the customized smartphones. We show that a simple machine learning technique such as random forest achives about 80% of accuracy in applicaton identification.},
keywords={},
doi={10.1587/transcom.E98.B.2111},
ISSN={1745-1345},
month={November},}

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TY - JOUR
TI - Application Specific Slicing for MVNO through Software-Defined Data Plane Enhancing SDN
T2 - IEICE TRANSACTIONS on Communications
SP - 2111
EP - 2120
AU - Akihiro NAKAO
AU - Ping DU
AU - Takamitsu IWAI
PY - 2015
DO - 10.1587/transcom.E98.B.2111
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E98-B
IS - 11
JA - IEICE TRANSACTIONS on Communications
Y1 - November 2015
AB - In this paper, we apply the concept of software-defined data plane to defining new services for Mobile Virtual Network Operators (MVNOs). Although there are a large number of MVNOs proliferating all over the world and most of them provide low bandwidth at low price, we propose a new business model for MVNOs and empower them with capability of tailoring fine-grained subscription plans that can meet users' demands. For example, abundant bandwidth can be allocated for some specific applications, while the rest of the applications are limited to low bandwidth. For this purpose, we have recently proposed the concept of application and/or device specific slicing that classifies application and/or device specific traffic into slices and applies fine-grained quality of services (QoS), introducing various applications of our proposed system [9]. This paper reports the prototype implementation of such proposal in the real MVNO connecting customized smartphones so that we can identify applications from the given traffic with 100% accuracy. In addition, we propose a new method of identifying applications from the traffic of unmodified smartphones by machine learning using the training data collected from the customized smartphones. We show that a simple machine learning technique such as random forest achives about 80% of accuracy in applicaton identification.
ER -