Today's mobile customers desire to remain connected anywhere, at any time, and using any device. This phenomenon has encouraged mobile network operators to build complex network architectures by incorporating new features and extensions, which are harder to manage and operate. In this article we propose a novel and simplified architecture for mobile networks. The proposed architecture, which we call CSDN (Cellular SDN), leverages software defined networking (SDN) and network functions virtualization (NFV). SDN abstracts the network and separates the control plane from the data plane; NFV decouples logical network functions from the underlying hardware, for dynamic resource orchestration. Furthermore, we argue that dynamic resource orchestration and optimal control need real-time context data analyses to make intelligent decisions. Thus, in the proposed architecture we exploit the capability of the mobile edge networks to gather information related to the network as well as the users. This information can be used to optimize network utilization and application performance, and to enhance the user experience. In addition, the gathered data can be shared with third party service providers, enabling the realization of innovative services.

Cellular Software Defined Network: a Framework

Mohamed Rasheed, Tinku
2015-01-01

Abstract

Today's mobile customers desire to remain connected anywhere, at any time, and using any device. This phenomenon has encouraged mobile network operators to build complex network architectures by incorporating new features and extensions, which are harder to manage and operate. In this article we propose a novel and simplified architecture for mobile networks. The proposed architecture, which we call CSDN (Cellular SDN), leverages software defined networking (SDN) and network functions virtualization (NFV). SDN abstracts the network and separates the control plane from the data plane; NFV decouples logical network functions from the underlying hardware, for dynamic resource orchestration. Furthermore, we argue that dynamic resource orchestration and optimal control need real-time context data analyses to make intelligent decisions. Thus, in the proposed architecture we exploit the capability of the mobile edge networks to gather information related to the network as well as the users. This information can be used to optimize network utilization and application performance, and to enhance the user experience. In addition, the gathered data can be shared with third party service providers, enabling the realization of innovative services.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/309535
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