2019mediaTUM (Technical University of Munich)Open access

Towards Virtualization of Software-Defined Networks: A Journey in Three Acts

Andreas Blenk, Wolfgang Kellerer

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Abstract

Today's networks lack the support to satisfy the highly diverse and fast changing demands of emerging applications and services. The paradigms Network Virtualization (NV) and Software-Defined Networking (SDN) can potentially overcome this impasse. The virtualization of software-defined networks is expected to bring dynamic resource sharing with guaranteed performance through NV and programmability through SDN; for the first time, tenants can program their requested network resources according to their service demands in a timely manner. However, the virtualization of SDN-based networks introduces new challenges for operators, e.g., a virtualization layer that provides low and guaranteed control plane latencies for tenants. Moreover, tenants' expectations range from a fast, nearly-instantaneous provisioning of virtual networks to predictable operations of virtual networks. With this paper, we give a comprehensive overview of the thesis, which can be split into three parts - a journey in three acts. The thesis first presents a measurement procedure and a flexible virtualization layer design for the virtualization of software-defined networks. Focusing on the control plane, it introduces mathematical models for analyzing four virtualization layer architectures. Third, for a fast and efficient virtual network provisioning on the data plane, the thesis proposes optimization systems using Machine Learning and Neural Computation.

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What this paper is about

Today's networks lack the support to satisfy the highly diverse and fast changing demands of emerging applications and services. The paradigms Network Virtualization (NV) and Software-Defined Networking (SDN) can potentially overcome this impasse. The virtualization of software-defined networks is expected to bring dynamic resource sharing with guaranteed performance through NV and programmability through SDN; for the first time, tenants can program their requested network resources according to their service demands in a timely manner. However, the virtualization of SDN-based networks introduces new challenges for operators, e.g., a virtualization layer that provides low and guaranteed control plane latencies for tenants. Moreover, tenants' expectations range from a fast, nearly-instantaneous provisioning of virtual networks to predictable operations of virtual networks. With this paper, we give a comprehensive overview of the thesis, which can be split into three parts - a journey in three acts. The thesis first presents a measurement procedure and a flexible virtualization layer design for the virtualization of software-defined networks. Focusing on the control plane, it introduces mathematical models for analyzing four virtualization layer architectures. Third, for a fast and efficient virtual network provisioning on the data plane, the thesis proposes optimization systems using Machine Learning and Neural Computation.

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Available abstract

Today's networks lack the support to satisfy the highly diverse and fast changing demands of emerging applications and services. The paradigms Network Virtualization (NV) and Software-Defined Networking (SDN) can potentially overcome this impasse. The virtualization of software-defined networks is expected to bring dynamic resource sharing with guaranteed performance through NV and programmability through SDN; for the first time, tenants can program their requested network resources according to their service demands in a timely manner. However, the virtualization of SDN-based networks introduces new challenges for operators, e.g., a virtualization layer that provides low and guaranteed control plane latencies for tenants. Moreover, tenants' expectations range from a fast, nearly-instantaneous provisioning of virtual networks to predictable operations of virtual networks. With this paper, we give a comprehensive overview of the thesis, which can be split into three parts - a journey in three acts. The thesis first presents a measurement procedure and a flexible virtualization layer design for the virtualization of software-defined networks. Focusing on the control plane, it introduces mathematical models for analyzing four virtualization layer architectures. Third, for a fast and efficient virtual network provisioning on the data plane, the thesis proposes optimization systems using Machine Learning and Neural Computation.

Key concepts: Full virtualization, Virtualization, Network virtualization, Computer science, Service virtualization, Software-defined networking, Provisioning, Distributed computing

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