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Software Defined Networking: Applicability and Service Possibilities

Software Defined Networking: Applicability and Service Possibilities

Hot PhD Thesis on Software Defined Networking: Applicability and Service Possibilities

Research Area:  Software Defined Networks

Abstract:

   Network Service Providers (NSP) often choose to over provision their networks instead of deploying proper Quality of Services (QoS) mechanisms that allow for traffic differentiation and predictable quality. This tendency of over provisioning is not sustainable for the simple reason that network resources are limited. Hence, to counteract this trend, current QoS mechanisms must become simpler to deploy and operate, in order to motivate NSPs to employ QoS techniques instead of over provisioning. Software Defined Networking (SDN) represents a paradigm shift in the way telecommunication and data networks are designed and managed.
    Further, each chapter proposes solutions to address the identified challenges, and demonstrates these solutions by testing them in various network scenarios. The last chapter of the thesis concentrates on applying SDN to improve QoS and increase the network utilization in a novel data center environment. This environment comprises a hybrid packet-circuit architecture, on top of which intelligent algorithms are applied in order to selectively offload traffic from the capacity constrained packet based network onto optical circuits. Overall, the research work presented in this thesis identifies and addresses the critical aspects of SDN based QoS provisioning. Moreover, several tests and demonstrations have been performed by using virtualization techniques. These tests aim to support the proposed ideas, and also to create a better picture of practical SDN deployments and the difficulties that arise in such virtualized environments.

Name of the Researcher:  Cosmin Marius Caba

Name of the Supervisor(s):  Jose Soler, Lars Dittmann

Year of Completion:  2016

University:  Technical University of Denmark

Thesis Link:   Home Page Url