Research Area: Software Defined Networks
Software Defined Networking (SDN) has seen growing deployment in the large wired data center networks due to its advantages like better network manageability and higher-level abstractions. At the core of SDN is the separation and centralization of the control plane from the forwarding elements in the network as opposed to the distributed control plane of current networks. However various issues need to be addressed for an efficient transition to SDN from existing legacy networks. In this thesis, we address following three important challenges in this regard. (1) The task of deploying the distributed controllers continues to be performed in a manual and static way. To address this problem, we present a novel approach called InitSDN to bootstrapping the distributed software defined network architecture and deploying the distributed controllers. (2) Data center networks (DCNs) rely heavily on the use of group communications for various tasks such as management utilities, collaborative applications, distributed databases, etc. SDN provides new opportunities for re-engineering multicast protocols that can address current limitations with IP multicast. To that end we present a novel approach to using SDN-based multicast (SDMC) for flexible, network load-aware, and switch memory-efficient group communication in DCNs. (3) SDN has been slow to be used in the wireless scenario like wireless mesh net- works (WSN) compared to wired data center networks. This is due to the fact that SDN (and its underlying OpenFlow protocol) was designed initially to run in the wired network where SDN controller has wired access to all the switches in the network. To address this challenge, we propose a pure opneflow based approach for adapting SDN in wireless mesh netowrks by extending current OpenFlow protocol for routing in the wireless network.
Name of the Researcher: Patil, Prithviraj Pradiprao
Name of the Supervisor(s): Dr. Aniruddha S. Gokhale
Year of Completion: 2016
University: Vanderbilt University
Thesis Link: Home Page Url
