Adaptive Routing Using SDN and NFV

In recent times, the primary focus of every ISP is to deliver high quality of service for multimedia applications. Due to ever-increasing network traffic, it is challenging for ISPs to accomplish optimal network conditions. To achieve high-quality services implementation of network monitoring and QoS routing algorithm is inevitable. Also, several modifications occur while network planning especially in managing physical devices to host network services required to achieve QoS routing. Dynamic routing in physical network hardware is not suitable for cost effective business models. Therefore, to lower operational and capital expenditure, we propose a technique called adaptive routing managed with the support of SDN (Software Defined Networking and NFV (Network Function Virtualization). We introduce an economical routing model which will assist in meeting the demands of the consumers and at the same time provide significant savings in product cost and usability. To perform adaptive routing, we designed a topology in a virtualized environment. We programmed RINA (Recursive InterNetwork Architecture) for SDN management which acts as a steady northbound API. To implement NFV, we hosted Intrusion detection service(IDS) as a Virtual Network Function (VNF). We created two scenarios where we execute shortest path routing and adaptive routing. To compare these different routing scenarios, we ran a client-server DASH (Dynamic Adaptive Streaming over HTTP) application. Furthermore, we injected Iperf traffic into the network categorized as unwanted traffic. Lastly, we performed adaptive routing applying control theoretic technique with the help of SDN and NFV. By comparing two routing scenarios, we observed a notable difference in throughput for DASH application.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Electrical Engineering (UMKC)

Grantor dc:publisher

University of Missouri--Kansas City

Year dc:date.issued

2017

Author dc:creator

• Parab, Tejas Balkrishna

Advisor dc:contributor.advisor

• Medhi, Deepankar

Language dc:language.iso

en_US

Handle dc:identifier.uri

https://hdl.handle.net/10355/62668

OAI identifier oai:identifier

oai:mospace.umsystem.edu:10355/62668