Master Thesis Defense - January 28, 2015: Survivable Virtual Network Redesign and Embedding in Cloud Data Center Networks

Yiheng Chen

Wednesday, January 28, 2015 at 10:30
Room EV003.309

You are invited to attend the following M.A.Sc. (Information Systems Security) thesis examination.

Examining Committee

Dr. J. Bentahar, Chair
Dr. C. Assi, Supervisor
Dr. L. Wang, CIISE Examiner
Dr. D. Qiu, External Examiner (ECE)

Abstract

Today, the cloud computing paradigm enables multiple virtualized services to co-exist on the same physical machine and share the same physical resources, hardware, as well as energy consumption expenses. To allow cloud customers migrate their services on to the cloud side, the Infrastructure Provider (InP) or cloud data centre operator provisions to its tenants virtual networks (VNs) to host their services. Virtual Networks can be thought of as segmenting the physical network and its resources, and such VN requests (or tenants) need to be mapped onto the substrate network and provisioned with sufficient physical resources as per the users' requirements. With this emerging computing paradigm, cloud customers may demand to have highly reliable services for the hosted applications; however, failures often happen unexpectedly in data-centers, interrupting critical cloud services. Consequently, VN or cloud services are provisioned with redundant resources to achieve the demanded level of service reliability. To maintain a profitable operation of their network and resources, and thus achieve increased long term revenues, cloud network operators often rely on optimizing the mapping of reliable cloud services. Such problem is referred to as in the literature as "survivable virtual network embedding" (SVNE) problem..

 In this thesis, the survivable VN embedding problem is studied and a novel cost-efficient Survivable Virtual Network Redesign algorithm is carefully designed, presented, and evaluated. Subsequently, we distinguish between the communication services provided by the cloud provider and study the problem of survivable embedding of multicast services; we formally model the problem, and present two algorithms to reactively maintain Multicast trees in cloud data centers upon failures.