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On the Efficiency of Network Architecture and Network Provisioning in Cloud Data Centers
PhD Thesis Proposal Defence
Title: "On the Efficiency of Network Architecture and Network Provisioning
in Cloud Data Centers"
by
Mr. Ting WANG
Abstract:
Large-scale virtualized data centers enable the new era of could computing
and provide the core infrastructure to meet the computing and storage
requirements for both enterprise information technology needs and
cloud-based services. To support the ever-growing cloud computing needs,
the number of physical servers and virtual machines in today's data
centers are increasing exponentially, which in turn leads to enormous
challenges in designing cost-effective data center networks (DCN) and
efficient resource sharing via network provisioning. With data
availability and security at stake, the issues with data center networks
are more critical than ever. As one of the most important determinants of
network performance, the data center network architecture plays a dominate
role in determining the system reliability, network capacity, latency and
even the routing efficiency. With this motivation, in this thesis paper,
we firstly present the design, implementation and evaluation of SprintNet,
a novel server-centric network architecture for data centers. SprintNet
achieves high performance in network capacity, fault tolerance, and
network latency. SprintNet is also a scalable, yet low-diameter network
architecture where the longest path length can be limited by four hops and
is independent of the number of layers. In response to the critical
shortcomings of the server-centric architectures, we then propose an
effective hardware based approach to solve these issues and improve the
network efficiency. Afterwards, we design two torus-based DCN
architectures named NovaCube and CLOT, where the torus topology well
implements the network locality forming the servers in close proximity of
each other, which increases the communication efficiency. Moreover, in the
highly multiplexed shared cloud data centers, in order to efficiently
share the physical network resources among multiple tenants that have
diversified virtual network topologies with different network
characteristics, in this thesis we then propose an efficient online
heuristic virtual network embedding framework called Presto. Presto
operates with quite low computation complexity and greatly reduces the
search space, which far outperforms other candidates. The goal of Presto
is to maximize the economic revenue of infrastructure providers and
increase the resource utilization while minimizing the embedding cost.
Finally, we propose two efficient heuristic schemes to achieve an energy
proportional data center network from the perspective of resource
allocation, routing and flow scheduling, without compromising throughput
and fault tolerance too much. Both theoretical analysis and extensive
simulations have been conducted to evaluate the overall performance and
effectiveness of these proposals.
Date: Thursday, 28 May 2015
Time: 2:00pm - 4:00pm
Venue: Room 2132B
lift 19
Committee Members: Prof. Mounir Hamdi (Supervisor)
Prof. Qian Zhang (Chairperson)
Dr. Brahim Bensaou
Dr. Jogesh Muppala
**** ALL are Welcome ****