Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Department

Electrical Engineering

First Advisor's Name

Jean Andrian

First Advisor's Committee Title

Committee Co-Chair

Second Advisor's Name

Deng Pan

Second Advisor's Committee Title

Committee Co-Chair

Third Advisor's Name

Hai Deng

Fourth Advisor's Name

Jeffrey Fan

Keywords

data center network, energy efficiency, green IT

Date of Defense

9-27-2012

Abstract

Energy efficient infrastructures or green IT (Information Technology) has recently become a hot button issue for most corporations as they strive to eliminate every inefficiency from their enterprise IT systems and save capital and operational costs. Vendors of IT equipment now compete on the power efficiency of their devices, and as a result, many of the new equipment models are indeed more energy efficient. Various studies have estimated the annual electricity consumed by networking devices in the U.S. in the range of 6 - 20 Terra Watt hours.

Our research has the potential to make promising solutions solve those overuses of electricity. An energy-efficient data center network architecture which can lower the energy consumption is highly desirable. First of all, we propose a fair bandwidth allocation algorithm which adopts the max-min fairness principle to decrease power consumption on packet switch fabric interconnects. Specifically, we include power aware computing factor as high power dissipation in switches which is fast turning into a key problem, owing to increasing line speeds and decreasing chip sizes. This efficient algorithm could not only reduce the convergence iterations but also lower processing power utilization on switch fabric interconnects. Secondly, we study the deployment strategy of multicast switches in hybrid mode in energy-aware data center network: a case of famous Fat-tree topology. The objective is to find the best location to deploy multicast switch not only to achieve optimal bandwidth utilization but also minimize power consumption. We show that it is possible to easily achieve nearly 50% of energy consumption after applying our proposed algorithm. Finally, although there exists a number of energy optimization solutions for DCNs, they consider only either the hosts or network, but not both. We propose a joint optimization scheme that simultaneously optimizes virtual machine (VM) placement and network flow routing to maximize energy savings. The simulation results fully demonstrate that our design outperforms existing host- or network-only optimization solutions, and well approximates the ideal but NP-complete linear program. To sum up, this study could be crucial for guiding future eco-friendly data center network that deploy our algorithm on four major layers (with reference to OSI seven layers) which are physical, data link, network and application layer to benefit power consumption in green data center.

Identifier

FI12111301

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