Abstract

Data centers consume a significant amount of energy. This problem is aggravated by the fact that most servers and desktops are underutilized when powered on, and still consume a majority of the energy of a fully utilized computer even when idle This problem would be much worse were it not for the growing use of virtual machines. Virtual machines allow system administrators to more fully utilize hardware capabilities by putting more than one virtual system on the same physical server. Many times, virtual machines are placed onto physical servers inefficiently. To address this inefficiency, I developed a new family of packing algorithms. This family of algorithms is meant to solve the problem of packing virtual machines onto a cluster of physical servers. This problem is different than the conventional bin packing problem in two ways. First, each server has multiple resources that can be consumed. Second, loads on virtual machines are probabilistic and not completely known to the packing algorithm. We first compare our developed algorithm with other bin packing algorithms and show that it performs better than state-of-the-art genetic algorithms in literature. We then show the general feasibility of our algorithm in packing real virtual machines on physical servers.

Degree

MS

College and Department

Physical and Mathematical Sciences; Computer Science

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2010-10-28

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd3994

Keywords

virtualization, optimization, energy, genetic algorithm

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