Distributed virtual machine migration for cloud data centre environments

Hamilton, Gregg (2014) Distributed virtual machine migration for cloud data centre environments. MSc(R) thesis, University of Glasgow.

Abstract

Virtualisation of computing resources has been an increasingly common practice in recent years, especially in data centre environments. This has helped in the rise of cloud computing, where data centre operators can over-subscribe their physical servers through the use of virtual machines in order to maximise the return on investment for their infrastructure. Similarly, the network topologies in cloud data centres are also heavily over-subscribed, with the links in the core layers of the network being the most over-subscribed and congested of all, yet also being the most expensive to upgrade. Therefore operators must find alternative, less costly ways to recover their initial investment in the networking infrastructure.

The unconstrained placement of virtual machines in a data centre, and changes in data centre traffic over time, can cause the expensive core links of the network to become heavily congested. In this thesis, S-CORE, a distributed, network-load aware virtual machine migration scheme is presented that is capable of reducing the overall communication cost of a data centre network.

An implementation of S-CORE on the Xen hypervisor is presented and discussed, along with simulations and a testbed evaluation. The results of the evaluation show that S-CORE is capable of operating on a network with traffic comparable to reported data centre traffic characteristics, with minimal impact on the virtual machines for which it monitors network traffic and makes migration decisions on behalf of. The simulation results also show that S-CORE is capable of efficiently and quickly reducing communication across the links at the core layers of the network.

• Item Type: Thesis (MSc(R))
• Qualification Level: Masters
• Keywords: cloud computing, data centers, distributed virtual machine migration, network management, resource consolidation
• Subjects: Q Science > QA Mathematics; Q Science > QA Mathematics > QA75 Electronic computers. Computer science; Q Science > QA Mathematics > QA76 Computer software
• Colleges/Schools: College of Science and Engineering > School of Computing Science
• Supervisor's Name: Pezaros, Dr. Dimitrios P.
• Date of Award: 2014
• Depositing User: Gregg Hamilton
• Unique ID: glathesis:2014-5077
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 02 Apr 2014 15:08
• Last Modified: 02 Apr 2014 15:27
• URI: https://theses.gla.ac.uk/id/eprint/5077