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Implementing Migration-Aware Virtual Machines

Authors: Taimur Al Said; Omer F. Rana;

Implementing Migration-Aware Virtual Machines

Abstract

Virtual Machines hosted in cloud systems are susceptible to migration usually without notifying the cloud consumer. This is generally undertaken to load balance user requests across multiple data centres, often without direct awareness of the user. Migration could be to a regional site or to a data centre in another geographical area, i.e. to a country which has non-conforming laws with regards to data privacy. This concern becomes even more significant when a cloud federation is considered, where a number of different providers may need to work together. It is therefore necessary to develop a mechanism that enables a user to detect if migration of a VM has happened. More importantly, such a mechanism should be user driven and not require input from a provider. We compare various techniques to enable a VM migration to be detected, by monitoring events inside a VM that could signify whether such a migration has taken place, and subsequently notifying the owner about such an event. A review of migration detection techniques is presented followed by the proposition of a hybrid model to carry out the migration detection process.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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