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Record W2095445631 · doi:10.1109/iri.2013.6642495

Efficient live wide area VM migration with IP address change using type II hypervisor

2013· article· en· W2095445631 on OpenAlexaff
Samuel A. Ajila, Omhenimhen Iyamu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsLive migrationComputer scienceHypervisorOperating systemVirtual machineComputer networkHost (biology)Network packetState (computer science)Virtual networkDistributed computingVirtualizationCloud computing

Abstract

fetched live from OpenAlex

Live wide area virtual machine migration is the transfer of a virtual machine currently running and connected to clients from one host server to another host server over a Wide Area Network. In this thesis we have designed and implemented an approach for live migration while allowing the IP address of the VM to change. Our approach is efficient and with little disruption in services. The solution is divided into three key parts, runtime state migration, persistent state migration, and network connection handling. The solution uses the type 2 hypervisor Virtual Box. The runtime state migration is executed using Virtual Box's teleportation function. The persistent state migration is split into stages executed at different point of the migration. The network connections are done using packet redirection and Dynamic DNS. Testing revealed a 358 times better in total disruption time compared to freeze and copy migration.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.241
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2013
Admission routes1
Has abstractyes

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