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Record W2114345510 · doi:10.1109/cnsr.2011.21

Tuning Open-iSCSI for Operation over WAN Links

2011· article· en· W2114345510 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Storage Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsiSCSIComputer scienceThroughputComputer networkSCSIOperating systemComputer data storageWireless

Abstract

fetched live from OpenAlex

The relocation of live, running virtual machines from one physical host to another is a new and very desirable function because it provides a variety of features, including resilience to failures and flexibility of location. The data transfers required for live migration are supported in several commercial products by a protocol called iSCSI (Internet SCSI), which runs on top of TCP. We thoroughly tested the performance of a common open source component, the Open-iSCSI initiator, and found a drastic throughput degradation on 100 Mbps networks where the round trip time was more than about 40 ms. We localized the problem to the TCP send buffer size and tested two methods of setting the TCP send buffer size appropriately. Based on our results, we propose a performance tuning scheme that enables users of Open-iSCSI to achieve significant throughput gains. Our scheme results in a dramatic throughput jump from 14 Mbps to 70 Mbps on a 100 Mbps link with an RTT of 100 ms. We also modified one of the data structures internal to Open-iSCSI to handle multiple memory pages in a single scatter/gather list entry. This modification resulted in an additional 20% throughput increase on a 100 Mbps link with an RTT of 200 ms.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.522
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.079
GPT teacher head0.306
Teacher spread0.227 · 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

Quick stats

Citations5
Published2011
Admission routes1
Has abstractyes

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