Bibliographic record
Abstract
Cloud computing usage has experienced a tremendous growth in companies over the past few years.It exposes, through the Internet, a set of technologies granting access to computing resources.These technologies virtualize physical machines to provide virtual resources which are isolated one from another.If this isolation mechanism is a guarantee for data security, it can cause a serious drop in performance.Indeed, virtual systems have the illusion of an exclusive access to the host's resources and they use them without considering the needs of others.This causes some interferences and decreases the performance of guest environments.Some applications, known as cloud operating systems, are commonly used to supervise cloud computing platforms.These applications simplify the interactions of the users with the infrastructure.However, they can cause faulty executions when misconfigured.Here we will focus on issues related to the use of Openstack as a cloud management application.The objective of this study is to provide administrators with a tool to monitor cloud tasks and locate potential drops of performance in both application and virtualization layers.Our approach is based on tracing, to produce detailed information about service operations.By tracing the various layers of the infrastructure simultaneously, it is possible to follow user requests and accurately determine the performance of deployed services.We use LTTng, a high-performance tracer, with very low impact on system behavior when tracing is enabled.It will be used to investigate all the host user space and kernel space executions.The traces will be collected and aggregated into a dedicated system to perform the analysis.The administrator can then obtain a resource utilization report, and be able to identify service troubles and subsequently take action to correct the problems.1. dans le domaine de l'infonuagique, un commutateur joue souvent le rle de routeur virtuel 2. Protocole rseau qui assure la configuration automatique des paramtres IP d'une station.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".