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.
Bibliographic record
Abstract
Cloud Computing is the emergent technology that promises on-demand, dynamic and easily accessible computing power. The “pay-as-you-use” scheme is attractive for small to medium sized businesses as these organizations are less inclined to purchase large amounts of physical machines to satisfy their immediate computing needs. Various cloud services are already available on the market. Many of them implement some form of dynamic provisioning of computing resources through the use of Virtual Machine (VM) tech- nologies like Xen [13], VMWare [28] or KVM [16]. Among them, the Amazon Elastic Cloud (EC2) [3] can be considered the most popular and mature solution. Eucalyptus [20], a cloud enabling infrastructure is the result of a research project from the University of California, Santa Barbara. Eucalyptus stands for “Elastic Utility Computing Architecture for Linking Your Programs To Useful Systems”. It aims to provide a simple to set up cloud solution for the research and development of cloud driven applications. By combining common web-service, Linux tools and the Xen Virtual Machine Hypervisor, Eucalyptus successfully implemented partial functionality of the popular Amazon EC2. As a consequence of recreating a “free” version of EC2, this open source project has attracted much attention and it is scheduled to be included into Ubuntu 9.10 (code name Karmic Koala) [15], the to-be-release version of a popular Linux distribution. This document records a recent effort to evaluate Eucalyptus as a viable open source solution to cloud computing. The evaluation focuses on the design, setup, usability and performance of Eucalyptus. In Section 2, we discuss the general design goals and infrastructure layout of Eucalyptus. Section 3 documents the process of setting up a Eucalyptus environment. Section 4 covers the usage and general impressions of Eucalyptus’s functionalities. In Section 5, we developed a demonstrator to illustrate the potential real-world usage of Eucalyptus v1.4. Finally in Section 7 and 8, we provide some related work and a conclusion to this document.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it