Design and Implementation of Highly Available Linux Clusters
Bibliographic record
Abstract
Fueled by the Internet revolution and the lure of opportunities in the new converging world of voice, data and video over cost-effective networks, telecom and networking companies are attempting to offer the most complete and compelling end-to-end enterprise solutions. The interest in clustering from the telecom world comes from the fact that we can address the availability and scaled performance using cost-effective hardware and software while maintaining near telecom-grade characteristics. These characteristics include continuous service availability, high reliability, superior performance, high throughput for fast and reliable data streaming, flexibility in terms of fast reconfiguration, linear scalability, and ease and completeness of management. In 2000, the ARIES (Advanced Research on Internet E-Servers) project started at Ericsson Research Canada, aimed at finding and prototyping the necessary technology to prove the feasibility of a clustered Internet Server that provides telecom-grade characteristics. In 2001, ARIES evolved into a new direction to enhance the clustering capabilities Linux to fulfill the future demands for Mobile Internet Servers. This tutorial will address in detail all the design and implementation issues we faced building Linux clusters using Linux and Open Source Software as the base technology; in addition it will provide a how-to for building Linux clusters starting from scratch. Ibrahim Haddad is a System Designer at the Ericsson Research Open Architecture Lab in Montreal, Canada where he is primarily involved in researching carrier-class server nodes for real-time all-IP networks. The focus of his work at Ericsson is to bring telecom grade characteristics to Linux so that it can be considered as a potential operating system for carrier-class servers. Ibrahim received his Bachelor and Masters degrees in Computer Science from the Lebanese American University and he is currently a Dr.Sc. Candidate at Concordia University. Ibrahim is also involved in several Open Source projects and is a regular contributor to the Linux Journal. Frederic Rossi is a System Designer at the Ericsson Research Open Architecture Lab in Montreal, Canada where he is researching new load balancing and traffic distribution algorithms to improve Linux capabilities to be considered as a platform of choice for telecom grade clusters. Frederic received his Bachelor and Masters degrees in Computer Science from the University of Paris VIII. Proceedings of the 2001 IEEE International Conference on Cluster Computing (CLUSTER01) 0-7695-1116-3/02 $17.00 © 2002 IEEE
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".