Notice bibliographique
Résumé
In recent years, multi-tier architectures have become the standard computing environment for web- and enterprise applications. The application server tier is often the heart of the system embedding the business logic. Adaptability, in particular the capability to adjust to the load submitted to the system and to handle the failure of individual components, are of outmost importance in order to provide 7/24 access and high performance. Replication is a common means to achieve these reliability and scalability requirements. With replication, the application server tier consists of several server replicas. Thus, if one replica fails, others can take over. Furthermore, the load can be distributed across the available replicas. Although many replication solutions have been proposed so far, most of them have been either developed for fault-tolerance or for scalability. Furthermore, only few have considered that the application server tier is only one tier in a multi-tier architecture, that this tier maintains state, and that execution in this environment can follow complex patterns. Thus, existing solutions often do not provide correctness beyond some basic application scenarios. In this thesis we tackle the issue of replication of the application server tier from ground off and develop a unified solution that provides both fault-tolerance and scalability. We first describe a set of execution patterns that describe how requests are typically executed in multi-tier architectures. They consider the flow of execution across client tier, application server tier, and database tier. In particular, the execution patterns describe how requests are associated with transactions, the fundamental execution units at application server and database tiers. Having these execution patterns in mind, we provide a formal definition of what it means to provide a correct execution across all tiers, even in case failures occur and the application server tier is replicated. Informally, a replicated system is correct if it behaves exactly as a non-replicated that never fails. From there, we propose a set of replication algorithms for fault-tolerance that provide correctness for the execution patterns that we have identified The main principle is to let a primary AS replica to execute all client requests, and to propagate any state changes performed by a transaction to backup replicas at transaction commit time. The challenges occur as requests can be associated in different ways with transactions. Then, we extend our fault-tolerance solution and develop a unified solution that provides both fault-tolerance and load-balancing. In this extended solution, each application server replica is able to execute client requests as a primary and at the same time serves as backup for other replicas. The framework provides a transparent, truly distributed and lightweight load distribution mechanism which takes advantage of the fault-tolerance infrastructure. Our replication tool is implemented as a plug-in of JBoss application server and the performance is carefully evaluated, comparing with JBoss' own replication solutions. The evaluation shows that our protocols have very good performance and compare favorably with existing solutions.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».