Le système de composants Fractal

Les approches à base de composants apparaissent de plus en plus incontournables pour le développement de systèmes et d'applications répartis. Il s'agit de faire face à la complexité sans cesse croissante de ces logiciels et de répondre aux grands défis de l'ingénierie des systèmes : passage à grande échelle, administration, autonomie. Après les objets dans la première moitié des années 1990, les composants se sont imposés comme le paradigme clé de l'ingénierie des intergiciels et de leurs applications dans la seconde moitié des années 1990. L'intérêt de la communauté industrielle et académique s'est d'abord porté sur les modèles de composants pour les applications comme EJB, CCM ou .NET. A partir du début des années 2000, le champ d'application des composants s'est étendu aux couches inférieures : systèmes et intergiciels. Il s'agit toujours, comme pour les applications, d'obtenir des entités logicielles composables aux interfaces spécifiées contractuellement, déployables et configurables~; mais il s'agit également d'avoir des plates-formes à composants suffisamment performantes et légères pour ne pas pénaliser les performances du système. Le modèle de composants Fractal remplit ces conditions

AcTinG: Accurate Freerider Tracking in Gossip

Abstract-Gossip-based content dissemination protocols are a scalable and cheap alternative to centralised content sharing systems. However, it is well known that these protocols suffer from rational nodes, i.e., nodes that aim at downloading the content without contributing their fair share to the system. While the problem of rational nodes that act individually has been well addressed in the literature, colluding rational nodes is still an open issue. Indeed, LiFTinG, the only existing gossip protocol addressing this issue, yields a high ratio of false positive accusations of correct nodes. In this paper, we propose AcTinG, a protocol that prevents rational collusions in gossip-based content dissemination protocols, while guaranteeing zero false positive accusations. We assess the performance of AcTinG on a testbed comprising 400 nodes running on 100 physical machines, and compare its behaviour in the presence of colluders against two state-of-the-art protocols: BAR Gossip that is the most robust protocol handling non-colluding rational nodes, and LiFTinG, the only existing gossip protocol that handles colluding nodes. The performance evaluation shows that AcTinG is able to deliver all messages despite the presence of colluders, whereas both LiFTinG and BAR Gossip suffer heavy message loss. It also shows that AcTinG is resilient to massive churn. Finally, using simulations involving up to a million nodes, we show that AcTinG exhibits similar scalability properties as standard gossip-based dissemination protocols

The Next 700 BFT Protocols

Modern Byzantine fault-tolerant state machine replication (BFT) protocols involve about 20.000 lines of challenging C++ code encompassing synchronization, networking and cryptography. They are notoriously difficult to develop, test and prove. We present a new abstraction to simplify these tasks. We treat a BFT protocol as a composition of instances of our abstraction. Each instance is developed and analyzed independently. To illustrate our approach, we first show how, with our abstraction, the benefits of a BFT protocol like Zyzzyva could have been obtained with much less pain. Namely, we develop AZyzzyva, a new protocol that mimics the behavior of Zyzzyva in best-case situations (for which Zyzzyva was optimized) using less than 24% of the actual code of Zyzzyva. To cover worst-case situations, our abstraction enables to compose AZyzzyva with any existing BFT protocol, typically, a classical one like PBFT which has been proved correct and widely tested. We then present Aliph, a new BFT protocol that outperforms previous BFT protocols both in terms of latency (by up to 30%) and throughput (by up to 360%). Development of Aliph required two new instances of our abstraction. Each instance contains less than 25% of the code needed to develop state-of-the-art BFT protocols

Support pour la reconfiguration d'implantation dans les applications à composants Java

De nombreux modèles de composants sont aujourd'hui utilisés à des fins variées : construction d'applications, d'intergiciels, ou encore de systèmes d'exploitation. Ces modèles permettent tous des reconfigurations de structure, c'est-à-dire des modifications de l'architecture de l'application. En revanche, peu permettent des reconfigurations d'implantation qui consistent à modifier dynamiquement le code des composants de l'application. Dans cet article nous présentons le travail que nous avons effectué dans JULIA, une implémentation Java du modèle FRACTAL, pour permettre le dynamisme d'implantation. Nous montrons comment les limitations du mécanisme de chargement de classes Java ont été contournées pour permettre de modifier les classes d'implémentation et d'interfaces des composants. Nous décrivons également l'intégration de notre proposition avec l'ADL de JULIA. –––––Nowadays, numerous component models are used for various purposes: to build applications, middleware or even operating systems. Those models commonly support structure reconfiguration, that is modification of application's architecture at runtime. On the other hand, very few allow implementation reconfiguration, that is runtime modification of the code of components building the application. In this article we present the work we performed on JULIA, a Java-based implementation of the FRACTAL component model, in order for it to support implementation reconfigurations. We show how we overcame the limitations of Java class loading mechanism to allow runtime modifications of components' implementation and interfaces. We also describe the integration of our solution with the JULIA ADL

Large Pages May Be Harmful on NUMA Systems

Application virtual address space is divided into pages, each requiring a virtual-to-physical translation in the page table and the TLB. Large working sets, common among modern applications, necessitate a lot of translations, which increases memory consumption and leads to high TLB and page fault rates. To address this problem, recent hardware introduced support for large pages Large pages require fewer translations to cover the same address space, so the associated problems diminish. We discover, however, that on systems with non-uniform memory access times (NUMA) large pages may fail to deliver benefits or even cause performance degradation. On NUMA systems the memory is spread across several physical nodes; using large pages may contribute to the imbalance in the distribution of memory controller requests and reduced locality of accesses, both of which can drive up memory latencies. Our analysis concluded that: (a) on NUMA systems with large pages it is more crucial than ever to use memory placement algorithms that balance the load across memory controllers and maintain locality; (b) there are cases when NUMA-aware memory placement is not sufficient for optimal performance, and the only resort is to split the offending large pages. To address these challenges, we extend an existing NUMA page placement algorithm with support for large pages. We demonstrate that it recovers the performance lost due to the use of large pages and makes their benefits accessible to application

Asynchronous, hierarchical and scalable deployment of component-based applications

Abstract. The deployment of distributed component-based applications is a complex task. Proposed solutions are often centralized, which excludes their use for the deployment of large-scale applications. Besides, these solutions do often not take into account the functional constraints, i.e. the dependences between component activations. Finally, most of them are not fault-tolerant. In this paper, we propose a deployment application that deals with these three problems. It is hierarchical, which is a necessary feature to guarantee scalability. Moreover, it is designed as a distributed workflow decomposed into tasks executing asynchronously, which allows an "as soon as possible" activation of deployed components. Finally, the proposed deployment application is fault-tolerant. This is achieved by the use of persistent agents with atomic execution. This deployment application has been tested and performance measurements show that it is scalable

Mely: Efficient Workstealing for Multicore Event-Driven Systems

Many high-performance communicating systems are designed using the event-driven paradigm. As multicore platforms are now pervasive, it becomes crucial for such systems to take advantage of the available hardware parallelism. Event-coloring is a promising approach in this regard. First, it allows programmers to simply and progressively inject support for the safe, parallel execution of multiple event handlers through the use of annotations. Second, it relies on a workstealing algorithm to dynamically balance the execution of event handlers on the available cores. This paper studies the impact of the workstealing algorithm on the overall system performance. We first show that the only existing workstealing algorithm designed for event-coloring runtimes is not always efficient: for instance, it causes a 33% performance degradation on a Web server. We then introduce several enhancements to improve the workstealing behavior. An evaluation using both microbenchmarks and real applications, a Web server and the Secure File Server (SFS), shows that our system consistently outperforms a state-of-the-art runtime (Libasync-smp), with or without workstealing. In particular, our new workstealing improves performance by up to +25% compared to Libasync-smp without workstealing and by up to +73% compared to the Libasync-smp workstealing algorithm, in the Web server case

SCA Platform Specifications - Version 2.0

The SCOrWare project aims at building an open source implementation of the Service Component Architecture (SCA) specifications. This implementation is composed of 1) a runtime platform for deploying, executing, and managing SCAbased applications, 2) a set of development tools for modeling, designing, and implementing SCA-based applications, and 3) a set of demonstrators. This document contains the specifications of the SCOrWare runtime platform. Section 1.1 lists the parts of SCA specifications supported by the SCOrWare platform. Section 1.2 gives an overview of the SCOrWare platform, and a summary of next chapters of this document. Section 1.3 lists the main update from the version 1 to the version 2 of this documen

Placement of Virtual Containers on NUMA systems: A Practical and Comprehensive Model

Our work addresses the problem of placement of threads, or virtual cores, onto physical cores in a multicore NUMA system. Different placements result in varying degrees of contention for shared resources, so choosing the right placement can have a large effect on performance. Prior work has studied this problem, but either addressed hardware with specific properties, leaving us unable to generalize the models to other systems, or modeled much simpler effects than the actual performance in different placements. Our contribution is a general framework for reasoning about workload placement on machines with shared resources. It enables us to build an accurate performance model for any machine with a hierarchy of known shared resources automatically, with only minimal input from the user. Using our methodology, data center operators can minimize the number of NUMA (CPU+memory) nodes allocated for an application or a service, while ensuring that it meets performance objectives

Data Science

International audienceLa data science, ou science des données, est la discipline qui traite de la collecte, de la préparation, de la gestion, de l'analyse, de l'interprétation et de la visualisation de grands ensembles de données complexes. Elle n'est pas seulement concernée par les outils et les méthodes pour obtenir, gérer et analyser les données ; elle consiste aussi à en extraire de la valeur et de la connaissance. Cet ouvrage présente les fondements scientifiques et les composantes essentielles de la science des données, à un niveau accessible aux étudiants de master et aux élèves ingénieurs. Notre souci a été de proposer un exposé cohérent reliant la théorie aux algorithmes développés dans ces domaines. Il s'adresse aux chercheurs et ingénieurs qui abordent les problématiques liées à la science des données, aux data scientists de PME qui utilisent en profondeur les outils d'apprentissage, mais aussi aux étudiants de master, doctorants ou encore futurs ingénieurs qui souhaitent un ouvrage de référence en data science. À qui s'adresse ce livre ? • Aux développeurs, statisticiens, étudiants et chefs de projets ayant à résoudre des problèmes de data science. • Aux data scientists, mais aussi à toute personne curieuse d'avoir une vue d'ensemble de l'état de l'art du machine learning