Software dependability modeling using an industry-standard architecture description language

Performing dependability evaluation along with other analyses at architectural level allows both making architectural tradeoffs and predicting the effects of architectural decisions on the dependability of an application. This paper gives guidelines for building architectural dependability models for software systems using the AADL (Architecture Analysis and Design Language). It presents reusable modeling patterns for fault-tolerant applications and shows how the presented patterns can be used in the context of a subsystem of a real-life application

Modeling and analysis of high availability techniques in a virtualized system

Availability evaluation of a virtualized system is critical to the wide deployment of cloud computing services. Time-based, prediction-based rejuvenation of virtual machines (VM) and virtual machine monitors, VM failover and live VM migration are common high-availability (HA) techniques in a virtualized system. This paper investigates the effect of combination of these availability techniques on VM availability in a virtualized system where various software and hardware failures may occur. For each combination, we construct analytic models rejuvenation mechanisms to improve VM availability; (2) prediction-based rejuvenation enhances VM availability much more than time-based VM rejuvenation when prediction successful probability is above 70%, regardless failover and/or live VM migration is also deployed; (3) failover mechanism outperforms live VM migration, although they can work together for higher availability of VM. In addition, they can combine with software rejuvenation mechanisms for even higher availability; (4) and time interval setting is critical to a time-based rejuvenation mechanism. These analytic results provide guidelines for deploying and parameter setting of HA techniques in a virtualized system

A template-based methodology for the specification and automated composition of performability models

Dependability and performance analysis of modern systems is facing great challenges: their scale is growing, they are becoming massively distributed, interconnected, and evolving. Such complexity makes model-based assessment a difficult and time-consuming task. For the evaluation of large systems, reusable submodels are typically adopted as an effective way to address the complexity and to improve the maintainability of models. When using state-based models, a common approach is to define libraries of generic submodels, and then compose concrete instances by state sharing, following predefined “patterns” that depend on the class of systems being modeled. However, such composition patterns are rarely formalized, or not even documented at all. In this paper, we address this problem using a model-driven approach, which combines a language to specify reusable submodels and composition patterns, and an automated composition algorithm. Clearly defining libraries of reusable submodels, together with patterns for their composition, allows complex models to be automatically assembled, based on a high-level description of the scenario to be evaluated. This paper provides a solution to this problem focusing on: formally defining the concept of model templates, defining a specification language for model templates, defining an automated instantiation and composition algorithm, and applying the approach to a case study of a large-scale distributed system69129330

Availability of CAUTRA, a Subset of the French Air Traffic Control System

International audienceThe aim of our work is to provide a quantified means helping in the definition of a new architecture for CAUTRA, a subset of the French Air Traffic Control system. In this paper we define a set of alternative architectures, give some elements for constructing their dependability models and compare their availability. Modeling is carried out following a modular and systematic approach, based on the derivation of block models at a high level of abstraction. In a second step, the blocks are replaced by their equivalent Generalized Stochastic Petri Nets to build up the detailed model of the architecture. The evaluations performed permit identification of a subset of architectures whose availability meets the dependability requirements and also identification of the best architecture among this subset

Dependability modeling and evaluation – From AADL to stochastic Petri nets

Conduire des analyses de sûreté de fonctionnement conjointement avec d'autres analyses au niveau architectural permet à la fois de prédire les effets des décisions architecturales sur la sûreté de fonctionnement du système et de faire des compromis. Par conséquent, les industriels et les universitaires se concentrent sur la définition d'approches d'ingénierie guidées par des modèles (MDE) et sur l'intégration de diverses analyses dans le processus de développement. AADL (Architecture Analysis and Design Language) a prouvé son aptitude pour la modélisation d'architectures et ce langage est actuellement jugé efficace par les industriels dans de telles approches. Notre contribution est un cadre de modélisation permettant la génération de modèles analytiques de sûreté de fonctionnement à partir de modèles AADL dans l‘objectif de faciliter l'évaluation de mesures de sûreté de fonctionnement comme la fiabilité et la disponibilité. Nous proposons une approche itérative de modélisation. Dans ce contexte, nous fournissons un ensemble de sous-modèles génériques réutilisables pour des architectures tolérantes aux fautes. Le modèle AADL de sûreté de fonctionnement est transformé en un RdPSG (Réseau de Petri Stochastique Généralisé) en appliquant des règles de transformation de modèle. Nous avons implémenté un outil de transformation automatique. Le RdPSG résultant peut être traité par des outils existants pour obtenir des mesures de sûreté de fonctionnement. L'approche est illustrée sur un ensemble du Système Informatique Français de Contrôle de Trafic Aérien. ABSTRACT : Performing dependability evaluation along with other analyses at architectural level allows both predicting the effects of architectural decisions on the dependability of a system and making tradeoffs. Thus, both industry and academia focus on defining model driven engineering (MDE) approaches and on integrating several analyses in the development process. AADL (Architecture Analysis and Design Language) has proved to be efficient for architectural modeling and is considered by industry in the context presented above. Our contribution is a modeling framework allowing the generation of dependability-oriented analytical models from AADL models, to facilitate the evaluation of dependability measures, such as reliability or availability. We propose an iterative approach for system dependability modeling using AADL. In this context, we also provide a set of reusable modeling patterns for fault tolerant architectures. The AADL dependability model is transformed into a GSPN (Generalized Stochastic Petri Net) by applying model transformation rules. We have implemented an automatic model transformation tool. The resulting GSPN can be processed by existing tools to obtain dependability measures. The modeling approach is illustrated on a subsystem of the French Air trafic Control System