Model-Based Availability Evaluation of Composed Web Services, Journal of Telecommunications and Information Technology, 2014, nr 4

Web services composition is an emerging software development paradigm for the implementation of distributed computing systems, the impact of which is very relevant both in research and industry. When a complex functionality has to be delivered on the Internet, a service integrator can produce added value by delivering more abstract and complex services obtained by composition of existing ones. But while isolated services availability can be improved by tuning and reconguring their hosting servers, with Composed Web Services (CWS) basic services must be taken as they are. In this case, it is necessary to evaluate the composition effects. The authors propose a high-level analysis methodology, supported by a tool, based on the transformation of BPEL descriptions of CWS into models based on the fault tree availability evaluation formalism that enables a modeler, unfamiliar with the underlying combinatorial probabilistic mathematics, to evaluate the availability of CWS, given components availability and expected execution behavior

Reliability -aware optimal checkpoint /restart model in high performance computing

Computational power demand for large challenging problems has increasingly driven the physical size of High Performance Computing (HPC) systems. As the system gets larger, it requires more and more components (processor, memory, disk, switch, power supply and so on). Thus, challenges arise in handling reliability of such large-scale systems. In order to minimize the performance loss due to unexpected failures, fault tolerant mechanisms are vital to sustain computational power in such environment. Checkpoint/restart is a common fault tolerant technique which has been widely applied in the single computer system. However, checkpointing in a large-scale HPC environment is much more challenging due to complexity, coordination, and timing issues. In this dissertation, we present a reliability-aware method for an optimal checkpoint/restart strategy. Our scheme aims to address the fault tolerance challenge, especially in a large-scale HPC system, by providing optimal checkpoint placement techniques derived from the actual system reliability. Unlike existing checkpoint models, which can only handle Poisson failure and a constant checkpoint interval, our model can perform a varying checkpoint interval and deal with different failure distributions. In addition, the approach considers optimality for both checkpoint overhead and rollback time. Our validation results suggest a significant improvement over existing techniques

Availability modeling and evaluation on high performance cluster computing systems

Cluster computing has been attracting more and more attention from both the industrial and the academic world for its enormous computing power, cost effective, and scalability. Beowulf type cluster, for example, is a typical High Performance Computing (HPC) cluster system. Availability, as a key attribute of the system, needs to be considered at the system design stage and monitored at mission time. Moreover, system monitoring is a must to help identify the defects and ensure the system\u27s availability requirement. In this study, novel solutions which provide availability modeling, model evaluation, and data analysis as a single framework have been investigated. Three key components in the investigation are availability modeling, model evaluation, and data analysis. The general availability concepts and modeling techniques are briefly reviewed. The system\u27s availability model is divided into submodels based upon their functionalities. Furthermore, an object oriented Markov model specification to facilitate availability modeling and runtime configuration has been developed. Numerical solutions for Markov models are examined, especially on the uniformization method. Alternative implementations of the method are discussed; particularly on analyzing the cost of an alternative solution for small state space model, and different ways for solving large sparse Markov models. The dissertation also presents a monitoring and data analysis framework, which is responsible for failure analysis and availability reconfiguration. In addition, the event logs provided from the Lawrence Livermore National Laboratory have been studied and applied to validate the proposed techniques

Stochastic models and dynamic measures for the characterization of bistable circuits

During the last few years, a great deal of interest has risen concerning the applications of stochastic methods to several biochemical and biological phenomena. Phenomena like gene expression, cellular memory, bet-hedging strategy in bacterial growth and many others, cannot be described by continuous stochastic models due to their intrinsic discreteness and randomness. In this thesis I have used the Chemical Master Equation (CME) technique to modelize some feedback cycles and analyzing their properties, including experimental data. In the first part of this work, the effect of stochastic stability is discussed on a toy model of the genetic switch that triggers the cellular division, which malfunctioning is known to be one of the hallmarks of cancer. The second system I have worked on is the so-called futile cycle, a closed cycle of two enzymatic reactions that adds and removes a chemical compound, called phosphate group, to a specific substrate. I have thus investigated how adding noise to the enzyme (that is usually in the order of few hundred molecules) modifies the probability of observing a specific number of phosphorylated substrate molecules, and confirmed theoretical predictions with numerical simulations. In the third part the results of the study of a chain of multiple phosphorylation-dephosphorylation cycles will be presented. We will discuss an approximation method for the exact solution in the bidimensional case and the relationship that this method has with the thermodynamic properties of the system, which is an open system far from equilibrium.In the last section the agreement between the theoretical prediction of the total protein quantity in a mouse cells population and the observed quantity will be shown, measured via fluorescence microscopy

Reliability and Performability Modeling using SHARPE 2000

The SHARPE package is now 13years old. Awell known package in the eld of reliability and performability, SHARPE is used in universities as well as in companies. Many important changes have been made during these years to improve the satisfaction of our users. Recently several new algorithms have been added and a Graphical User Interface has been implemented. This paper presents the current status of the tool.

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

Journal of Telecommunications and Information Technology, 2014, nr 4

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