Modelling Constrained Dynamic Software Architecture with Attributed Graph Rewriting Systems

Dynamic software architectures are studied for handling adap- tation in distributed systems, coping with new requirements, new envi- ronments, and failures. Graph rewriting systems have shown their ap- propriateness to model such architectures, particularly while considering the consistency of theirs reconfigurations. They provide generic formal means to specify structural properties, but imply a poor description of specific issues like behavioural properties. This paper lifts this limita- tion by proposing a formal approach for integrating the consideration of constraints, non-trivial attributes, and their propagation within the framework of graph rewriting systems

Uso racional de medicamentos

Ao longo das três unidades deste módulo, teremos um panorama do uso racional de medicamentos, a partir de sua definição, até sua compreensão como objetivo difícil de ser alcançado pelos profissionais da Saúde. Ademais, conheceremos as barreiras para o URM e as maneiras de enfrentá-las, e vimos como a prescrição e a dispensação de medicamentos são relevantes para favorecer seu uso racional. Por fim, compreenderemos como sua atuação profissional pode contribuir para um melhor uso dos medicamentos e, portanto, a uma melhor qualidade de vida dos usuários.1.0Ministério da Saúde/OPAS/OM

Practical use of a risk assessment model for complications after cardiac surgery

FUNDAMENTO: Identificar os fatores de risco para complicações pós-operatórias do paciente cardiopata com indicação cirúrgica que podem influenciar na decisão sobre a conduta terapêutica. OBJETIVO: Descrever a experiência de um hospital de Cardiologia na validação e uso prático de um escore de risco pré-operatório. MÉTODOS: Para validação do escore escolhido (Tuman), avaliaram-se consecutiva e prospectivamente 300 pacientes adultos antes da cirurgia cardíaca eletiva com o uso de circulação extracorpórea (CEC). Pacientes com escore de 0 a 5 foram considerados de baixo risco; de 6 a 9 como risco moderado; e maior que 10, como alto risco para complicações cardíacas, infecciosas, neurológicas, pulmonares e renais, além de óbito. RESULTADOS: A classificação de Tuman mostrou relação estatisticamente significante com ocorrência de complicações infecciosas (p=0,010), com outras complicações pós-operatórias (p=0,034) e com evolução para óbito (p<0,001). Infecção pulmonar foi a mais freqüente dentre as complicações infecciosas (15,3%), Os pacientes infectados tiveram maior tempo de permanência na UTI (p=0,001) e internação mais prolongada (p=0,001). Após o uso rotineiro, uma nova avaliação de 154 pacientes operados em 2005 confirmou a validade desse escore na identificação daqueles com maior risco de infecções pós-operatórias. CONCLUSÃO: Escolheu-se o escore de Tuman por envolver variáveis de fácil obtenção, por classificar no mesmo sistema as cirurgias mais freqüentemente realizadas e prever risco de complicações pós-operatórias, além da mortalidade. Seu uso continuado nesse hospital permitiu identificar o grupo de pacientes com maior risco de complicações, especialmente as infecciosas, mas não foi preciso na predição do risco individual.BACKGROUND: The identification of risk factors for postoperative complications in cardiac patients with surgical indication may influence the therapeutic decision. OBJECTIVE: To describe the experience of a Cardiology hospital in the validation and practical use of a preoperative risk score. METHODS:To validate TUMAN's score, chosen by considering morbidity and mortality, 300 adult patients were prospectively evaluated before elective cardiac surgery with the use of extracorporeal circulation (ECC). Patients with a score of zero to five were considered as being low risk; from six to nine, as moderate risk and a score higher than 10 as high risk for cardiac, infectious, neurological, pulmonary and renal complications, as well as death. RESULTS: The TUMAN classification showed a statistically significant association with the occurrence of infectious complications (p = 0.010), with the other postoperative complications (p = 0.034) and death (p <0.001). Pulmonary infection was the most frequent infectious complication (15.3%) and Infected patients had a longer ICU stay duration (p = 0.001) and more prolonged hospitalization (p = 0001). After routine use, a new review of 154 patients operated in 2005, confirmed the validity of this score in the identification of those with the highest risk of postoperative infections. CONCLUSION: TUMAN's score was chosen as it uses variables that can be promptly obtained, classifies in the same system the most frequently performed surgeries and predicts risk of postoperative complications, in addition to mortality. Its continued use in this hospital has been able to identify the group of patients with increased risk of complications, especially infectious ones, although it was not useful in the prediction of individual risk

Correctness by Construction and Style Preserving Reconfigurations of Distributed Systems.

In distributed systems and dynamic environments, software architectures may evolve. A crucial issue when conducting system evolutions is to maintain the system in a consistent and functional state. Based on formal proofs in design-time, correctness by construction has recently emerged to efficiently guarantee system coherency. This article proposes a new method for the construction and specification of correct by construction system reconfigurations. Such transformations are characterized by graph rewriting rules that necessarily preserve the coherency of a system. We firstly propose operators on graph transformations and show that they conserve their correctness. Given a system specified by a graph grammar, these operators then serve to construct and characterize a set of correct transformations. We show in particular that any correct configuration can be reached starting from any other one without inconsistent intermediate step, using these transformations only

Energy-efficient and thermal-aware resource management for heterogeneous datacenters

International audienceWe propose in this paper to study the energy-, thermal- and performance-aware resource management in heterogeneous datacenters. Witnessing the continuous development of heterogeneity in datacenters, we are confronted with their different behaviors in terms of performance, power consumption and thermal dissipation: indeed, heterogeneity at server level lies both in the computing infrastructure (computing power, electrical power consumption) and in the heat removal systems (different enclosure, fans, thermal sinks). Also the physical locations of the servers become important with heterogeneity since some servers can (over)heat others. While many studies address independently these parameters (most of the time performance and power or energy), we show in this paper the necessity to tackle all these aspects for an optimal resource management of the computing resources. This leads to improved energy usage in a heterogeneous datacenter including the cooling of the computer rooms. We build our approach on the concept of heat distribution matrix to handle the mutual influence of the servers, in heterogeneous environments, which is novel in this context. We propose a heuristic to solve the server placement problem and we design a generic greedy framework for the online scheduling problem. We derive several single-objective heuristics (for performance, energy, cooling) and a novel fuzzy-based priority mechanism to handle their tradeoffs. Finally, we show results using extensive simulations fed with actual measurements on heterogeneous servers

Exploiting Performance Counters to Predict and Improve Energy Performance of HPC Systems

International audienceHardware monitoring through performance counters is available on almost all modern processors. Although these counters are originally designed for performance tuning, they have also been used for evaluating power consumption. We propose two approaches for modelling and understanding the behaviour of high performance computing (HPC) systems relying on hardware monitoring counters. We evaluate the effectiveness of our system modelling approach considering both optimising the energy usage of HPC systems and predicting HPC applications' energy consumption as target objectives. Although hardware monitoring counters are used for modelling the system, other methods -- including partial phase recognition and cross platform energy prediction -- are used for energy optimisation and prediction. Experimental results for energy prediction demonstrate that we can accurately predict the peak energy consumption of an application on a target platform; whereas, results for energy optimisation indicate that with no a priori knowledge of workloads sharing the platform we can save up to 24\% of the overall HPC system's energy consumption under benchmarks and real-life workloads

Self-management of machine-to-machine communications: a multi-models approach

International audienceMachine-to-Machine (M2M) paradigm apply to systems composed by numerous devices sharing information and making cooperative decisions with little or no human intervention. The M2M standard defined by the European Telecommunications Standards Institute (ETSI) is the only one providing an end-to-end view of the global M2M architecture. Noticeably, it furnishes a standardised framework for inter-operable M2M services that satisfies most of M2M modelling requirements. However, and even though M2M systems usually operate in highly evolving contexts, this standard does not address the issue of system adaptations. It is furthermore unsuitable for building self-managed systems. This paper introduces a multi-model approach for modelling manageable M2M systems. Said approach consists in a formal graph-based model on top of the ETSI M2M standard, alongside bi-directional updates that ensure layer coherency. Its fitness for enforcing self-management properties is demonstrated by designing high-level reconfiguration rules. Finally, its applicability is illustrated and evaluated using a smart-metering application

Beyond CPU Frequency Scaling for a Fine-grained Energy Control of HPC Systems

International audienceModern high performance computing subsystems (HPC) - including processor, network, memory, and IO - are provided with power management mechanisms. These include dynamic speed scaling and dynamic resource sleeping. Understanding the behavioral patterns of high performance computing systems at runtime can lead to a multitude of optimization opportunities including controlling and limiting their energy usage. In this paper, we present a general purpose methodology for optimizing energy performance of HPC systems consid- ering processor, disk and network. We rely on the concept of execution vector along with a partial phase recognition technique for on-the-fly dynamic management without any a priori knowledge of the workload. We demonstrate the effectiveness of our management policy under two real-life workloads. Experimental results show that our management policy in comparison with baseline unmanaged execution saves up to 24% of energy with less than 4% performance overhead for our real-life workloads

Software architectures: multi-scale refinement

We propose a multi-scale modeling approach for complex software system architecture description. The multi-scale description may help to obtain meaningful granularities of these systems and to understand and master their complexity. This vision enables an architect designer to express constraints concerning different description levels, oriented to facilitate adaptability management. We define a correct-by-design approach that allows a given abstract architectural description to be refined into architecture models. We follow a progressive refinement process based on model transformations; it begins with a coarse-grain description and ends with a fine-grain description that specifies design details. The adaptability property management is performed through model transformation operations. The model transformation ensures the correctness of UML description, and the correctness of the modeled system. We experimented our approach with a use case that models a smart home system for the monitoring of elderly and disabled persons at home