Experimental Analysis on Autonomic Strategies for Cloud Elasticity

International audienceIn spite of the indubitable advantages of elasticity in Cloud infrastructures, some technical and conceptual limitations are still to be considered. For instance , resource start up time is generally too long to react to unexpected workload spikes. Also, the billing cycles' granularity of existing pricing models may incur consumers to suffer from partial usage waste. We advocate that the software layer can take part in the elasticity process as the overhead of software reconfigurations can be usually considered negligible if compared to infrastructure one. Thanks to this extra level of elasticity, we are able to define cloud reconfigurations that enact elasticity in both software and infrastructure layers so as to meet demand changes while tackling those limitations. This paper presents an autonomic approach to manage cloud elasticity in a cross-layered manner. First, we enhance cloud elasticity with the software elasticity model. Then, we describe how our au-tonomic cloud elasticity model relies on dynamic selection of elasticity tactics. We present an experimental analysis of a subset of those elasticity tactics under different scenarios in order to provide insights on strategies that could drive the autonomic selection of the proper tactics to be applied

Logico-numerical Control for Software Components Reconfiguration

International audienceWe target the problem of the safe control of reconfigurations in component-based software systems, where strategies of adaptation to variations in both their environment and internal resource demands need to be enforced. In this context, the computing system involves software components that are subject to control decisions. We approach this problem under the angle of Discrete Event Systems (DES), involving properties on events observed during the execution (e.g., requests of computing tasks, work overload), and a state space representing different configurations such as activity or assemblies of components. We consider in particular the potential of applying novel logico-numerical control techniques to extend the expressivity of control models and objectives, thereby extending the application of DES in component-based software systems. We elaborate methodological guidelines for the application of logico-numerical control based on a case- study, and validate the result experimentally

Enabling Green Energy awareness in Interactive Cloud Application

International audienceWith the proliferation of Cloud computing, data centers have to urgently face energy consumption issues. Although recent efforts such as the integration of renewable energy to data centers or energy efficient techniques in (virtual) machines contribute to the reduction of carbon footprint, creating green energy awareness around Interactive Cloud Applications by smartly using the presence of green energy has not been yet addressed. By awareness, we mean the inherited capability of Software-as-a-Service applications to dynamically adapt with the availability of green energy and to reduce energy consumption while green energy is scarce or absent. In this paper, we present two application controllers based on different metrics (e.g., availability of green energy, response time, user experience level). Based on extensive experiments with a real application benchmark and workloads in Grid'5000, results suggest that providers revenue can be increased as high as 64%, while 13% brown energy can be reduced without deprovisioning any physical or virtual resources at IaaS layer and 17 fold increment of performance can be guaranteed

SIMULA - Ambiente de Simulação em Sistemas Multiagentes Reativos

Os sistemas multiagentes reativos são um tema de estudo da inteligência artificial distribuída e têm sido usados em pesquisas e estudos ligados a campos importantes de aplicação, gerando o desenvolvimento de sistemas não apenas para a área acadêmica, mas também para atender às necessidades do mercado industrial. Este trabalho apresenta a definição e a implementação de um protótipo de um ambiente de simulação que possibilita o desenvolvimento de aplicações em sistemas multiagentes reativos. Este ambiente tem a finalidade de facilitar a criação de tais aplicações com o uso de agentes, atingindo um resultado satisfatório. O ambiente definido é o SIMULA, que possibilita ao usuário criar suas aplicações através de elementos de uma interface gráfica. O usuário, na interação com o ambiente, determina os agentes envolvidos no problema e como eles agirão no processo de resolução do mesmo. Apresenta-se, inicialmente, uma visão geral da área, seguida de breve descrição de três modelos de sistemas multiagentes reativos, com um quadro comparativo dos mesmos. A seguir, descreve-se, como objetivo principal, a definição do ambiente proposto para o desenvolvimento de aplicações baseadas neste paradigma, estabelecendo uma comparação com dois outros ambientes existentes.V Workshop sobre Aspectos Teóricos de la Inteligencia Artificial (ATIA)Red de Universidades con Carreras en Informática (RedUNCI

SIMULA - Ambiente de Simulação em Sistemas Multiagentes Reativos

Os sistemas multiagentes reativos são um tema de estudo da inteligência artificial distribuída e têm sido usados em pesquisas e estudos ligados a campos importantes de aplicação, gerando o desenvolvimento de sistemas não apenas para a área acadêmica, mas também para atender às necessidades do mercado industrial. Este trabalho apresenta a definição e a implementação de um protótipo de um ambiente de simulação que possibilita o desenvolvimento de aplicações em sistemas multiagentes reativos. Este ambiente tem a finalidade de facilitar a criação de tais aplicações com o uso de agentes, atingindo um resultado satisfatório. O ambiente definido é o SIMULA, que possibilita ao usuário criar suas aplicações através de elementos de uma interface gráfica. O usuário, na interação com o ambiente, determina os agentes envolvidos no problema e como eles agirão no processo de resolução do mesmo. Apresenta-se, inicialmente, uma visão geral da área, seguida de breve descrição de três modelos de sistemas multiagentes reativos, com um quadro comparativo dos mesmos. A seguir, descreve-se, como objetivo principal, a definição do ambiente proposto para o desenvolvimento de aplicações baseadas neste paradigma, estabelecendo uma comparação com dois outros ambientes existentes.V Workshop sobre Aspectos Teóricos de la Inteligencia Artificial (ATIA)Red de Universidades con Carreras en Informática (RedUNCI

Experimental Analysis on Autonomic Strategies for Cloud Elasticity

International audienceIn spite of the indubitable advantages of elasticity in Cloud infrastructures, some technical and conceptual limitations are still to be considered. For instance , resource start up time is generally too long to react to unexpected workload spikes. Also, the billing cycles' granularity of existing pricing models may incur consumers to suffer from partial usage waste. We advocate that the software layer can take part in the elasticity process as the overhead of software reconfigurations can be usually considered negligible if compared to infrastructure one. Thanks to this extra level of elasticity, we are able to define cloud reconfigurations that enact elasticity in both software and infrastructure layers so as to meet demand changes while tackling those limitations. This paper presents an autonomic approach to manage cloud elasticity in a cross-layered manner. First, we enhance cloud elasticity with the software elasticity model. Then, we describe how our au-tonomic cloud elasticity model relies on dynamic selection of elasticity tactics. We present an experimental analysis of a subset of those elasticity tactics under different scenarios in order to provide insights on strategies that could drive the autonomic selection of the proper tactics to be applied

High-level Language Support for the Control of Reconfigurations in Component-based Architectures

International audienceNowadays, smart home is extended beyond the house itself to encompass connected platforms on the Cloud as well as mobile personal devices. This Smart Home Extended Architecture (SHEA) helps customers to remain in touch with their home everywhere and any time. The endless increase of connected devices in the home and outside within the SHEA multiplies the deployment possibilities for any application. Therefore, SHEA should be taken from now as the actual target platform for smart home application deployment. Every home is different and applications offer different services according to customer preferences. To manage this variability, we extend the feature modeling from software product line domain with deployment constraints and we present an example of a model that could address this deployment challenge

Behavioural Model-based Control for Autonomic Software Components

International audienceAutonomic Managers (AMs) have been largely used to autonomously control reconfigurations within software compo- nents. This management is performed based on past monitoring events, configurations as well as behavioural programs defining the adaptation logics and invariant properties. The challenge here is to provide assurances on navigation through the configuration space, which requires taking decisions that involve predictions on possible futures of the system. This paper proposes the design of AMs based on logical discrete control approaches, where the use of behavioural models enriches the manager with a knowledge not only on events, states and past history, but also with possible future configurations. We define a Domain Specific Language, named Ctrl-F, which provides high-level constructs to describe behavioural programs in the context of software components. The formal definition of Ctrl-F is given by translation to Finite State Automata, which allow for the exploration of behavioural programs by verification or Discrete Controller Synthesis, automatically generating a controller enforcing correct behaviours. We implement an AM by integrating the result of Ctrl-F compilation and validate it with an adaptation scenario over Znn.com, a self-adaptive case study

A Model-based Architecture for Autonomic and Heterogeneous Cloud Systems

Best Paper AwardInternational audienceOver the last few years, Autonomic Computing has been a key enabler for Cloud system's dynamic adaptation. However, autonomously managing complex systems (such as in the Cloud context) is not trivial and may quickly become fastidious and error-prone. We advocate that Cloud artifacts, regardless of the layer carrying them, share many common characteristics. Thus, this makes it possible to specify, (re)configure and monitor them in an homogeneous way. To this end, we propose a generic model-based architecture for allowing the autonomic management of any Cloud system. From a " XaaS " model describing a given Cloud system, possibly over multiple layers of the Cloud stack, Cloud administrators can derive an autonomic manager for this system. This paper introduces the designed model-based architecture, and notably its core generic XaaS modeling language. It also describes the integration with a constraint solver to be used by the autonomic manager , as well as the interoperability with a Cloud standard (TOSCA). It presents an implementation (with its application on a multi-layer Cloud system) and compares the proposed approach with other existing solutions

Evaluation of water resources in a high-mountain basin in Serra da Estrela, Central Portugal, using a semi-distributed hydrological model

High-mountain basins provide a source of valuable water resources. This paper presents hydrological models for the evaluation of water resources in the highmountain Zezere river basin in Serra da Estrela, Central Portugal. Models are solved with VISUAL BALAN v2.0, a code which performs daily water balances in the root zone, the unsaturated zone and the aquifer and requires a small number of parameters. A lumped hydrological model failsto fit measured stream flows. Its limitations are overcome by considering the dependence of the temperature and precipitation data with elevation and the spatial variability in hydrogeomorphological variables with nine sub-basins of uniform parameters. Model parameters are calibrated by fitting stream flow measurements in the Zezere river. Computed stream flows are highly sensitive to soil thickness, whereas computed groundwater recharge is most sensitive to the interflow and percolation recession coefficients. Interflow is the main component of total runoff, ranging from 41 to 55% of annual precipitation. High interflows are favored by the steep relief of the basin, by the presence of a high permeability soil overlying the fractured low permeability granitic bedrock and by the extensive subhorizontal fracturing at shallow depths. Mean annual groundwater recharge ranges from 11 to 15% of annual precipitation. It has a significant uncertainty due to uncertainties in soil parameters. This methodology proves to be useful to handle the research difficulties regarding a complex mountain basin in a context of data scarcity.info:eu-repo/semantics/publishedVersio