Deploying on the Grid with DeployWare

In Proceedings of the 8th IEEE International Symposium on Cluster Computing and the Grid (TO APPEAR)International audienceIn this paper, we present DeployWare to address the deployment of distributed and heterogeneous software systems on large scale infrastructures such as grids. Deployment of software systems on grids raises many challenges like 1) the complexity to take into account orchestration of all the deployment tasks and management of software dependencies, 2) the heterogeneity of both physical infrastructures and software composing the system to deploy, 3) the validation to early detect errors before concrete deployments and 4) scalability to tackle thousands of nodes. To address these challenges, DeployWare provides a metamodel that abstracts concepts of the deployment, a virtual machine that executes deployment processes on grids from DeployWare descriptions, and a graphical console that allows to manage deployed systems, at runtime. To validate our approach, we have experimented DeployWare with a lot of software technologies, such as CORBA and SOA-based systems, on one thousand of nodes of Grid'5000, the french experimental grid infrastructure

Deploying on the Grid with DeployWare

In Proceedings of the 8th IEEE International Symposium on Cluster Computing and the Grid (TO APPEAR)International audienceIn this paper, we present DeployWare to address the deployment of distributed and heterogeneous software systems on large scale infrastructures such as grids. Deployment of software systems on grids raises many challenges like 1) the complexity to take into account orchestration of all the deployment tasks and management of software dependencies, 2) the heterogeneity of both physical infrastructures and software composing the system to deploy, 3) the validation to early detect errors before concrete deployments and 4) scalability to tackle thousands of nodes. To address these challenges, DeployWare provides a metamodel that abstracts concepts of the deployment, a virtual machine that executes deployment processes on grids from DeployWare descriptions, and a graphical console that allows to manage deployed systems, at runtime. To validate our approach, we have experimented DeployWare with a lot of software technologies, such as CORBA and SOA-based systems, on one thousand of nodes of Grid'5000, the french experimental grid infrastructure

Enabling Context-Aware Web Services: A Middleware Approach for Ubiquitous Environments

In ubiquitous environments, mobile applications should sense and react to environmental changes to provide a better user experience. In order to deal with these concerns, Service-Oriented Architectures (SOA) provide a solution allowing applications to interact with the services available in their surroundings. In particular, context-aware Web Services can adapt their behavior considering the user context. However, the limited resources of mobile devices restrict the adaptation degree. Furthermore, the diverse nature of context information makes difficult its retrieval, processing and distribution. To tackle these challenges, we present the CAPPUCINO platform for executing context-aware Web Services in ubiquitous environments. In particular, in this chapter we focus on the middleware part that is built as an autonomic control loop that deals with dynamic adaptation. In this autonomic loop we use FraSCAti, an implementation of the Service Component Architecture (SCA) specification, as the execution kernel for Web Services. The context distribution is achieved with SPACES, a flexible solution based on REST (REpresentational State Transfer ) principles and benefiting from the COSMOS (COntext entitieS coMpositiOn and Sharing ) context manage- ment framework. The application of our platform is illustrated with a mobile commerce application scenario that combines context-aware Web Services and social networks

Towards Model-Driven Validation of Autonomic Software Systems in Open Distributed Environments

New distributed systems are running onto fluctuating environments (e.g. ambient or grid computing). These fluctuations must be taken into account when deploying these systems. Autonomic computing aims at realizing programs that implement self-adaptation behaviour. Unfortunately in practice, these programs are not often statically validated, and their execution can lead to emergent undesirable behaviour. In this paper, we argue that static validation is mandatory for large autonomic distributed systems. We identify two kinds of validation that are relevant and crucial when deploying such systems. These validations affect the deployment procedures of software composing a system, as well as the autonomic policies of this system. Using our Dacar model-based framework for deploying autonomic software distributed architectures, we show how we tackle the problem of static validation of autonomic distributed system

Experimentations With CoRDAGe, A Generic Service For Co-Deploying and Re-Deploying Applications On Grids

Computer grids are made of thousands of heterogeneous physical resources that belong to different administration domains. This makes the use of the grid very complex. In this paper, we focus on deploying distributed applications at a large scale. As the application requirements may often not be anticipated, dynamic re-deployment is needed; if various applications have to co-operate within a workflow, they should also be co-deployed in a consistent way. In a previous paper, we have described the CORDAGE deployment model and its architecture. It meets the three properties of transparency, versatility, and neutrality. We report in this paper on its application to a real co-deployment over the GRID'5000 experimental platform, using different configurations, including multiple clients, multiple applications and multiple grid sites

Enabling Context-Aware Web Services: A Middleware Approach for Ubiquitous Environments

In ubiquitous environments, mobile applications should sense and react to environmental changes to provide a better user experience. In order to deal with these concerns, Service-Oriented Architectures (SOA) provide a solution allowing applications to interact with the services available in their surroundings. In particular, context-aware Web Services can adapt their behavior considering the user context. However, the limited resources of mobile devices restrict the adaptation degree. Furthermore, the diverse nature of context information makes difficult its retrieval, processing and distribution. To tackle these challenges, we present the CAPPUCINO platform for executing context-aware Web Services in ubiquitous environments. In particular, in this chapter we focus on the middleware part that is built as an autonomic control loop that deals with dynamic adaptation. In this autonomic loop we use FraSCAti, an implementation of the Service Component Architecture (SCA) specification, as the execution kernel for Web Services. The context distribution is achieved with SPACES, a flexible solution based on REST (REpresentational State Transfer ) principles and benefiting from the COSMOS (COntext entitieS coMpositiOn and Sharing ) context manage- ment framework. The application of our platform is illustrated with a mobile commerce application scenario that combines context-aware Web Services and social networks

Autonimic energy-aware task scheduling

International audienceThe increasing processing capability of data-centers increases considerably their energy consumption which leads to important losses for companies. Energy-aware task scheduling is a new challenge to optimize the use of the computation power provided by multiple resources. In the context of Cloud resources usage depends on users requests which are generally unpredictable. Autonomic computing paradigm provides systems with self-managing capabilities helping to react to unstable situation. This article proposes an autonomic approach to provide energy-aware scheduling tasks. The generic autonomic computing framework FrameSelf coupled with the CloudSim energy-aware simulator is presented. The proposed solution enables to detect critical schedule situations and simulate new placements for tasks on DVFS enabled hosts in order to improve the global energy efficiency