A Characterization Framework for Software Deployment Technologies

Carzaniga, Antonio; Fuggetta, Alfonso; Hall, Richard S.; Heimbigner, Dennis; Hoek, André van der; Wolf, Alexander L.

doi:10.21236/ada452086

Cited by 105 publications

(81 citation statements)

References 8 publications

(9 reference statements)

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“…Software deployment is defined in [2] as being a process composed of several phases as follows: release, installation, activation, deactivation, adaptation, update, uninstall and retire. Let classify the application deployment approaches using the following criteria, (i) the deployment target either distributed or local and (ii) the deployment constraints.…”

Section: State Of the Art: Software Deployment Systemsmentioning

confidence: 99%

A Graph-Based Approach for Contextual Service Loading in Pervasive Environments

Hamida

Mouël

Frénot

et al. 2008

On the Move to Meaningful Internet Systems: OTM 2008

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Abstract. The pervasive computing paradigm promises great abilities whenever and wherever a user goes. However, as people are shifting from the desktop to more resource-constrained devices, issues due to scarce resources may appear preventing from the use of the available services and applications. In this paper, we consider the adaptive deployment as a mainstream solution to suit service-oriented applications to different context constraints such as the users requirements, the hosts resources, the services properties and the surrounding environments. We put forward a graph-based deployment approach for service-based applications so as to make these applications adaptable to the runtime contextual constraints. We introduce the AxSeL architecture, A conteXtual Service Loader in which services and their dependencies are represented as a bidimensional graph. The dependency graph is then coloured through a process taking into account the devices, services and users constraints. This process aims to choose to load or not a service according to its execution context. A prototype based on Java and OSGi technologies is implemented in order to demonstrate and evaluate our approach.

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Section: State Of the Art: Software Deployment Systemsmentioning

confidence: 99%

A Graph-Based Approach for Contextual Service Loading in Pervasive Environments

Hamida

Mouël

Frénot

et al. 2008

On the Move to Meaningful Internet Systems: OTM 2008

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“…Of these three component tools, only Nix focusses on variable features provided by different instantiations of components, and only Nix discusses the opportunities for a transparent configuration environment [10]. Software component developers often use their own specific deployment tools or custom build checks to see whether the system on which the component is deployed satisfies all requirements for consistent and correct deployment [11]. The developer therefore must develop its own models and formalisations to ensure a correct component deployment.…”

Section: Component Deployment Issuesmentioning

confidence: 99%

Modelling Deployment Using Feature Descriptions and State Models for Component-Based Software Product Families

Jansen

Brinkkemper

2005

Lecture Notes in Computer Science

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Abstract. Products within a product family are composed of different component configurations where components have different variable features and a large amount of dependency relationships with each other. The deployment of such products can be error prone and highly complex if the dependencies between components and the possible features a component can supply are not managed explicitly. This paper presents a method that uses the knowledge available about components to ensure correct, complete, and consistent deployment of configurations of interrelated components. The method provided allows the user to perform analysis on the deployment before the deployment is performed, thus allowing error prevention before making any changes to the system. The method and model are discussed and presented to provide an alternative to current component deployment techniques.

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“…The goal is to find a valid deployment f such that the system's availability is maximized. 1 In the most general case, the number of possible deployments is k n . However, some of these deployments may be invalid (i.e., they may not satisfy the required constraints).…”

Section: Problem and Approachmentioning

confidence: 99%

“…Our approach, illustrated in Figure 2, employs runtime redeployment to increase a system's availability by (1) monitoring the system, (2) visualizing, estimating, and analyzing its redeployment architecture, and (3) effecting the selected redeployment architecture. We leverage an architectural middleware, Prism-MW, to support runtime system monitoring.…”

Section: Problem and Approachmentioning

confidence: 99%