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

Abstract

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.

Orthogonal Classification of Middleware Technologies

“…When executing an application over a device, it can happen that the device has no more resources to execute all the services of the application, this middleware can dynamically decide which service to unload from the application, and when the resources are available to upload the service. The approach is done spontaneously, without the user intervention and is based on a graph colouring techniques [2]. • Spontaneous substitution [11]: transparent substitution between services depending on QoS properties.…”

“…The interfaces are described syntactically but also semantically, which allows interoperability for the composition. • Spontaneous adaptation [2]: adapting the execution of applications to the platforms using graph based techniques. An application is a set of services connected together.…”

Components mobility for energy efficiency of digital home

“…First because "suitable" is defined according to the operational specifications, e.g., performance, security, availability, energy efficiency. Secondly, because to process large sets, planners are usually based on Artificial Intelligent (AI) techniques: graphs colouring [10], evolution algorithms [1], constraint solvers [8,5]. These planners consider the deployment of constrained components on various environments: network [8], datacenter [2], embedded systems [14] or even pervasive environments [12].…”

Kalimucho: Contextual Deployment for QoS Management

“…However none of these works tackle the problem of distributed deployment. Some works such as Carisma and AxSeL [3] provide contextual deployment solutions. As well as optimize resources consumption, they allow driving deployment according to physical and/or logical dependencies.…”