Toward Sensor and Software Product Line Based Context Aware Cloud Environment Assignment

TL;DR

This paper proposes a framework for developing context-aware cloud applications using sensor and software product line engineering, employing feature models and algorithms to adapt services based on sensed context.

Contribution

It introduces a novel approach combining product line engineering with context reasoning for adaptive cloud applications, enhancing flexibility and performance.

Findings

Feature models effectively represent context information and service configurations.

The CSCAFM algorithm generates context-aware services meeting performance requirements.

The approach improves adaptability of mobile cloud applications to user context.

Abstract

Because of the growing interest for mobile device and pervasive applications deployed on cloud computing, the providing of intelligent and ubiquitous context-aware applications that take into account the user's context is one of the main challenges in future applications. In this article we consider how to augment applications aware context used by mobiles device and deployed on cloud computing. The behavior of these applications should depend not only on their internal state and user interactions but also on the context sensed during their execution. Indeed, our approach based on two essential mechanisms, context sensoring and context reasoning. We consider the information acquired by the context sensoring as a product line and we use feature models to represent this information received, the services provided by cloud provider, the available resources and constraints. At the context reasoning step, the context provisioning feature model (CSCAFM) algorithm permits to generate service context-aware that fulfils the requirements of use ensures a certain level of performance of resources.