Run-time Support to Manage Architectural Variability Speci ed with CVL

Abstract

The execution context in which pervasive systems or mobile computing run changes continuously. Hence, applications for these systems should be adapted at run-time according to the current context. In order to implement a context-aware dynamic reconfiguration service, most approaches usually require to model at design-time both the list of all possible configurations and the plans to switch among them. In this paper we present an alternative approach for the automatic run-time generation of application configurations and the reconfiguration plans. The generated configurations are optimal regarding di erent criteria, such as functionality or resource consumption (e.g. battery or memory). This is achieved by: (1) modelling architectural variability at design-time using Common Variability Language (CVL), and (2) using a genetic algorithm that finds at run-time nearly-optimal configurations using the information provided by the variability model. We also specify a case study and we use it to evaluate our approach, showing that it is efficient and suitable for devices with scarce resources.