MICE: Monitoring and ModelIng the Context Evolution

Context is an application-specific set of heterogeneous data that a context-aware system should be capable to sense to accordingly adapt its behavior. Context evolution may affect the qualities of the functionalities provided by context-aware systems, in terms of variations of its non-functional properties. In this paper we propose a distributed tool that is capable to monitor, retrieve and arrange heterogeneous data from any IP-enabled device in a set of state-based awareness manager models. The latter are meant to model the context evolution and to be integrated in model-driven approaches to evaluate the impact of the evolution of context on the quality of the provisioned services.

[1]  Paola Inverardi,et al.  The Future of Software: Adaptation and Dependability , 2008, ISSSE.

[2]  Schahram Dustdar,et al.  COPAL: An adaptive approach to context provisioning , 2010, 2010 IEEE 6th International Conference on Wireless and Mobile Computing, Networking and Communications.

[3]  Vittorio Cortellessa,et al.  A Unified Approach to Model Non-Functional Properties of Mobile Context-Aware Software , 2009, NFPinDSML@MoDELS.

[4]  Marius Mikalsen,et al.  Distributed context management in a mobility and adaptation enabling middleware (MADAM) , 2006, SAC '06.

[5]  Cecilia Mascolo,et al.  Reflective Middleware Solutions for Context-Aware Applications , 2001, Reflection.

[6]  Vittorio Cortellessa,et al.  Performance Modeling and Analysis of Context-Aware Mobile Software Systems , 2010, FASE.

[7]  David Harel,et al.  Statecharts: A Visual Formalism for Complex Systems , 1987, Sci. Comput. Program..

[8]  Cecilia Mascolo,et al.  CARISMA: Context-Aware Reflective mIddleware System for Mobile Applications , 2003, IEEE Trans. Software Eng..

[9]  Frank Eliassen,et al.  Service Plans for Context- and QoS-aware Dynamic Middleware , 2006, 26th IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW'06).

[10]  Gordon S. Blair,et al.  A reflective framework for discovery and interaction in heterogeneous mobile environments , 2005, MOCO.

[11]  Jadwiga Indulska,et al.  A survey of context modelling and reasoning techniques , 2010, Pervasive Mob. Comput..

[12]  Nelly Bencomo,et al.  Supporting the modelling and generation of reflective middleware families and applications using dynamic variability , 2008 .

[13]  Mary Shaw,et al.  Software Engineering for Self-Adaptive Systems: A Research Roadmap , 2009, Software Engineering for Self-Adaptive Systems.