Context-aware systems are able to sense and adapt to the environment. Mobile applications can benefit from context-awareness since they incur to context changes during their execution. A detailed understanding of the context is needed to know what a context-aware system should sense and adapt to. This paper introduces a statistical approach that helps in determining contextual situations that require adaptation. The approach starts from monitoring mobile context variables values, modeling their states, and deducing from these models a Markov chain model, where each state represents a contextual situation. Depending on transition probabilities and system quality at each state we can decide when it is necessary to apply context-awareness.

A statistical approach for context-awareness of mobile applications

Di Marco A.;Inverardi P.
2020

Abstract

Context-aware systems are able to sense and adapt to the environment. Mobile applications can benefit from context-awareness since they incur to context changes during their execution. A detailed understanding of the context is needed to know what a context-aware system should sense and adapt to. This paper introduces a statistical approach that helps in determining contextual situations that require adaptation. The approach starts from monitoring mobile context variables values, modeling their states, and deducing from these models a Markov chain model, where each state represents a contextual situation. Depending on transition probabilities and system quality at each state we can decide when it is necessary to apply context-awareness.
978-3-030-59154-0
978-3-030-59155-7
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11697/151247
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