Generic context adaptation for mobile cloud computing environments

  • Gabriel OrsiniEmail author
  • Dirk Bade
  • Winfried Lamersdorf
Original Research


Markets for mobile applications offer myriads of apps ranging from simple to quite demanding ones. The latter are on the rise since every new generation of smartphones is equipped with more resources (CPU, memory, bandwidth, energy) to even allow re-source-demanding services like speech- or face recognition to be executed locally on a device. But compared to their stationary counterparts, mobile devices remain comparatively limited in terms of resources. Because of this, current approaches aim at extending mobile device capabilities with computation and storage resources offered by cloud services or other nearby devices. This paradigm, known as mobile cloud computing (MCC), is challenged by the dynamically changing context of mobile devices, which developers are required to take into account to decide, e.g., which application parts are when to offload. To rise to such and similar challenges we introduce the concept of Generic Context Adaptation (GCA), a data mining process that facilitates the adaptation of (mobile) applications to their current and future context. Moreover, we evaluate our approach with real usage data provided by the Nokia Mobile Data Challenge (MDC) as well as with CloudAware, a context-adaptive mobile middleware for MCC that supports automated and context-aware self-adaptation techniques.


Mobile cloud computing Mobile edge computing Context adaptation Context awareness 



Parts of the research in this paper used the MDC Database made available by Idiap Research Institute, Switzerland and owned by Nokia.


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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Gabriel Orsini
    • 1
    Email author
  • Dirk Bade
    • 1
  • Winfried Lamersdorf
    • 1
  1. 1.Distributed Systems Group, Department of Computer ScienceUniversity of HamburgHamburgGermany

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