A Research Roadmap for Context-Awareness-Based Self-managed Systems

  • Weishan Zhang
  • Klaus Marius Hansen
  • Paolo Bellavista
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7759)


Cloud computing, autonomic computing, pervasive and mobile computing tends to converge, maximizing the benefits from different computing paradigms. This convergence makes emerging applications such as search and rescue applications, smart city and smart planet applications, e.g., to minimize the power consumption of a full city to achieve green computing vision, more promising on the one hand, but more complex to manage on the other hand. Interesting research questions arise due to this convergence. For example, how to efficiently retrieve underlying contexts that are difficult to recognize especially with resource-limited handheld devices, how to make use of these contexts for achieving self-management, and how to process large-scale contexts. These challenges require that researchers from software engineering, artificial intelligence, pattern recognition, high-performance distributed systems, cloud and mobile computing, etc. collaborate in order to make systems work in an efficiently self-managed manner.


Cloud Computing Mobile Computing Smart City Pervasive Computing Mobile Cloud 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Weishan Zhang
    • 1
  • Klaus Marius Hansen
    • 2
  • Paolo Bellavista
    • 3
  1. 1.Department of Software EngineeringChina University of PetroleumQingdaoChina
  2. 2.Department of Computer Science (DIKU)University of CopenhagenCopenhagen SDenmark
  3. 3.DISIUniversity of BolognaBolognaItaly

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