An Architecture for Context-Aware Adaptive Data Stream Mining

نویسندگان

  • Pari Delir Haghighi
  • Mohamed Medhat Gaber
  • Shonali Krishnaswamy
  • Arkady Zaslavsky
  • Seng Loke
چکیده

In resource-constrained devices, adaptation of data stream processing to variations of data rates, availability of resources and environment changes is crucial for consistency and continuity of running applications. Context-aware and resource-aware adaptation, as a new dimension of research in data stream mining, enhances and improves distributed data stream processing tasks. Context-awareness is one of the key aspects of ubiquitous computing as applications’ successful operations rely on detecting changes and adjusting accordingly. This paper presents a general architecture for context-aware adaptive mining of data streams that aims to dynamically and autonomously adjust input, output and algorithms of data stream mining according to changes in context and resource availability.

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تاریخ انتشار 2007