An architecture for context-aware adaptive data stream mining

P. Haghighi, M. Gaber, S. Krishnaswamy, A. Zaslavsky

Research output: Contribution to conferencePaperpeer-review

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Abstract

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 adaptation, as a new dimension of research in data stream mining, enhances and optimizes 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 data stream mining parameters according to changes in context and resource availability in distributed and heterogeneous computing environments.
Original languageEnglish
Publication statusPublished - 17 Sep 2007
EventProceedings of the International Workshop on Knowledge Discovery from Ubiquitous Data Streams (IWKDUDS07) - Warsaw, Poland
Duration: 17 Sep 2007 → …

Conference

ConferenceProceedings of the International Workshop on Knowledge Discovery from Ubiquitous Data Streams (IWKDUDS07)
CountryPoland
CityWarsaw
Period17/09/07 → …

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