An architecture for context-aware adaptive data stream mining
Pari Delir Haghighi, Mohamed Medhat Gaber, Shonali Priyadarsini Krishnaswamy, Arkady Zaslavsky · 2007
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 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. 1.