Ambient Intelligence (AmI) joins together the fields of ubiquitous computing and communications, context awareness, and\r\nintelligent user interfaces. Energy, fault-tolerance, and mobility are newly added dimensions of AmI.Within the context of AmI the\r\nconcept of mobile ad hoc networks (MANETs) for ââ?¬Å?anytime and anywhereââ?¬Â is likely to play larger roles in the future in which people\r\nare surrounded and supported by small context-aware, cooperative, and nonobtrusive devices that will aid our everyday life. The\r\nconnection between knowledge generation and communication ad hoc networking is symbioticââ?¬â?knowledge generation utilizes\r\nad hoc networking to perform their communication needs, and MANETs will utilize the knowledge generation to enhance their\r\nnetwork services. The contribution of the present study is a distributed evolving fuzzy modeling framework (EFMF) to observe and\r\ncategorize relationships and activities in the user and application level and based on that social context to take intelligent decisions\r\nabout MANETs service management. EFMF employs unsupervised online one-pass fuzzy clustering method to recognize nodesââ?¬â?¢\r\nmobility context from social scenario traces and ubiquitously learn ââ?¬Å?friendsââ?¬Â and ââ?¬Å?strangersââ?¬Â indirectly and anonymously.
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