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Exploiting Mobile Ad Hoc Networking and Knowledge Generation to Achieve Ambient Intelligence

机译:利用移动自组织网络和知识生成来实现环境智能

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摘要

Ambient Intelligence (AmI) joins together the fields of ubiquitous computing and communications, context awareness, and intelligent user interfaces. Energy, fault-tolerance, and mobility are newly added dimensions of AmI. Within the context of AmI the concept of mobile ad hoc networks (MANETs) for “anytime and anywhere” is likely to play larger roles in the future in which people are surrounded and supported by small context-aware, cooperative, and nonobtrusive devices that will aid our everyday life. The connection between knowledge generation and communication ad hoc networking is symbiotic—knowledge generation utilizes ad hoc networking to perform their communication needs, and MANETs will utilize the knowledge generation to enhance their network services. The contribution of the present study is a distributed evolving fuzzy modeling framework (EFMF) to observe and categorize relationships and activities in the user and application level and based on that social context to take intelligent decisions about MANETs service management. EFMF employs unsupervised online one-pass fuzzy clustering method to recognize nodes' mobility context from social scenario traces and ubiquitously learn “friends” and “strangers” indirectly and anonymously.
机译:环境智能(AmI)将无处不在的计算和通信,上下文感知和智能用户界面等领域结合在一起。能源,容错和移动性是AmI的新增功能。在AmI的背景下,面向“随时随地”的移动自组织网络(MANET)的概念在未来可能会发挥更大的作用,因为人们将被小型上下文感知,协作和非干扰性设备包围和支持,帮助我们的日常生活。知识生成与通信自组织网络之间的联系是共生的-知识生成利用自组织网络来满足其通信需求,而MANET将利用知识生成来增强其网络服务。本研究的贡献是一个分布式演化的模糊建模框架(EFMF),用于观察和分类用户和应用程序级别的关系和活动,并基于该社交环境对MANETs服务管理做出明智的决策。 EFMF采用无监督的在线一遍模糊聚类方法,从社交场景跟踪中识别节点的移动环境,并无处不在地以匿名方式学习“朋友”和“陌生人”。

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