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Design and implementation of a large-scale context fusion network

机译:大规模上下文融合网络的设计与实现

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摘要

We motivate a context fusion network (CFN), an infrastructure model that allows context-aware applications to select distributed data sources and compose them with customized data-fusion operators into a directed acyclic information fusion graph. Such a graph represents how an application computes high-level understandings of its execution context from low-level sensory data. Multiple graphs by different applications interconnect with each other to form a global graph. A key advantage of a CFN is reusability, both at code-level and instance-level, facilitated by operator composition. We designed and implemented a distributed CFN system, Solar, which maps the logical operator graph representation onto a set of overlay hosts. In particular, Solar meets the challenges inherent to heterogeneous and volatile ubicomp environments. By abstracting most complexities into the infrastructure, Solar facilitates both the development and deployment of context-aware applications. We present the operator composition model, basic services of the Solar overlay network, and programming support for the developers. We also discuss some applications built with Solar and the lessons we learned from our experience.
机译:我们激发了上下文融合网络(CFN),它是一种基础结构模型,它允许上下文感知的应用程序选择分布式数据源,并将它们与自定义的数据融合运算符组合成有向非循环信息融合图。这样的图形表示应用程序如何从低级感觉数据计算对其执行上下文的高级理解。不同应用程序的多个图彼此互连以形成全局图。 CFN的主要优势是在代码级和实例级的可重用性,并通过操作员的组合得以促进。我们设计并实现了分布式CFN系统Solar,该系统将逻辑运算符图表示形式映射到一组重叠主机上。特别是,Solar迎接了异构且易变的ubicomp环境固有的挑战。通过将最复杂的事物抽象到基础架构中,Solar促进了上下文感知应用程序的开发和部署。我们提供了运营商组成模型,Solar覆盖网络的基本服务以及对开发人员的编程支持。我们还将讨论一些使用Solar构建的应用程序以及从我们的经验中学到的教训。

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