Context discovery in sensor networks

Chia-Hsing Hou, Hung-Chang Hsiao, C. King, Chun-Nan Lu
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引用次数: 7

Abstract

Context discovery refers loosely to the operations of extraction, aggregation, storage and deduction of environmental information. Such information can be delivered to context-aware applications so that they can adapt their behavior according to the discovered contexts. Context information may be sensed and extracted by various sensors deployed freely in the environment These sensors must be interconnected to allow sensed data be collected. They are often heterogeneous with different sensing and computing capabilities to allow multimodal sensing. To help the interaction among the heterogeneous sensors in a context-aware environment, we need an efficient data-centric communication substrate on top of these sensors. The substrate must be self-organizing, self-tuning, and self-healing. It also needs to exploit the ad hoc interactions among heterogeneous sensors for energy conservation and operation efficiency. In this paper, we introduce such a substrate called TRAILBLAZER to enable the discovery of high-level contexts. We evaluate TRAILBLAZER via simulation. The results show that the communication among sensors is efficient in terms of the consumed energy when compared with an ideal solution and it is also fault-resilient.
传感器网络中的上下文发现
上下文发现泛指对环境信息进行提取、聚合、存储和演绎的操作。这样的信息可以传递给上下文感知的应用程序,以便它们可以根据发现的上下文调整自己的行为。环境信息可以通过在环境中自由部署的各种传感器来感知和提取,这些传感器必须相互连接才能收集感知到的数据。它们通常是异构的,具有不同的感知和计算能力,以允许多模态感知。为了帮助在上下文感知环境中异构传感器之间的交互,我们需要在这些传感器之上建立一个高效的以数据为中心的通信基板。基板必须是自组织、自调整和自修复的。它还需要利用异构传感器之间的特殊相互作用来节约能源和提高运行效率。在本文中,我们引入了这样一个称为TRAILBLAZER的基板来发现高级上下文。我们通过模拟来评估开拓者。结果表明,与理想方案相比,传感器之间的通信在能量消耗方面是有效的,并且具有容错性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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