Exploiting co-location history for efficient service selection in ubiquitous computing systems

Alexandros Karypidis, S. Lalis
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引用次数: 9

Abstract

As the ubiquitous computing vision materializes, the number and diversity of digital elements in our environment increases. Computing capability comes in various forms and is embedded in different physical objects, ranging from miniature devices such as human implants and tiny sensor particles, to large constructions such as vehicles and entire buildings. The number of possible interactions among such elements, some of which may be invisible or offer similar functionality, is growing fast so that it becomes increasingly hard to combine or select between them. Mechanisms are thus required for intelligent matchmaking that will achieve controlled system behavior, yet without requiring the user to continuously input desirable options in an explicit manner. In this paper we argue that information about the co-location relationship of computing elements is quite valuable in this respect and can be exploited to guide automated service selection with minimal or no user involvement. We also discuss the implementation of such mechanism that is part of our runtime system for smart objects.
利用共址历史进行普适计算系统中的高效服务选择
随着无处不在的计算视觉的实现,我们环境中数字元素的数量和多样性也在增加。计算能力以各种形式出现,并嵌入到不同的物理对象中,从人体植入物和微小传感器颗粒等微型设备到车辆和整个建筑物等大型结构。这些元素之间可能的相互作用的数量正在迅速增加,其中一些可能是不可见的或提供类似的功能,因此在它们之间进行组合或选择变得越来越困难。因此,智能配对机制需要实现控制系统行为,但不需要用户以明确的方式连续输入所需选项。在本文中,我们认为关于计算元素的共定位关系的信息在这方面是非常有价值的,并且可以用于指导自动化服务选择,而无需用户参与。我们还讨论了这种机制的实现,它是智能对象运行时系统的一部分。
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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