Making Mobile Users' Devices Aware of the Surrounding Physical Environment: An Approach Based on Cognitive Heuristics

M. Mordacchini, A. Passarella, M. Chorley, Gualtiero Colombo, Vlad Tanasescu
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引用次数: 4

Abstract

In this paper we investigate the properties of a cognitive heuristics based approach, by way of which the mobile devices of users can become aware of the physical environment surrounding them. Cognitive heuristics are the mental models used in cognitive psychology to describe how human brains efficiently process the huge amount of information constantly coming from the environment around us. As personal mobile devices represent proxies in the cyber world of their human users, we investigate how the same cognitive heuristics can be used by mobile devices to become self-aware of the features of the physical environment around their users. Specifically, we assume that physical locations are described as a network of tags. We consider a self-organising opportunistic network environment, where devices exchange information when meeting directly. We propose algorithms based on cognitive heuristics through which users' nodes obtain tags either directly when coming in proximity of locations, or indirectly through other nodes they meet. We analyse the properties of the networks of tags resulting at individual nodes, as they emerge from this process, as a function of various cognitive parameters. We show that using cognitive heuristics leads, under the same resource constraints, to much more effective information diffusion with respect to other reference solutions. Interestingly, we find critical thresholds for key parameters that discriminate between information diffusion and information loss. Finally, we show that, despite resource constraints, the structure of the network of tags at individual nodes is remarkably close to the ideal that would be obtained with infinite resources.
让移动用户设备感知周围的物理环境:一种基于认知启发式的方法
在本文中,我们研究了一种基于认知启发式方法的特性,通过这种方法,用户的移动设备可以意识到他们周围的物理环境。认知启发式是认知心理学中使用的心智模型,用来描述人类大脑如何有效地处理来自我们周围环境的大量信息。由于个人移动设备代表了其人类用户在网络世界中的代理,我们研究了移动设备如何使用相同的认知启发式来自我意识到用户周围物理环境的特征。具体地说,我们假设物理位置被描述为一个标签网络。我们考虑一个自组织的机会主义网络环境,其中设备在直接会面时交换信息。我们提出了基于认知启发式的算法,通过这种算法,用户的节点可以在接近位置时直接获得标签,或者通过他们遇到的其他节点间接获得标签。我们分析在单个节点产生的标签网络的属性,因为它们从这个过程中出现,作为各种认知参数的函数。我们表明,在相同的资源约束下,使用认知启发式导致相对于其他参考解决方案更有效的信息扩散。有趣的是,我们发现了区分信息扩散和信息损失的关键参数的临界阈值。最后,我们表明,尽管有资源约束,单个节点上的标签网络结构非常接近无限资源下的理想结构。
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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