Intelligent information dissemination in collaborative, context-aware environments

K. Frank, Matthias Röckl, T. Pfeifer
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引用次数: 4

Abstract

Today's mobile computing environments aggregate many entities, all of them with a number of internal sensors, processing applications and other, user given information that can be shared with others over the available networks. Tomorrow's ubiquitous computing environments, where the number of sensors is assumed to be even significantly higher, face the challenge that information exchange between entities has to be controlled, not only to protect privacy and to unburden the wireless networks - but also to reduce load on the receiving entities that have to process all incoming information. The approach we propose in this work measures the importance of some information and the interest of the receiver in it, before it is transferred. We apply it in two scenarios with limited resources. In vehicle-to-vehicle communications the transmission time while cars meet and bandwidth availability of the wireless channel is the critical resource, forcing to reduce information exchange. In context inference on mobile devices processing power and battery life are limited and responsiveness to user actions is most important. Hence only the most important information should be processed.
协作、上下文感知环境中的智能信息传播
今天的移动计算环境聚集了许多实体,它们都有许多内部传感器、处理应用程序和其他用户提供的信息,这些信息可以通过可用的网络与他人共享。未来的无处不在的计算环境中,传感器的数量被认为会显著增加,面临着实体之间的信息交换必须受到控制的挑战,这不仅是为了保护隐私和减轻无线网络的负担,也是为了减少接收实体必须处理所有传入信息的负荷。我们在这项工作中提出的方法是在信息传递之前测量一些信息的重要性和接收者对它的兴趣。我们将其应用于两种资源有限的场景。在车对车通信中,车与车之间的传输时间和无线信道的带宽可用性是关键资源,迫使信息交换减少。在移动设备上的上下文推理处理能力和电池寿命是有限的,对用户操作的响应是最重要的。因此,只处理最重要的信息。
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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