特邀论文:智慧社区中的易逝数据

Glenn Ricart
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引用次数: 0

摘要

现在和未来的分布式智能和连接社区应用程序将持续感知易逝数据,并据此做出决策。当数据表示在过去某个时间点(可能在分布式应用程序的某个遥远部分)感知到的信息,并且其基础事实可能已经发生变化时,我们说数据是易逝的。本文讨论了传感源、网络和控制器可以采取的行动,以便在我们只知道真相的延迟版本的情况下做出最佳决策。其中一些保持数据新鲜度的操作是基于已知的实时技术,如时间敏感网络。在此基础上,我们添加了基于消息的信息论,以及内容和网络处理之间的跨层协调。易腐信息的意外性(惊喜)和时效性(新鲜度)都可以使用香农信息熵框架进行编码。给出了与这些概念相关的未来智能社区系统的示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Invited Paper: Perishable Data in Smart Communities
Distributed smart and connected community applications of the present and future will continuously sense perishable data on which they make decisions. We say the data are perishable when they represent information sensed at a past point in time, possibly at a distant part of the distributed application, and for which the ground truth could have since changed. This paper discusses actions the sensing source, the network, and the controller can take to make the best possible decisions given that we know only a delayed version of the truth. Some of these actions to preserve freshness of data are based on known real-time techniques such as Time Sensitive Networking. To these we add Information Theory applied on a message-by-message basis and cross-layer coordination between content and network handling. Both the unexpectedness (surprisal) and timeliness (freshness) properties of perishable information can be encoded using a Shannon information entropy framework. Examples of smart community systems of the future for which these concepts are relevant are given.
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