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Optimized local control strategy for voice-based interaction-tracking badges for social applications

机译:针对社交应用的基于语音的交互跟踪徽章的优化本地控制策略

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This paper presents a method to design optimized local control strategies for Cyber-Physical Systems that produce reliable data models for social applications. Data models have different semantics and abstraction levels. The local control strategies manage ad-hoc nano-clouds of embedded computing and communication nodes (CCNs) used for data collection, modeling, and communication. Control strategies consider tradeoffs defined by the resource constraints of embedded CCNs (e.g., computing power, communication bandwidth, and energy), assurance requirements (e.g., robustness) of the models, and privacy of users. Experiments evaluate and demonstrate the effectiveness of the control strategies for nano-clouds composed of smart voice-based interaction-tracking badges.
机译:本文提出了一种方法,可以为网络物理系统设计优化的本地控制策略,从而为社交应用生成可靠的数据模型。数据模型具有不同的语义和抽象级别。本地控制策略管理用于数据收集,建模和通信的嵌入式计算和通信节点(CCN)的临时纳米云。控制策略考虑了由嵌入式CCN的资源约束(例如,计算能力,通信带宽和能量),模型的保证要求(例如,鲁棒性)以及用户隐私所定义的权衡。实验评估并证明了由基于智能语音的交互跟踪标记组成的纳米云控制策略的有效性。

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