标题： 基于无线信道约束的语义分组协同边缘推理 显示英文标题

标题： Collaborative Edge Inference via Semantic Grouping under Wireless Channel Constraints

摘要： 在本文中，我们研究了协作推理的框架，或称为边缘集成。 该框架使多个边缘设备通过交换中间特征而非原始观测值来提高分类准确性。 然而，高效的通信策略对于平衡准确性与带宽限制至关重要。 基于一种选择性信息交换的关键查询机制，本研究通过研究特征通信中的信道噪声影响、中间协作点的选择以及任务间的通信-准确性权衡，扩展了协作推理。 通过分析不同协作点对性能的影响并探索通信剪枝，我们表明可以在最小化资源使用的同时优化准确性。 我们证明中间协作方法对信道错误具有鲁棒性，并且查询传输需要比数据传输本身更高的可靠性。 显示英文摘要

摘要： In this paper, we study the framework of collaborative inference, or edge ensembles. This framework enables multiple edge devices to improve classification accuracy by exchanging intermediate features rather than raw observations. However, efficient communication strategies are essential to balance accuracy and bandwidth limitations. Building upon a key-query mechanism for selective information exchange, this work extends collaborative inference by studying the impact of channel noise in feature communication, the choice of intermediate collaboration points, and the communication-accuracy trade-off across tasks. By analyzing how different collaboration points affect performance and exploring communication pruning, we show that it is possible to optimize accuracy while minimizing resource usage. We show that the intermediate collaboration approach is robust to channel errors and that the query transmission needs a higher degree of reliability than the data transmission itself.