Conformal Distributed Remote Inference in Sensor Networks Under Reliability and Communication Constraints

• URL: http://arxiv.org/abs/2409.07902v1
• Date: Thu, 12 Sep 2024 10:12:43 GMT
• Title: Conformal Distributed Remote Inference in Sensor Networks Under Reliability and Communication Constraints
• Authors: Meiyi Zhu, Matteo Zecchin, Sangwoo Park, Caili Guo, Chunyan Feng, Petar Popovski, Osvaldo Simeone,
• Abstract summary: Communication-constrained distributed conformal risk control (CD-CRC) CD-CRC is a novel decision-making framework for sensor networks under communication constraints.
• Score: 61.62410595953275
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper presents communication-constrained distributed conformal risk control (CD-CRC) framework, a novel decision-making framework for sensor networks under communication constraints. Targeting multi-label classification problems, such as segmentation, CD-CRC dynamically adjusts local and global thresholds used to identify significant labels with the goal of ensuring a target false negative rate (FNR), while adhering to communication capacity limits. CD-CRC builds on online exponentiated gradient descent to estimate the relative quality of the observations of different sensors, and on online conformal risk control (CRC) as a mechanism to control local and global thresholds. CD-CRC is proved to offer deterministic worst-case performance guarantees in terms of FNR and communication overhead, while the regret performance in terms of false positive rate (FPR) is characterized as a function of the key hyperparameters. Simulation results highlight the effectiveness of CD-CRC, particularly in communication resource-constrained environments, making it a valuable tool for enhancing the performance and reliability of distributed sensor networks.

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