ORIGINAL RESEARCH article
Front. Comput. Sci.
Sec. Networks and Communications
This article is part of the Research TopicResource Coordination and Joint Optimization in Cloud-Edge-End SystemsView all 7 articles
Latency and Trust Constrained Fog Node Selection Using Deep Reinforcement Learning
Provisionally accepted
- 1Karunya Institute of Technology and Sciences, Coimbatore, India
- 2Sahrdaya College of Engineering and Technology, Kodakara, India
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Automated healthcare IoT systems demand secure, low-latency, and energy-efficient computation—capabilities well-supported by fog computing. Effective selection of fog nodes is critical for maximizing the performance of fog-based IoT platforms. This paper introduces a Secure Proximal Policy Optimization (Secure PPO) algorithm for trust-aware fog node selection, considering latency, energy consumption, processing power, and a trust flag for each node. Secure PPO enforces a trust constraint while optimizing latency and energy via PPO's clipped objective, ensuring stable and reliable learning. Simulation results demonstrate that Secure PPO achieves substantial improvements over A2C and DQN. Specifically, Secure PPO reduces inference latency by 24.36% and 37.57%, lowers convergence time by 55.56% and 66.67%, and decreases energy consumption by 11.90% and 20.04% compared to A2C and DQN, respectively. Additionally, Secure PPO improves accuracy by 9.42% and 18.88% over A2C and DQN. The framework maintains sub-millisecond inference time and ensures secure, reliable fog-based execution of automated healthcare tasks, substantially enhancing patient safety and operational efficiency within healthcare IoT environments.
Keywords: deep reinforcement learning, energy efficiency, fog computing, Latency reduction, Secure PPO, trust-aware node selection
Received: 12 Oct 2025; Accepted: 10 Dec 2025.
Copyright: © 2025 BABU, Josemin Bala and BABU. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
ANJU BABU
ANJU BABU
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