Symbor Weronika, Falas Łukasz
Department of Computer Science and Systems Engineering, Faculty of Information and Communication Technology, Wrocław University of Science and Technology, 50-370 Wrocław, Poland.
Sensors (Basel). 2025 Jan 4;25(1):247. doi: 10.3390/s25010247.
The distributed nature of IoT systems and new trends focusing on fog computing enforce the need for reliable communication that ensures the required quality of service for various scenarios. Due to the direct interaction with the real world, failure to deliver the required QoS level can introduce system failures and lead to further negative consequences for users. This paper introduces a prediction-based resource allocation method for Multi-Access Edge Computing-capable networks, aimed at assurance of the required QoS and optimization of resource utilization for various types of IoT use cases featuring adaptability to changes in users' requests. The method considers the current resource load and predicted changes in resource utilization based on historical request data, which are then utilized to adjust the resource allocation optimization criteria for upcoming requests. The proposed method was developed for scenarios utilizing edge computing, e.g., autonomous vehicle data exchange, which can be susceptible to periodic resource demand fluctuations related to typical rush hours, predictable with the proposed approach. The results indicate that the proposed approach can increase the reliability of processes conducted in IoT systems.
物联网系统的分布式特性以及聚焦于雾计算的新趋势，使得对可靠通信的需求变得迫切，这种可靠通信要确保在各种场景下都能达到所需的服务质量。由于与现实世界的直接交互，如果无法提供所需的服务质量水平，可能会导致系统故障，并给用户带来进一步的负面后果。本文介绍了一种针对具备多接入边缘计算能力的网络的基于预测的资源分配方法，旨在确保所需的服务质量，并针对各类物联网用例优化资源利用，同时具备适应用户请求变化的能力。该方法考虑当前的资源负载以及基于历史请求数据预测的资源利用变化情况，然后利用这些信息来调整针对即将到来请求的资源分配优化标准。所提出的方法是针对利用边缘计算的场景开发的，例如自动驾驶车辆的数据交换，这种场景可能会受到与典型高峰时段相关的周期性资源需求波动的影响，而所提出的方法能够对其进行预测。结果表明，所提出的方法能够提高物联网系统中所执行流程的可靠性。
