Evaluating 5G-connected IoT for Power Line Temperature Prediction: Real-World Latency and Cost Trade-offs Between MEC and Cloud

2026-07-04

AI Summary

This study addresses the dual challenge of ultra-low latency (approximately 8 ms) and cost-effectiveness in power line temperature prediction for smart grids by designing and empirically evaluating a real-time analytics system leveraging 5G and Mobile Edge Computing (MEC). For the first time in a real-world 5G environment, the end-to-end latency and economic performance of MEC are rigorously compared against multi-region cloud deployments. Experimental results demonstrate that the MEC-based approach achieves an average latency of 44.62 ms, significantly outperforming cloud-based solutions; however, it still falls short of meeting the most stringent real-time control requirements. These findings expose critical performance bottlenecks of current edge computing infrastructures in power Internet-of-Things applications and provide essential empirical insights to guide the design of future low-latency architectures.

Abstract

One of the key promises of Mobile Edge Computing (MEC) is its low latency. Current large-scale IoT deployments rely on cloud for their reliability, low cost, and ease of use. For outdoor IoT deployments, 5G cellular networks offer significantly enhanced bandwidth and dramatically reduced latency compared to previous generations, enabling real-time data processing and control. Therefore, leveraging 5G connectivity is crucial for outdoor IoT applications requiring responsiveness and complex data handling. Combining MEC with 5G has the potential to provide the ease of cloud computing alongside low latency. We investigate the latency performance on a 5G cellular network with an experimental MEC setup. In our proof-of-concept, we demonstrate the benefits of using an edge-based compute server for real-time power transmission line analytics. We compare our solution with state-of-the-art multi-region cloud deployments and discuss the advantages of mobile edge computing (MEC). Our real-world evaluation demonstrates a low latency of 44.62 ms for MEC compared to cloud regions; however, the gap is narrowing. While such low latencies can benefit real-world deployments, they remain insufficient to meet the stringent requirements of smart power grid operations (~8 ms).

Problem

• 5G
• IoT
• latency
• MEC
• power grid

Innovation

• Mobile Edge Computing (MEC)
• 5G-connected IoT
• latency evaluation
• power line temperature prediction
• edge-cloud trade-off