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

Jul 16, 2026

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Mobile Edge Computing (MEC) promises low latency, while large-scale IoT deployments often rely on cloud services for reliability, cost efficiency, and simplicity. For outdoor IoT, 5G provides higher bandwidth and much lower latency than prior generations, enabling real-time processing and control. This study experimentally evaluates latency on a 5G network using an MEC setup and compares it with multi-region cloud deployments, including measured operational cost trade-offs. Results show MEC latency of 44.62 ms vs. cloud, with a narrowing gap, but still above smart power grid limits (~8 ms).

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages12

Reading Time30 min

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arXiv :2607 .03993v 1 [ cs .NI] 4 Jul 2026 Evaluating 5G-connected IoT for Power Line Temperature Prediction: Real-World Latency and Cost Trade-offs Between MEC and Cloud Aakash Sharma 1 , Sigmund Akselsen2 , Anders Andersen 1 , Lars Ailo Bongo 1 , and Arne Munch-Ellingsen2 1 UiT – The Arctic University of Norway, Tromsø, Norway, [aakash.sharma@uit.no](aakash.sharma@uit.no) 2 Telenor Research, Fornebu, Norway 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) . Keywords: mobile edge computing, iot, latency, edge, 5G, MEC 1 Introduction Mobile Edge Computing, or Multi-Access Edge Computing (MEC), introducesa novel architecture that enables computing closer to the edge of the network, reducing latency and enabling real-time processing capabilities. A key feature of MEC is its ability to facilitate low-latency communication between endpoints, making it attractive for applications requiring low latencies. The fifth generation (5G) cellular networks provide a complementary infrastructure, offering faster network speeds, lower latency, and increased bandwidth to support the growing number of devices connecting to the Internet. The Internet of Things (IoT) is a notable beneficiary of 5G, enabling seamless integration 2 Aakash Sharma et al. of a vast array of devices into our digital landscape. Furthermore, recent advancements in machine learning and artificial intelligence have the potential to augment the intelligence and control of IoT devices, unlocking new possibilities. The widespread availability of 5G networks provides a unique opportunity to test and validate the benefits of MEC in real-world scenarios, which is crucial for its large-scale adoption. Multi-access Edge Computing (MEC) targets a new class of applications and services with stringent requirements on ultra-low latency, high bandwidth, and efficient resource utilization [6] . Although multiple architectures and approaches have been proposed to reduce latency in MEC, real-world evaluations are required to determine which classes of low-latency applications can be supported by current 5G networks [6,15] . Recent studies indicate that 5G and MEC architectures are being designed to support distributed AI/ML workloads by enabling low-latency, real-time processing close to data sources [10] . The increasing complexity of next-generation networks and services necessitates AI/ML-driven automation and optimization, making MEC a key enabler for future intelligent applications. This study is set in Norway, a unique test environment due to the widespread availability of 5G, varied landscape, and remote communities in Northern Norway. We focus on IoT devices that connect directly to 5G networks, excluding those that rely on home Wi-Fi connec

FAQs

What key latency result is reported, and how does it relate to smart grid requirements?

The real-world evaluation reports 44.62 ms latency for MEC compared to cloud regions, while the gap is narrowing; however, this remains higher than stringent smart power grid operation requirements of about 8 ms.

Jul 16, 2026

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