November 2025 - Jieun Lee (JL) is a Research Professor at Sejong University in Korea. She recently co-authored a paper on “Standardised Interworking and Deployment of IoT and Edge Computing Platforms”. For this interview, she discusses the motivations behind this publication and the important contributions of European Telecommunications Standards Institute (ETSI) and oneM2M communities.
Q: Let us begin by with an introduction about you and your IoT interests.
JL: I am a Research Professor in the newly launched Department of Intelligence and Information Convergence at Sejong University. I focus on IoT platforms with an emphasis on standardization.
I began my studies in computer science and developed a strong interest in IoT systems and network architectures, which later led me to complete a PhD in Security Information and IoT. As part of my PhD, I spent a year in France as an invited researcher at EGM, a research and engineering company, which is a partner of ETSI. During this time, I became involved in several ETSI groups including MEC, PDL, and CIM, contributing to discussions on edge-IoT interworking and data interoperability. After receiving my PhD, I returned to Korea and joined the faculty at Sejong University.
My first introduction to standardization was in 2021 when I made my first contribution to oneM2M. At that time, I was working at KETI. Since 2023, I have been contributing to MEC and oneM2M activities, including an ETSI White Paper that provides the foundations for how organizations can deploy interworking MEC and oneM2M systems. These experiences shaped my current research direction, which focuses on standards-based IoT platforms and their practical applications.
Q: What is behind the launch of the new Department of Intelligence and Information Convergence?
JL: The department focuses on artificial intelligence (AI) capabilities, which is seen in Korea as being at the core of the Fourth Industrial Revolution. In addition to carrying out research, there is strong educational aspect in the form of software teaching, industry-linked internships, seminars, and hands-on training. We want to build on the latest technological themes and assist industry to develop commercial-grade products.
As an example of my teaching responsibilities, I have about two-hundred students on my course on “Introduction to Intelligent IoT.” They include Sejong University students as well as those from four other universities in Korea. This scale is part of our goal to develop a skilled workforce. I teach an introductory course on intelligent IoT and introduce students to the newest AIoT (AI + IoT) trends. I also teach “Intelligent IoT Platforms,” where students gain hands-on experience with real platforms using oneM2M standards such as tinyIoT, Mobius, and ACME CSE.
The department has strong industry ties. As the university’s representative to the IoT COSS (Internet of Things Convergence & Open Sharing System) program funded by the Korean government, Sejong University is committed to fostering talent and helping industry develop commercial-grade IoT products. We send students on two-to-three-week programs where they work with small businesses. Students also participate in hackathons and support other forms of industrial collaboration.
Q: For interested readers, what are tinyIoT, Mobius, and ACME CSE?
JL: Using oneM2M terminology, Mobius and ACME CSE are conventional common services entities (CSEs); they correspond to what industry users would call an IoT platform. Both are open-source platforms. Mobius was developed by KETI to support local industry and research communities. ACME CSE is a more recent offering that was developed by Andreas Kraft of Deutsche Telekom.
Mobius and ACME are typically meant for deployment in cloud and server environments (although they can be deployed in edge gateways). tinyIoT is designed as a lightweight system that can be deployed closer to edge environments. Reverting to oneM2M terminology, tinyIoT can operate as a CSE and as a middle node (MN). It is up to date in terms of oneM2M’s roadmap, being able to support Release 4 and Release 5 capabilities.
Q: Let us talk about the paper you recently published. What factors motivated the study?
JL: The paper, published in the Digital Communications and Networks (DCN) journal, focuses on implementing interoperable IoT and Edge Computing platforms. Standardization of the interworking interfaces is important when combining these two platform types. From my prior research, two independent standardization activities are ETSI’s standardization of Multiaccess Edge Computing (MEC), and oneM2M’s activities in dynamic data management and IoT services at the edge, notably in situations that require real-time support and security. Efforts to bring these two activity streams began with the publication of an ETSI White paper. This was a collaborative MEC-oneM2M effort that bridges the communications industry’s 3GPP standardization framework with IoT and oneM2M.
The DCN paper proposes an approach for integrating MEC and oneM2M standard platforms in IoT applications. Although MEC and oneM2M follow different architectural approaches, our analysis for the paper demonstrates synergies that can use geographically distributed computing resources at base stations to enable efficient deployment while adding value for time-sensitive, IoT applications.
Figure 1 Comparison of ETSI MEC, oneM2M, and Our Work.
The aim of the paper is to lay the groundwork for implementation, testing, and evaluation of different architectural configurations. We have selected tinyIoT as the oneM2M CSE and we are working on a modified, open-source application for the MEC part.
This work provides practical analysis and validation scenarios by extending key concepts that were first outlined in the white paper. Our goal was to move from theoretical interoperability discussions to a tangible framework that can be implemented and tested in real IoT-Edge deployments.
Q: What are your plans to move forward with the research from this paper?
JL: There are two strands of work we are pursuing. One is through the ESTIMED project. ESTIMED stands for “Enabling Standardized IoT deployments in MEC Environments for advanced systems.” It brings together ETSI’s MEC and oneM2M into a horizontal platform for interoperable and scalable IoT systems. The project is co-funded by the European Commission and EFTA and involves a consortium of international participants.
The second strand of work is to make advances to tinyIoT. We are in early discussions with a couple of partners to experiment with IoT. What I would like to emphasize is that this work is not just conceptual. We are already moving into implementation and testing, starting with tinyIoT as the oneM2M platform and an open-source MEC application. Our focus right now is to evaluate different architectural configurations in realistic environments — not only in simulation, but also in controlled lab settings on campus.
We are also coordinating with several external partners to explore deployment in real-world scenarios. Those collaborations are still being finalized. However, the direction is clear: we want to validate that MEC-oneM2M interworking can deliver low-latency, trustworthy IoT services at the edge. That is the next step.
Q: Are there any other research activities arising from your work?
JL: As a researcher, I am always exploring new concepts and synergies in IoT and related technologies such as AI. In addition to my involvement in the project, I also proposed a swarm computing scenario to the ETSI STF 685 team (project on Enabling Standardized IoT deployments in MEC Environments for advanced systems), demonstrating how MEC and oneM2M could be jointly utilized to improve coordination and scalability among distributed Edge nodes. In this case, the idea of swarm computing is to coordinate multiple Edge nodes to improve latency and decision making.
Imagine a scenario where several robots are navigating a space, like a factory or a hotel, to complete a fetch-and-delivery task. Each robot is an Edge node which is constantly sensing and collecting local information. There are benefits if individual robots share that information via node-to-node communications. These industrial and hotel space scenarios are examples where the combination of MEC and oneM2M functionality are highly complementary. We are currently testing these ideas in one of our university buildings, beginning initially with simulations and then progressing to a laboratory testbed.
Q: Where can readers get more information on the topics you have shared with us?
JL: Here are links to the ETSI White Paper on MEC and oneM2M interworking, and to my team’s DCN paper.
For coding and experimental work, here is the tinyIoT code repository. Additional open-source platforms such as MOBIUS and ACME CSE are also freely available for experimentation.
