Korea University · Computer Science
Professor Soohyun Park's research lab specializes in next-generation intelligent networking and autonomous systems, with a strong focus on underwater and aerial Internet of Things (IoUT and IoUT) technologies, cooperative multi-agent systems, and quantum-enhanced reinforcement learning for real-time optimization. The lab investigates scalable communication protocols, energy-efficient scheduling, and reliable networking in challenging environments such as deep-sea and aerial domains. Key research directions include underwater acoustic and optical communications, autonomous drone delivery systems, and quantum-accelerated decision-making for Industry 4.0 and smart logistics.
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Owing to the hasty growth of communication technologies in the Underwater Internet of Things (UIoT), many researchers and industries focus on enhancing the existing technologies of UIoT systems for developing numerous applications such as oceanography, diver networks monitoring, deep-sea exploration and early warning systems. In a constrained UIoT environment, communication media such as acoustic, infrared (IR), visible light, radiofrequency (RF) and magnet induction (MI) are generally used to t
For Industry 4.0 Revolution, cooperative autonomous mobility systems are widely used based on multiagent reinforcement learning (MARL). However, the MARLbased algorithms suffer from huge parameter utilization and convergence difficulties with many agents. To tackle these problems, a quantum MARL (QMARL) algorithm based on the concept of actor-critic network is proposed, which is beneficial in terms of scalability, to deal with the limitations in the noisy intermediatescale quantum (NISQ) era. Ad
The underwater internet of things (UIoT) has emerged as a booming technology in today’s digital world due to the enhancement of a wide range of underwater applications concerning ocean exploration, deep-sea monitoring, underwater surveillance, diver network monitoring, location and object tracking, etc. Generally, acoustic, infrared (IR), visible light (VL), radiofrequency (RF), and magnet induction (MI) are used as the medium of communication in order to transfer information among digitally lin
As oceans cover the majority of the earth’s surface, it becomes inevitable in extending the concepts of Internet of Things (IoT) to ocean bodies, thereby tiling the way for a new drift in the digital world, the Internet of Underwater Things (IoUT). The primary objective of IoUT is the creation of a network of several smart interconnected undersea things, to digitally link water bodies by using devices such as autonomous underwater vehicles. Since the traditional ideas of IoT cannot be merely exp
It has been widely considered that autonomous aerial drone-delivery will play a key role in next-generation logistics. For enabling robust and reliable autonomous multi-drone aerial package delivery services, the proposed algorithm has to mainly consider two objectives, i.e., (i) the maximization of total number of delivered packages and (ii) the efficient energy utilization which is defined as the energy consumption facilitation for increasing the number of delivered packages while avoiding bat
In this paper, several MAC scheduling methods applicable to an underwater environment are proposed. Besides, a new marine communication system model was proposed to improve the reliability of the proposed SBMAC method. The scheme minimizes transmission of control frames except for data transmission and various transmission methods and ACK methods can be used together. Simulation models are set indices and analysis of the underwater environment is established to conduct reliable simulations. Cons
In order to build realistic metaverse systems, enabling high synchronization between physical-space and virtual meta-space is essentially required. For this purpose, this paper proposes a novel system-wide coordination algorithm for high synchronization under characteristics ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , highly realistic meta-space construction under the constraints of physical-space). The proposed algorithm consist
In modern networks, the use of drones as mobile base stations (MBSs) has been discussed for coverage flexibility. However, the realization of drone-based networks raises several issues. One of critical issues is drones are extremely power-hungry. To overcome this, we need to characterize a new type of drones, so-called charging drones, which can deliver energy to MBS drones. Motivated by the fact that the charging drones also need to be charged, we deploy ground-mounted charging towers for deliv
Recent advances in low Earth orbit (LEO) satellites have made it possible to achieve zero blind spots on Earth. Considering the give locations of these devices, this makes satellite-ground links between quantum devices a practical possibility. This paper proposes the first quantum federated learning (QFL) application in satellite-ground communication. To improve communication and computing performance, this paper adopts slimmable quantum federated learning (SQFL) and slimmable quantum neural net
In the last few decades, underwater communication systems have been widely used for the development of navy, military, business, and safety applications, etc. However, in underwater communication systems, there are several challenging issues, such as limitations in bandwidth, propagation delay, 3D topology, media access control, routing, resource utilization, and power constraints. Underwater communication systems work under severe channel conditions such as ambient noise, frequency selectivity,
This article addresses novel quantum multi-agent reinforcement learning (QMARL)-based scheduling for integrated terrestrial ground-stations and large-scale non-terrestrial cube-satellites networks to enable coordinated global access services. By utilizing quantum-based neural networks for designing QMARL, stable large-scale cube-satellite scheduling can be realized thanks to fast training with quantum-specific learning computation methods. In addition to the benefit from conventional QMARL algor
This article proposes a distributed angular routing algorithm in time-varying dynamic low Earth orbit (LEO) satellite constellation networks. For designing satellite routing algorithms, it is essential to consider 1) distributed operation due to the difficulty in global centralized computation and 2) angle-based computation under the consideration of orbit coordinate systems. Therefore, our proposed routing algorithm is based on distributed angular computation. Moreover, the proposed algorithm i
A metaverse is composed of a physical-space and virtual-space, with the aim of having users in both the virtual reality and the real world experience. Prioritization is essential, but it is not straight-forwarded due to the limitation of computing resources in real-world, making it impossible to synchronize all data. Therefore, it is crucial to allocate resources based on regional preferences in physical-space and content preferences of users in virtual-space. The referencing system consists of
In this paper, we review well-known handovers algorithms in satellite environment. The modern research trends and contributions are proposed and summarized in order to overcome their considering problems in satellite-air-ground integrated network environment caused by the fast movement of Low Earth Orbit (LEO) satellite and related frequent handover occurrences.
According to the advances in quantum computing and distributed learning, quantum federated learning (QFL) has recently become an emerging field of study. In QFL, each quantum computer or device locally trains its quantum neural network (QNN) with trainable gates, and communicates only these gate parameters over classical channels, without costly quantum communications. To successfully opeate QFL under various and dynamic channel conditions in Internet of Things (IoT) environments, this article d
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