https://scholar.dgist.ac.kr/handle/20.500.11750/12125 2026-04-04T12:02:49Z 2026-04-04T12:02:49Z Kim, Jeongsoo Jeon, Suhyeon Kwak, Jeongho https://scholar.dgist.ac.kr/handle/20.500.11750/58507 2025-07-25T03:31:58Z 2024-10-21T15:00:00Z

Title: SOS: Dynamic Secure Code Offloading for Power Minimization in LEO Satellite Edge Computing Author(s): Kim, Jeongsoo; Jeon, Suhyeon; Kwak, Jeongho Abstract: The satellite edge computing (SEC) has recently received considerable attention thanks to its wide area service around the world. However, this also creates a risk of exposing private user data to eavesdroppers. Physical layer security can help prevent this, yet it requires extra usage of network resources. Hence, efficient management of these resources is essential for saving power and ensuring secure code offloading. Moreover, from the perspective of mobile devices that request services, the level of security demands is quite different for various services, yet current studies have not fully considered this aspect. In this paper, we propose a secure code offloading framework for an SEC system with a jamming strategy in the existence of eavesdropping satellite. We formulate an average power minimization problem of an LEO satellite, a gateway, and a mobile device while ensuring security and the stability of queues. This includes making decisions of code offloading, computing/network resource allocation, and jamming unit selection. As a solution of this problem, we propose an SOS algorithm by invoking stochastic optimization theory. Finally, via extensive simulations, we demonstrate that the proposed SOS algorithm can save up to 60% of average power compared to existing algorithms while maintaining the same delay and zero leakage of information toward eavesdropper.

2024-10-21T15:00:00Z Kwon, JiHyun Park, SangEun Chwa, Hoon Sung Kwak, Jeongho Choi, Ji-Woong Kim, BaekGyu https://scholar.dgist.ac.kr/handle/20.500.11750/57931 2025-07-25T02:43:06Z 2024-10-15T15:00:00Z

Title: Preliminary Design of Hybrid Simulation Framework for Workload Analysis in Automotive Edge Computing Author(s): Kwon, JiHyun; Park, SangEun; Chwa, Hoon Sung; Kwak, Jeongho; Choi, Ji-Woong; Kim, BaekGyu Abstract: Many vehicular tasks shall be completed in a timely manner as they move. In automotive edge computing, a vehicle can offload such tasks to an edge server in proximity to process them faster than using the cloud computing model. However, such an edge server has limited communication coverage and relatively smaller computing power compared to the general cloud server, it is important to distribute the offloaded workloads appropriately. One needs to understand such workload patterns and quantitatively analyze them for such workload distribution. We propose a preliminary hybrid simulation framework that generates compute workloads via a combination of the virtual vehicular traffic and the physical edge-server platforms. © 2024 IEEE.

2024-10-15T15:00:00Z Kim, Jeonghwan Kim, Eunsu Kwak, Jeongho https://scholar.dgist.ac.kr/handle/20.500.11750/57926 2025-07-25T02:43:06Z 2024-10-16T15:00:00Z

Title: Edge Computing on the Sky: Dynamic Code Offloading Using Realistic Satellite Onboard Processors Author(s): Kim, Jeonghwan; Kim, Eunsu; Kwak, Jeongho Abstract: The emergence of Low Earth Orbit (LEO) satellite environments has spurred active research into edge computing techniques utilizing these satellites. However, these efforts encounter significant challenges due to the physical battery limitations of the satellites. To address these issues, this paper introduces a novel edge computing technique that takes real-time battery conditions into account. © 2024 IEEE.

2024-10-16T15:00:00Z Choi, Pyeongjun Kim, Jeonghwan Kwak, Jeongho https://scholar.dgist.ac.kr/handle/20.500.11750/57920 2025-07-25T03:27:18Z 2024-10-15T15:00:00Z

Title: Joint Task Offloading and Resource Allocation for Integrated V2V and V2I Communication Author(s): Choi, Pyeongjun; Kim, Jeonghwan; Kwak, Jeongho Abstract: As autonomous driving technology becomes more sophisticated, VEC is in the limelight. However, it faces limitations in network conditions or the existence of RSU. In this paper, we propose a Lyapunov optimization-based algorithm that jointly optimizes both offloading policy and computing resources to minimize energy consumption while maintaining finite service time with the help of V2V and V2I communication. © 2024 IEEE.

2024-10-15T15:00:00Z