DRL-Based Satellite Network Slice Planning and Handover in the Korean Peninsula Scenarios

Seonghoon Kim; Taeyeoun Kim; Jeongho Kwak; Jihwan P. Choi

doi:10.1109/ICTC58733.2023.10393845

DRL-Based Satellite Network Slice Planning and Handover in the Korean Peninsula Scenarios

Seonghoon Kim, Taeyeoun Kim, Jeongho Kwak, Jihwan P. Choi

Department of Electrical Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

This paper introduces a novel approach using deep reinforcement learning (DRL) to enhance network slicing planning and handovers in satellite networks. We propose a proactive handover trigger based on remaining service time and employ the deep deterministic policy gradient (DDPG) algorithm to maximize the utility of virtual networks (VNs). Focusing on the Korean Peninsula, we simulate a low earth orbit (LEO) satellite network based on Starlink satellite specifications and demonstrate the superiority of our intelligent network management technique compared to baseline methods, particularly in terms of latency performance and the number of handovers.

Original language	English
Title of host publication	ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence
Subtitle of host publication	Exploring the Frontiers of ICT Innovation
Publisher	IEEE Computer Society
Pages	132-133
Number of pages	2
ISBN (Electronic)	9798350313277
DOIs	https://doi.org/10.1109/ICTC58733.2023.10393845
State	Published - 2023
Event	14th International Conference on Information and Communication Technology Convergence, ICTC 2023 - Jeju Island, Korea, Republic of Duration: 11 Oct 2023 → 13 Oct 2023

Publication series

Name	International Conference on ICT Convergence
ISSN (Print)	2162-1233
ISSN (Electronic)	2162-1241

Conference

Conference	14th International Conference on Information and Communication Technology Convergence, ICTC 2023
Country/Territory	Korea, Republic of
City	Jeju Island
Period	11/10/23 → 13/10/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

Satellite network
deep reinforcement learning
handover
satellite network slicing planning

Access to Document

10.1109/ICTC58733.2023.10393845

Cite this

Kim, S., Kim, T., Kwak, J., & Choi, J. P. (2023). DRL-Based Satellite Network Slice Planning and Handover in the Korean Peninsula Scenarios. In ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence: Exploring the Frontiers of ICT Innovation (pp. 132-133). (International Conference on ICT Convergence). IEEE Computer Society. https://doi.org/10.1109/ICTC58733.2023.10393845

Kim, Seonghoon ; Kim, Taeyeoun ; Kwak, Jeongho et al. / DRL-Based Satellite Network Slice Planning and Handover in the Korean Peninsula Scenarios. ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence: Exploring the Frontiers of ICT Innovation. IEEE Computer Society, 2023. pp. 132-133 (International Conference on ICT Convergence).

@inproceedings{51bfff1112c24389b3600edbe3af8cc6,

title = "DRL-Based Satellite Network Slice Planning and Handover in the Korean Peninsula Scenarios",

abstract = "This paper introduces a novel approach using deep reinforcement learning (DRL) to enhance network slicing planning and handovers in satellite networks. We propose a proactive handover trigger based on remaining service time and employ the deep deterministic policy gradient (DDPG) algorithm to maximize the utility of virtual networks (VNs). Focusing on the Korean Peninsula, we simulate a low earth orbit (LEO) satellite network based on Starlink satellite specifications and demonstrate the superiority of our intelligent network management technique compared to baseline methods, particularly in terms of latency performance and the number of handovers.",

keywords = "Satellite network, deep reinforcement learning, handover, satellite network slicing planning",

author = "Seonghoon Kim and Taeyeoun Kim and Jeongho Kwak and Choi, \{Jihwan P.\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 14th International Conference on Information and Communication Technology Convergence, ICTC 2023 ; Conference date: 11-10-2023 Through 13-10-2023",

year = "2023",

doi = "10.1109/ICTC58733.2023.10393845",

language = "English",

series = "International Conference on ICT Convergence",

publisher = "IEEE Computer Society",

pages = "132--133",

booktitle = "ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence",

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Kim, S, Kim, T, Kwak, J & Choi, JP 2023, DRL-Based Satellite Network Slice Planning and Handover in the Korean Peninsula Scenarios. in ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence: Exploring the Frontiers of ICT Innovation. International Conference on ICT Convergence, IEEE Computer Society, pp. 132-133, 14th International Conference on Information and Communication Technology Convergence, ICTC 2023, Jeju Island, Korea, Republic of, 11/10/23. https://doi.org/10.1109/ICTC58733.2023.10393845

DRL-Based Satellite Network Slice Planning and Handover in the Korean Peninsula Scenarios. / Kim, Seonghoon; Kim, Taeyeoun; Kwak, Jeongho et al.
ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence: Exploring the Frontiers of ICT Innovation. IEEE Computer Society, 2023. p. 132-133 (International Conference on ICT Convergence).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - DRL-Based Satellite Network Slice Planning and Handover in the Korean Peninsula Scenarios

AU - Kim, Seonghoon

AU - Kim, Taeyeoun

AU - Kwak, Jeongho

AU - Choi, Jihwan P.

PY - 2023

Y1 - 2023

N2 - This paper introduces a novel approach using deep reinforcement learning (DRL) to enhance network slicing planning and handovers in satellite networks. We propose a proactive handover trigger based on remaining service time and employ the deep deterministic policy gradient (DDPG) algorithm to maximize the utility of virtual networks (VNs). Focusing on the Korean Peninsula, we simulate a low earth orbit (LEO) satellite network based on Starlink satellite specifications and demonstrate the superiority of our intelligent network management technique compared to baseline methods, particularly in terms of latency performance and the number of handovers.

AB - This paper introduces a novel approach using deep reinforcement learning (DRL) to enhance network slicing planning and handovers in satellite networks. We propose a proactive handover trigger based on remaining service time and employ the deep deterministic policy gradient (DDPG) algorithm to maximize the utility of virtual networks (VNs). Focusing on the Korean Peninsula, we simulate a low earth orbit (LEO) satellite network based on Starlink satellite specifications and demonstrate the superiority of our intelligent network management technique compared to baseline methods, particularly in terms of latency performance and the number of handovers.

KW - Satellite network

KW - deep reinforcement learning

KW - handover

KW - satellite network slicing planning

UR - https://www.scopus.com/pages/publications/85184571714

U2 - 10.1109/ICTC58733.2023.10393845

DO - 10.1109/ICTC58733.2023.10393845

M3 - Conference contribution

AN - SCOPUS:85184571714

T3 - International Conference on ICT Convergence

SP - 132

EP - 133

BT - ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence

PB - IEEE Computer Society

T2 - 14th International Conference on Information and Communication Technology Convergence, ICTC 2023

Y2 - 11 October 2023 through 13 October 2023

ER -

Kim S, Kim T, Kwak J, Choi JP. DRL-Based Satellite Network Slice Planning and Handover in the Korean Peninsula Scenarios. In ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence: Exploring the Frontiers of ICT Innovation. IEEE Computer Society. 2023. p. 132-133. (International Conference on ICT Convergence). doi: 10.1109/ICTC58733.2023.10393845

DRL-Based Satellite Network Slice Planning and Handover in the Korean Peninsula Scenarios

Abstract

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Keywords

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