메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술대회자료
저자정보
Hee-Gon Kim (Pohang University of Science and Technology) Suhyun Park (Pohang University of Science and Technology) Stanislav Lange (Norwegian University of Science and Technology) Doyoung Lee (Pohang University of Science and Technology) Dongnyeong Heo (Handong Global University) Heeyoul Choi (Handong Global University) Jae-Hyoung Yoo (Pohang University of Science and Technology) James Won-Ki Hong (Pohang University of Science and Technology)
저널정보
한국통신학회 한국통신학회 APNOMS 한국통신학회 APNOMS 2020
발행연도
2020.9
수록면
13 - 18 (6page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
Software-Defined Networking (SDN) and Network Function Virtualization (NFV) help reduce OPEX and CAPEX as well as increase network flexibility and agility. But at the same time, operators have to cope with the increased complexity of managing virtual networks and machines, which are more dynamic and heterogeneous than before. Since this complexity is paired with strict time requirements for making management decisions, traditional mechanisms that rely on, e.g., Integer Linear Programming (ILP) models are no longer feasible. Machine learning has emerged as a possible solution to address network management problems to get near-optimal solutions in a short time. In this paper, we propose a Graph Neural Network (GNN) based algorithm to manage VNFs. The proposed model solves the complex VNF management problem in a short time and gets near-optimal solutions.

목차

Abstract
I. INTRODUCTION
II. RELATED WORK
III. PROBLEM DEFINITION
IV. GRAPH NEURAL NETWORK
V. DATA GENERATION
VI. LEARNING PROCESS
VII. EXPERIMENT
VIII. CONCLUSION
IX. ACKNOWLEDGMENT
REFERENCES

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2021-567-001678853