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
학술저널
저자정보
Muhammad Imran (Hongik University) Muhammad Atif Ur Rehman (Hongik University) Byung-Seo Kim (Hongik University)
저널정보
대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.10 No.3
발행연도
2021.6
수록면
250 - 258 (9page)
DOI
10.5573/IEIESPC.2021.10.3.250

이용수

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

초록· 키워드

오류제보하기
Edge Computing (EC) and Named Data Networking (NDN) are two emerging technologies that are considered as the most representative technologies for the future Internet. NDN directly forwards an application layer name in the network layer, mitigating the requirements of an individual and complex network addressing schemes for devices. The intermediate nodes and/or routers in NDN architecture cache the content inside their memory according to the caching policy to fulfill similar requests in the future within a short time. EC, on the other hand, offers computation, software services, data, and storage that are close to end-users compared to cloud computing, which results in lower delay and high speed of task execution. In the 5G communication scenarios and beyond, ultra-low latency, efficient mobility management, and security are fundamental requirements. Thus, the synergy of NDN with EC appears as a promising candidate and has attracted extensive attention from academia in the recent past. Therefore, in this survey paper, we discuss various techniques that integrate EC with Information Centric Networking (ICN)/NDN and fulfill the aforementioned requirements. We also shed light on the limitations and open research challenges in the field of NDN and EC for the research community.

목차

Abstract
1. Introduction
2. Named Data Networking: In a nutshell
3. An overview of Edge Computing
4. Information-centric Edge Computing
5. Open Research Issues
6. Conclusion
References

참고문헌 (27)

참고문헌 신청

함께 읽어보면 좋을 논문

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

이 논문의 저자 정보

이 논문과 함께 이용한 논문

최근 본 자료

전체보기

댓글(0)

0