한국전자통신학회논문지 (The Journal of the Korea institute of electronic communication sciences)

한국전자통신학회 (Korea Institute of Electronic Communication Science)
권호 표지
DOI QR코드

DOI QR Code

CCN에서 실시간 콘텐츠 인기도 기반 캐시 정책

A Real-time Content Popularity-Based Cache Policy in Content Centric Network

  • 서민근 (국방대학교 관리대학원) ;
  • 권태욱 (국방대학교 컴퓨터공학과)
  • 투고 : 2023.09.18
  • 심사 : 2023.12.27
  • 발행 : 2023.12.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

CCN(: Content Centric Network)은 기존 네트워크 구조를 개선하기 위해 등장한 네트워크로, 주소 대신 콘텐츠 이름에 기반하여 통신한다. 캐시를 활용하여 트래픽을 분산시키고, 중간노드에서 콘텐츠를 전송함으로써 응답시간 감소 효과를 가져오고 있다. 본 논문에서는 CCN 환경에서 제한된 CS 공간을 효율적으로 활용할 수 있도록 인기도를 고려한 캐시 정책을 제안한다. 어떤 콘텐츠에 우선순위를 두어 저장하고 방출할지를 결정하는지에 따라 CCN의 성능이 크게 달라질 수 있다. 가장 효율적인 캐시 교체를 위해 생성자 인기도, 생성자 거리, 콘텐츠 히트수를 기반으로 콘텐츠 인기도를 계산해 우선순위를 정하는 실시간 콘텐츠 인기도 기반 효율적인 캐시 교체정책을 제안하였으며, 새로운 정책의 효율성을 실험을 통해 입증하였다.

Content Centric Network (CCN) is a network that emerged to improve the existing network structure and communicates based on content names instead of addresses. It utilises caches to distribute traffic and reduce response time by delivering content from intermediate nodes. In this paper, we propose a popularity-based caching policy to efficiently utilise the limited CS space in CCN environment. The performance of CCNs can vary significantly depending on which content is prioritised to be stored and released. To achieve the most efficient cache replacement, we propose a real-time content popularity-based efficient cache replacement policy that calculates and prioritises content popularity based on constructor popularity, constructor distance, and content hits, and demonstrate the effectiveness of the new policy through experiments.

키워드

참고문헌

  1. Cisco, "Cisco Annual Internet Report(2018-2023) White paper," report, 2020.
  2. Cisco, "Cisco Visual Networking Index: Forecast and Trends, 2017-2022 White paper," report, 2019.
  3. V. Jacobson, D. K. Smetters, J. D. Tornton, M. F. Plass, N. H. Briggs, and R. L. Braynard, "Networking Named Content," Proc. the 5th international conference on Emerging networking experiments and technologies, Rome, Italy, Dec. 2009, pp. 1-12.
  4. J. Kim, H. Jung, and W. Park, "Content Centric Networking Technology," Journal of the Electronics and Telecommunications Trends, vol. 25, no. 6, 2010, pp. 136-143.
  5. S. Podlipnig and L. B. S. Rmenyi, "A Survey of Web Cache Replacement Strategies," ACM Computing Survey, vol. 35, no 4, 2003.
  6. M. K. Qureshi, A. Jaleel, Y. N. Patt, S. C. Steely, and J. Emer, "Adaptive Insertion Policies for High Performance Caching," Proc. of the 34th International Symposium on Computer Architecture (ISCA 2007), San Diego, CA, USA, 2007, pp.381-391.
  7. A. K. Y. Wong, "Web cache replacement policies: a pragmatic approach," IEEE Network magazine, vol. 20, no. 1, 2006, pp. 28-34. https://doi.org/10.1109/MNET.2006.1580916
  8. N. C. Fofack, P. Nain, G. Neglia, and D. Towsley, "Analysis of TTL-based cache networks," Proc. of 6th International ICST Conference on Performance Evaluation Methodologies and Tools, Cargese, Freance, 2012, pp.1-10.
  9. J. Choi and T. Kwon, "Real-time Producer Popularity-based LFU in Content Centric Network," J. of the Korean Institute of Electronic Communications Science, vol. 16, no. 6, Dec. 2021, pp. 1113-1120.
  10. G. Kim and T. Kwon, "Cache Policy based on Producer Distance to Reduce Response Time in CCN," J. of the Korean Institute of Electronic Communications Science, vol. 16, no. 6, Dec. 2021, pp. 1121-1132.
  11. J. Min and T. Kwon, "A Cache Policy on Producer Popularity-Distance in CCN," J. of the Korean Institute of Electronic Communications Science, vol. 17, no. 5, Oct. 2022, pp. 791-799.