DOI QR코드

DOI QR Code

MST 알고리즘 기반 콘텐츠 전송 네트워크에 관한 연구

Content Delivery Network Based on MST Algorithm

  • Lee, Hyung-ok (Chonnam National University Department of Electronics and Computer Engineering) ;
  • Kang, Mi-young (Chonnam National University Department of Computer Engineering) ;
  • Nam, Ji-seung (Chonnam National University Department of Computer Engineering)
  • 투고 : 2015.10.06
  • 심사 : 2016.01.27
  • 발행 : 2016.02.29

초록

스마트폰의 증가와 PC 성능 향상으로 유무선 통신망에 트래픽이 폭발적으로 증가하고 있다. 여기에는 페이스북, 유투브와 같은 멀티미디어 서비스와 파일 공유가 큰 부분을 차지하고 있다. CDN(Content Delivery Network)은 원거리에 있는 콘텐츠 사업자의 웹 서버에 저장된 콘텐츠를 이용자 근처 CDN 서버에 미리 저장, 콘텐츠 요구 발생 시 최적의 CDN 서버로부터 콘텐츠를 제공하는 콘텐츠 전송 기술이다. 본 논문에서는 콘텐츠 요청 메시지 전달에 Minimum Spanning Tree(MST) 알고리즘을 응용한 SCRP(Shortest Core Routing Path) 알고리즘을 사용해 CDN 서버와 클라이언트의 콘텐츠 전달에 이용되는 전체 트래픽 양을 최적화하였다. 또한 HC_LRU 캐시 알고리즘을 통해 캐시 적중률을 향상시킴으로써 콘텐츠 요청에 대한 평균 응답시간을 단축시켰다. 제안한 SCRP와 HC_LRU 알고리즘을 통해 트래픽을 지역화하고 병목현상을 방지하여 네트워크 자원을 효율적으로 사용하는 확장성 있는 콘텐츠 전송 네트워크 시스템을 구축할 수 있다.

The traffic in the wired and wireless networks has increased exponentially because of increase of smart phone and improvement of PC performance. Multimedia services and file transmission such as Facebook, Youtube occupy a large part of the traffic. CDN is a technique that duplicates the contents on a remote web server of content provider to local CDN servers near clients and chooses the optimal CDN server for providing the content to the client in the event of a content request. In this paper, the content request message between CDN servers and the client used the SCRP algorithm utilizing the MST algorithm and the traffic throughput was optimized. The average response time for the content request is reduced by employing HC_LRU cache algorithm that improves the cache hit ratio. The proposed SCRP and HC_LRU algorithm may build a scalable content delivery network system that efficiently utilizes network resources, achieves traffic localization and prevents bottlenecks.

키워드

참고문헌

  1. X. Hei, et al., "A measurement study of a large-scale P2P IPTV system," IEEE Trans. Multimedia, vol. 9, no. 8, pp. 1672-1687, 2007. https://doi.org/10.1109/TMM.2007.907451
  2. Y. Liu, Y. Guo, and C. Liang, "A survey on peer-to-peer video streaming systems," Peer-to-peer Netw. Appl., vol. 1, no. 1, pp. 18-28, 2008. https://doi.org/10.1007/s12083-007-0006-y
  3. H. Schulze and K. Mochalski, Internet Study 2008/2009, IPOQUE Report, vol. 37, pp. 351-362, 2009.
  4. J. Seedorf, S. Kiesel, and M. Stiemerling, "Traffic localization for P2P-applications: the ALTO approach," IEEE Peer-to-Peer Comput., 2009, pp. 171-177, Sept. 2009.
  5. B. Mathieu and P. Paris, "A topology-aware P2P video streaming system," IEEE GIIS'09, pp. 1-8, Jun. 2009.
  6. Y. Tian, et al., "Improving stability for peer-to-peer multicast overlays by active measurements," J. Syst. Architecture, vol. 54, no. 1, pp. 305-323, 2008. https://doi.org/10.1016/j.sysarc.2007.07.002
  7. F. Wang, J. Liu, and Y. Xiong, "Stable peers: Existence, importance, and application in peer-to-peer live video streaming," INFOCOM 2008, Phoenix, AZ, Apr. 2008.
  8. J. Park, "Efficient parent peer selection method in a wireless P2P system," J. KICS, vol. 39, no. 12, pp. 870-872, Dec. 2014.
  9. T. A. Neves, et al., "Optimization in content distribution networks," in Proc. Int. Conf. Eng. Optimization, Rio de Janeiro, Brazil, Jun. 2008.
  10. C. Huang, et al., "Understanding hybrid CDN-P2P: why limelight needs its own Red Swoosh," in Proc. NOSSDAV ACM, pp. 75-80, May 2008.
  11. G. Pierre and M. Van Steen, "Globule: a collaborative content delivery network," IEEE Commun. Mag., vol. 44, no. 8, pp. 127-133, 2006. https://doi.org/10.1109/MCOM.2006.1678120
  12. S. Gitzenis, G. S. Paschos, and L. Tassiulas, "Asymptotic laws for content replication and delivery in wireless networks," IEEE INFOCOM, pp. 531-539, Mar. 2012.
  13. S. H. Kong and J.-Y. Lee, "Effective contents delivery system using service adaptive network architecture(SaNA)," J. KICS, vol. 39, no. 6, pp. 406-413, Jun. 2014.
  14. S. Ratnasamy, et al., "A scalable content-addressable network," ACM, vol. 31, no. 4, pp. 161-172, 2001.
  15. B. Godfrey, et al., "Load balancing in dynamic structured P2P systems," INFOCOM 2004, vol. 4, pp. 2253-2262, Mar. 2004
  16. B. Azimdoost, C. Westphal, and H. R. Sadjadpour, "On the throughput capacity of information-centric networks," in Proc. 25th Int. Teletraffic Congress 2013, pp. 1-9, Sept. 2013.
  17. H. Che, Y. Tung, and Z. Wang, "Hierarchical web caching systems: Modeling, design and experimental results," IEEE J. Sel. Areas in Commun., vol. 20, no. 7, pp. 1305-1314, 2002. https://doi.org/10.1109/JSAC.2002.801752
  18. C. Fricker, P. Robert, and J. Roberts, "A versatile and accurate approximation for LRU cache performance," in Proc. 24th Int. Teletraffic Congress, no. 8, Sept. 2012.
  19. S. Han, H. Park and T. Kwon, "Shelf-Life time based cache replacement policy suitable for web environment," J. KICS, vol. 40, no. 6, pp. 1091-1101, Jun. 2015. https://doi.org/10.7840/kics.2015.40.6.1091