Analysis of CDN Caching Strategies for Global Applications
Ukamaka Azode
ENSC 833 - Network Protocols and Performance
Engineering Science, Simon Fraser University, April 2026.
Ukamaka Azode
ENSC 833 - Network Protocols and Performance
Engineering Science, Simon Fraser University, April 2026.
Content Delivery Networks (CDNs) reduce latency and cloud egress costs for global applications; however, cache efficiency varies significantly with configuration choices [1]. Most production CDNs employ origin-pull caching, which minimizes storage requirements and operational complexity, but cache hit ratios and performance depend heavily on cache size, eviction policies, and content characteristics [2].
This project uses NS-3 network simulation to optimize origin-pull CDN configurations under realistic global traffic patterns. The simulation models a production application with origin servers in Azure East US serving users across North America (20ms baseline), Europe (80ms), Asia (180ms), and Australia (220ms), with edge nodes strategically placed in 8 geographic regions.
The research evaluates cache configurations ranging from 10GB to 500GB per edge node using three eviction policies: LRU (Least Recently Used), LFU (Least Frequently Used), and TTL-based expiration [5]. Content distribution reflects typical web applications: static assets (40%, highly cacheable), API responses (35%, conditionally cacheable with 5-minute TTL), HTML pages (20%, short TTL), and user-specific content (5%, non-cacheable).
Performance metrics include cache hit ratio by content type, Time-To-First-Byte (TTFB) improvement by geographic region, origin bandwidth reduction percentage, and storage efficiency across cache sizes [3]. Test scenarios examine steady-state traffic patterns, flash events (50x traffic spike for 2 hours simulating product launches), global cache invalidation during deployments, regional failover behaviour, and cold-start performance for new edge locations [4].
The research addresses practical questions such as: "What cache hit ratio justifies edge node deployment costs?" and "Does increasing cache size from 100GB to 500GB provide meaningful performance gains?" Expected results will quantify the relationship among cache configuration, performance improvements, and infrastructure costs [6], thereby enabling evidence-based decisions on CDN architecture to optimize global application delivery.
[1] E. Nygren, R. K. Sitaraman, and J. Sun, "The Akamai Network: A Platform for High-Performance Internet Applications," ACM SIGOPS Operating Systems Review, vol. 44, no. 3, pp. 2-19, Jul. 2010.
[2] J. Dilley, B. Maggs, J. Parikh, H. Prokop, R. Sitaraman, and B. Weihl, "Globally Distributed Content Delivery," IEEE Internet Computing, vol. 6, no. 5, pp. 50-58, Sep./Oct. 2002.
[3] S. Triukose, Z. Wen, and M. Rabinovich, "Measuring a Commercial Content Delivery Network," in Proc. 20th International Conference on World Wide Web (WWW), 2011, pp. 467-476.
[4] V. K. Adhikari, Y. Guo, F. Hao, M. Varvello, V. Hilt, M. Steiner, and Z. L. Zhang, "Unreeling Netflix: Understanding and Improving Multi-CDN Movie Delivery," in Proc. IEEE INFOCOM, 2012, pp. 1620-1628.
[5] S. Podlipnig and L. Böszörmenyi, "A Survey of Web Cache Replacement Strategies," ACM Computing Surveys, vol. 35, no. 4, pp. 374-398, Dec. 2003.
[6] D. S. Berger, P. Gland, S. Singla, and F. Cidon, "Exact Analysis of TTL Cache Networks," in Proc. ACM SIGMETRICS Performance Evaluation Review, vol. 42, no. 1, pp. 389-400, Jun. 2014.