Scalable techniques for memory-efficient CDN simulations

Since CDN simulations are known to be highly memory-intensive, in this paper, we argue the need for reducing the memory requirements of such simulations. We propose a novel memory-efficient data structure that stores cache state for a small subset of popular objects accurately and uses approximations for storing the state for the remaining objects. Since popular objects receive a large fraction of the requests while less frequently accessed objects consume much of the memory space, this approach yields large memory savings and reduces errors. We use bloom filters to store approximate state and show that careful choice of parameters can substantially reduce the probability of errors due to approximations. We implement our techniques into a user library for constructing proxy caches in CDN simulators. Our experimental results show up to an order of magnitude reduction in memory requirements of CDN simulations, while incurring a 5?10% error.

• Type: Conference
• Year: 2003
• Where: WWW
• Authors: Purushottam Kulkarni, Prashant J. Shenoy, Weibo Gong
• Keywords: CDN Simulations, CDN Simulators, Internet Technology, Large Memory Savings, WWW 2003