The potential costs and benefits of long-term prefetching for content distribution

This paper examines the costs and potential benefits of long-term prefetching for content distribution. In traditional short-term prefetching, caches use recent access history to predict and prefetch objects likely to be referenced in the near future. In contrast, long-term prefetching uses long-term steady-state object access rates and update frequencies to identify objects to replicate to content distribution locations. Compared to demand caching, long-term prefetching increases network bandwidth and disk space costs but may benefit a system by improving hit rates. Using analytic models and trace-based simulations, we examine algorithms for selecting objects for long-term prefetching. We find that although the Zipf-like popularity distribution of web objects makes it challenging to prefetch enough objects to significantly improve hit rates, systems can achieve significant benefits at modest costs by focusing on long-lived objects.

• Type: Journal
• Year: 2002
• Where: COMCOM
• Authors: Arun Venkataramani, Praveen Yalagandula, Ravi Kokku, Sadia Sharif, Michael Dahlin
• Keywords: COMCOM 2002, Long-term, Long-term Prefetching Uses, Long-term Steady-state Object