|Di Xiao||Texas A&M, USA|
|Xiaoyong Li||Texas A&M University, USA|
|Daren Cline||Texas A&M University, USA|
|Dmitri Loguinov||Texas A&M University, USA|
Since inception, DNS has used a TTL-based re-plication scheme that allows the source (i.e., an authoritative domain server) to control the frequency of record eviction from client caches. Existing studies of DNS predominantly focus on reducing query latency and source bandwidth, both of which are optimized by increasing the cache hit rate. However, this causes less-frequent contacts with the source and results in higher staleness of retrieved records. Given high data-churn rates at certain providers (e.g., dynamic DNS, CDNs) and importance of consistency to their clients, we propose that cache models include the probability of freshness as an integral performance measure. We derive this metric under general update/download processes and present a novel framework for measuring its value using remote observation (i.e., without access to the source or the cache). Besides freshness, our methods can estimate the inter-update distribution of DNS records, cache hit rate, distribution of TTL, and query arrival rate from other clients. Furthermore, these algorithms do not require any changes to the existing infrastructure/protocols.