Prefix Top Lists: Gaining Insights with Prefixes from Domain-based Top Lists on DNS Deployment

Abstract

Domain-based top lists such as the Alexa Top 1M strive to portray the popularity of web domains. Even though their shortcomings (e.g., instability, no aggregation, lack of weights) have been pointed out, domain-based top lists still are an important element of Internet measurement studies. In this paper we present the concept of prefix top lists, which ameliorate some of the shortcomings, while providing insights into the importance of addresses of domain-based top lists. With prefix top lists we aggregate domain-based top lists into network prefixes and apply a Zipf distribution to assign weights to each prefix. In our analysis we find that different domain-based top lists provide differentiated views on Internet prefixes. In addition, we observe very small weight changes over time. We leverage prefix top lists to conduct an evaluation of the DNS to classify the deployment quality of domains. We show that popular domains adhere to name server recommendations for IPv4, but IPv6 compliance is still lacking. Finally, we provide these enhanced and more stable prefix top lists to fellow researchers which can use them to obtain more representative measurement results.