A Measurement Study of DNS Query Protocols in Mobile Networks: Efficiency, Reliability and Choice

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Liangyi Gong, Sai Wang, Lanqi Yang, Chun Long, Xiaochen Fan, Daibo Liu, Changhua Pei

Published: 2024, Last Modified: 17 Jan 2026MSN 2024EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: The Domain Name System (DNS) runs as a fundamental infrastructure of the mobile Internet. Various DNS protocols employed in the current network ecology can be predominantly classified as unencrypted DNS and encrypted DNS. However, existing research mainly focuses on assessing DNS performance within conventional internet structures, neglecting their evaluation in mobile contexts. In our pioneering study examining DNS within mobile networks, we developed an Android-based application to evaluate the efficiency and reliability of DNS protocols. The App issues nine domain name lookups to four cloud DNS providers supporting unencrypted and encrypted DNS protocols. Collaborating with volunteers from four countries, we collected about 52,000 test records. Our findings reveal substantial variability in the efficiency and reliability of all DNS protocols across different mobile scenarios. Overall, encrypted DNS protocols exhibit superior efficiency compared to plaintext DNS when oriented towards cloud DNS resolvers. In high-speed mobile scenarios, all DNS protocols demonstrate reduced efficiency, with encrypted DNS protocols showing relatively higher reliability. Our broad-scale measurement results indicate that the performance of DNS protocols varies across mobile contexts, but users are typically uninformed about these differences and do not realize how to break free. Intending to assist users in selecting an optimal DNS protocol, we propose a protocol choice model based on auto-encoding LSTM networks which leverages features of networking and protocols to predict the most suitable DNS protocol with reduced query time and enhanced reliability in the current scenario. Notably, we have achieved the prediction of the optimal DNS protocol for the future by foreseeing the network status ahead. Empirical results demonstrate an impressive 98.73% accuracy in prediction of DNS protocol selection.