Geo-Intelligent DNS Resolver Using Deep Learning

In the current-day Web infrastructure, DNS resolution plays a major role in optimizing the performance as well as user experience of networks. Conventional DNS resolvers remain completely geo-unaware, which might lead to truly poor routing decisions under greatly larger latency. The Geo-Smart DNS Resolver makes the DNS server choice based on client geolocation and other dynamic criteria, like current traffic flows, real-time traffic pattern, and deep learning-based predictive models[3]. For traffic forecasting, we have actually applied LSTM models. Furthermore, for selecting any server, we used Reinforcement Learning, and, as the geolocation correlator, MaxMind GeoIP. This methodology greatly improved load balancing through the utilization of actual traffic flows. In this fashion, our DNS resolver provides improved performance within DNS queries via shortening of the response time and optimizing of the server selection methods.

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Publication Details

Published
2025-07-04
DOI
https://doi.org/10.1109/icctdc64446.2025.11158842
Primary Topic
Sensor Technology and Measurement Systems
Type
article
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article

Geo-Intelligent DNS Resolver Using Deep Learning

P. Yamini Devi, K. Gopal, Ganesh Merugu, Jookanti Uday Sri Charan
Sensor Technology and Measurement Systems
article

Geo-Intelligent DNS Resolver Using Deep Learning

P. Yamini Devi, K. Gopal, Ganesh Merugu, Jookanti Uday Sri Charan
article en

Abstract

In the current-day Web infrastructure, DNS resolution plays a major role in optimizing the performance as well as user experience of networks. Conventional DNS resolvers remain completely geo-unaware, which might lead to truly poor routing decisions under greatly larger latency. The Geo-Smart DNS Resolver makes the DNS server choice based on client geolocation and other dynamic criteria, like current traffic flows, real-time traffic pattern, and deep learning-based predictive models[3]. For traffic forecasting, we have actually applied LSTM models. Furthermore, for selecting any server, we used Reinforcement Learning, and, as the geolocation correlator, MaxMind GeoIP. This methodology greatly improved load balancing through the utilization of actual traffic flows. In this fashion, our DNS resolver provides improved performance within DNS queries via shortening of the response time and optimizing of the server selection methods.

Chaitanya Bharathi Institute of Technology (IN)
Openalex Percentile: Top 70%
Sensor Technology and Measurement Systems
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