Special Issue of Computer Networks on "Traffic and Performance in the Big Data Era", 27 June 2016
Resources such as Web pages or videos that are published in the Internet are referred
to by their Uniform Resource Locator (URL). If a user accesses a resource
via its URL, the host name part of the URL needs to be translated into a routable
IP address. This translation is performed by the Domain Name System service
(DNS). DNS also plays an important role when Content Distribution Networks
(CDNs) are used to host replicas of popular objects on multiple servers that are
located in geographically different areas. A CDN makes use of the DNS service to
infer client location and direct the client request to the optimal server. While most
Internet Service Providers (ISPs) offer a DNS service to their customers, clients
may instead use a public DNS service. The choice of the DNS service can impact
the performance of clients when retrieving a resource from a given CDN. In this
paper we study the impact on download performance for clients using either the
DNS service of their ISP or the public DNS service provided by Google DNS.We
adopt a causal approach that exposes the structural dependencies of the different
parameters impacted by the DNS service used and we show how to model these
dependencies with a Bayesian network. The Bayesian network allows us to explain
and quantify the performance benefits seen by clients when using the DNS
service of their ISP. We also discuss how the further improve client performance.
Type:
Journal
Date:
2016-06-27
Department:
Data Science
Eurecom Ref:
4940
Copyright:
© Elsevier. Personal use of this material is permitted. The definitive version of this paper was published in Special Issue of Computer Networks on "Traffic and Performance in the Big Data Era", 27 June 2016 and is available at : http://dx.doi.org/10.1016/j.comnet.2016.06.023
See also:
