Content retrieval using cloud-based DNS

Abstract

Abstract-Cloud-computing systems are rapidly gaining momentum, providing flexible alternatives to many services. We study the Domain Name System (DNS) service, used to convert host names to IP addresses, which has historically been provided by a client's Internet Service Provider (ISP). With the advent of cloud-based DNS providers such as Google and OpenDNS, clients are increasingly using these DNS systems for URL and other name resolution.Performance degradation with cloud-based DNS has been reported, especially when accessing content hosted on highly distributed CDNs like Akamai. In this work, we investigate this problem in depth using Akamai as the content provider and Google DNS as the cloud-based DNS system. We demonstrate that the problem is rooted in the disparity between the number and location of servers of the two providers, and develop a new technique for geolocating data centers of cloud providers. Additionally, we explore the design space of methods for cloudbased DNS systems to be effective. Client-side, cloud-side, and hybrid approaches are presented and compared, with the goal of achieving the best client-perceived performance. Our work yields valuable insight into Akamai's DNS system, revealing previously unknown features.

namehelp

“…Several studies have shown the potential advantages of a "personalized" selection of DNS servers based on responsiveness [1,3,4]. The close relationship between many web applications and DNS demands a careful analysis of Copyright is held by the author/owner(s).…”

A Tutorial on Network Latency and Its Measurements

“…For accurate measurements, end hosts at strategic locations are used (Francis, et al, 2001), latency is estimated based on coordinated using landmark hosts (Ng & Zhang, 2001) or DNS queries (Gummadi, Saroiu, & S., 2002), or routing topology (Dabek, Cox, Kaashoek, & Morris, 2004) (H. Madhyastha, 2006). Measured latencies also help select target servers to achieve specified optimization goals in routing, content distribution networks, and cloud computing (Wendell, Jiang, Freedman, & Rexford, 2010) (Khosla, Fahmy, & Hu, 2012) (Ding, Chen, T., & Fu, 2010). Their objective function is to minimize the total execution time and select best replica servers considering server loads, cost and locations.…”