Doctor of Philosophy, Case Western Reserve University, 2014, EECS - Computer and Information Sciences
Network measurement is crucial for ensuring Internet's effective operation, security, and continued development. However, collecting representative measurements in a complex infrastructure like the Internet is extremely challenging. To address this challenge, we propose a novel approach to provide focused, on-demand Internet measurements called DipZoom (for Deep Internet Performance Zoom). Unlike prior approaches that face a difficulty in building a measurement platform with sufficiently
diverse measurements and measuring hosts, DipZoom implements a matchmaking
service, which uses P2P concepts to bring together experimenters in need of measurements and external measurement providers.
Further, to demonstrate the utility of DipZoom as a tool for real-world research, we use it to answer some of the challenging questions regarding Internet operation.
Specifically, we use DipZoom to conduct an extensive study of content delivery networks (CDN ), which are among the key components of today Internet infrastructure. in performance, security, and improvement aspects.
First, we conduct a large-scale performance study of the CDN platform operated by the leading DNS service provider. The study's result shows that the number of worldwide data centers in CDN platform could be significantly reduced without affecting the content delivery performance. Therefore, system designers can decide on the number of data centers to meet their other objectives without having to worry about performance degradation.
Second, we used some measuring techniques developed for the above performance study to uncover a significant security vulnerability in CDNs. We showed that several CDNs, including commercial CDNs, not only left their customers vulnerable to the application-level denial of service attack, but CDNs themselves are also susceptible to be recruited to amplify the attack.
Finally, based on insights gained in our CDN studies, we propose an approach to improve the cont (open full item for complete abstract)
Committee: MICHAEL RABINOVICH (Advisor); TEKIN OZSOYOGLU (Committee Member); SHUDONG JIN (Committee Member); VIRA CHANKONG (Committee Member); MARK ALLMAN (Committee Member)
Subjects: Computer Science