Computer Science Department
School of Computer Science, Carnegie Mellon University
Discovery and Application of Network Information
The low-level details obtained directly from network components provide the information needed by distributed applications to adapt themselves to modern network environments. Low-level access overcomes the limitations inherent in benchmarking by providing a scalable, non-invasive measurement technique that provides network topology information while continuing to support the predictions of end-to-end application performance available through benchmarking. In this dissertation, I address the need for low-level information, the feasibility of providing it through an application-level interface, the accuracy of end-to-end predictions made provided by low-level information, and the topology discovery capabilities using low-level information. The topology discovery algorithms I present are the first to use the incomplete information available through network components and are provably good with minimal knowledge. My research demonstrates that violating the end-to-end networking abstraction by providing applications with access to low-level network knowledge meets the needs of many applications and is feasible on modern networks.