Network measurement is an important tool in network research and operations, and is increasingly utilized in end-user applications. However, active measurements compete with other applications for limited network resources. These measurements are typically performed by individual users and applications, with limited coordination or planning. This dissertation addresses network measurement in the context of a measurement infrastructure, which can coordinate measurements, monitor and control their resource consumption, and even improve the quality of measurement results. We address three specific areas of operation in a measurement infrastructure. We present an architecture for an infrastructure that uses admission control to bound the resource consumption of measurements. We use estimates of the resources consumed by real-world measurement tools in the admission control mechanism. We evaluate methods of estimating the resource consumption of measurements in terms of network bandwidth, and show that these estimates are important to the accuracy of admission control. We propose several algorithms for determining when network measurements can be replaced by a network inference mechanism to reduce measurement load in the network at a cost of measurement accuracy. We experimentally evaluate these algorithms on measurement patterns designed to present difficulties, measurement patterns based on real-world peer-to-peer distributed communication, and random measurements. We show that the algorithms successfully reduce the measurement load on the first two types of graphs, and that they do not incur undue expense on the latter. We design and evaluate a family of methods for selecting vantage points from which to take active measurements to increase reachability into the Internet. We show that two of these methods perform substantially better than selecting vantage points at random, allowing a larger number of hosts to be probed with direct measurements with the same number of vantage points.

Researchers should cite this work as follows:

• Ethan L Blanton (2012). Controlling the cost and increasing the utility of network measurement infrastructures. Purdue University Research Repository. doi:10.4231/D3TH8BM5D

  BibTex | EndNote

1. Computer Science
2. Computer Science (Dept)
3. Inference
4. Internet

This data set contains the raw data from Chapter 5 of the dissertation.