| Summary: | As more applications rely on distributed systems (peer-to-peer services, content distribution networks, cloud services), it becomes necessary to identify hosts that return content to the user with minimal delay. A large scale map of delays would aid in solving this problem. Existing methods, which deploy devices to every region of the Internet or use of a single vantage point have yet to create such a map. While services such as PlanetLab offer a distributed network for measurements, they only cover 0.3% of the Internet. The focus of our research is to increase the speed of the single vantage point approach so that it becomes a feasible solution.
We evaluate the feasibility of performing large scale measurements by performing an experiment using more hosts than any previous study. First, an efficient scanning algorithm is developed to perform the measurement scan. We then find that a custom Windows network driver is required to overcome bottlenecks in the operating system. After developing a custom driver, we perform a measurement scan larger than any previous study. Analysis of the results reveals previously unidentified drawbacks to the existing architectures and measurement methodologies. We propose novel meth- ods for increasing the speed of experiments, improving the accuracy of measurement results, and reducing the amount of traffic generated by the scan. Finally, we present architectures for performing an Internet scale measurement scan.
We found that with custom drivers, the Windows operating system is a capable platform for performing large scale measurements. Scan results showed that in the eleven years since the original measurement technique was developed, the response patterns it relied upon had changed from what was expected. With our suggested improvements to the measurement algorithm and proposed scanning architectures, it may be possible to perform Internet scale measurement studies in the future.
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