Challenges and Issues on Collecting and Analyzing Large Volumes of Network Data Measurements

This paper presents the main challenges and issues faced when collecting and analyzing a large volume of network data measurements. We refer in particular to data collected by means of Neubot, an open source project that uses active probes on the client side to measure the evolution of key network parameters over time to better understand the performance of end-users’ Internet connections. The measured data are already freely accessible and stored on Measurement Lab (M-Lab), an organization that provides dedicated resources to perform network measurements and diagnostics in the Internet. Given the ever increasing amount of data collected by the Neubot project as well as other similar projects hosted by M-Lab, it is necessary to improve the platform to efficiently handle the huge amount of data that is expected to come in the very near future, so that it can be used by researchers and end-users themselves to gain a better understanding of network behavior.