The initial proposal to research Cornell's Network Traffic was presented by Ben Oakley for the CSC/STA 255 "Dealing with Data" class. Upon hearing the idea, Jeffrey Klow, Paul German, and Emily Andrulis decided to come on board and dig into the data. With help from the Tims in the IT department, they were able to use log files tracking the network usage on Cornell's campus with high resolution for a week, and lower resolution that goes back to November.
To learn more about everyone involved with the Network Traffic Project check out the information below. We would like to give a big thanks to the Tims for all their help with supplying us data and information about the network, as well as Ann and Ross for continuously helping us create our visualizations and fix our R code during class periods.
Emily is a junior and computer science major. She was interested in this project because of its real world application with better informing our IT department about our network traffic and data usage. Throughout the project she has been our scribe and presentation manger, writing up our final papers and creating our power points as well as creating and organizing our web page. She also stepped up as our main contact with the Tims after Ben's absence, and in the last week she has contributed most with the static graphs and overall analysis for our conclusions and future work section.
Paul is a senior and computer science major. Paul has contributed to the Network Traffic Project through his help coding the scripts to make the R data frames and create the first graphs for our group proposal. Most notably, Paul has been the driving force behind our interactive graphs and he has been the one to make everything for our Shiny applications.
Jeff is a sophomore who is interested in computer science. Throughout the project, Jeff has been the one charging ahead with coding our scripts and creating more functions or variables in R that would help us all out when trying to work with the data later on. Almost all the work from the func.R and updateLogDF.R scripts can be credited to him, and he has been the one we know we can turn to if we need some savvy coding to get us out of a bind. With our visualizations, he worked mainly on creating our animated graphs, but he also made contributions to our other graphs by fixing axes labels and adding average loess curves to some.
Ben is a sophomore at Cornell. He can be credited as the original idea man for the Network Traffic Project, since it was his initial proposal that convinced the rest of the team that this was a worthwhile venture for our main project. Unfortunately, Ben's contributions to the Network Traffic Project were short lived, and he has not been able to help assist us in our efforts since his first presentation.
Time Weber (left) and Tim Messick (right), collectively known as "the Tims", both work in the IT department for Cornell College as the Network Engineer and Client/Server Integration Specialist respectively. They can be found working together in the Network Services Office in Law 306D. In the initial project proposal, Ben went to the Tims with an idea that he might be able to analyse the school's network traffic if they could provide him with the data he needed. Luckily for Ben and the rest of us, the Tims have been nothing but helpful each step of the way. Providing us with new log files every day around the same time for a week and answering any and all of questions throughout the process, we cannot thank them enough for all their assistance. Our project would not have been possible without them.
Professors Ann Cannon (left) and Ross Sowell (right) worked together to co-teach
the "Dealing with Data" course for the first time this year. Ann Cannon is Cornell's
resident Statistician and has been leading the Statistics half of the course, while Ross
Sowell is a Computer Science Professor who is teaching the coding portion of the class.
Throughout our project both Ann and Ross have been a continuous source of assistance and
encouragement, providing us with helpful feedback and pointing us in the right direction
for coding and analysis questions. We really appreciate their help and owe them a big thanks!