1. NETWORK TRAFFIC Jeffrey Klow, Paul German, Emily Andrulis, and Ben Oakley

2. Getting the Data  Talk to the Tims  Decreasing resolution -> Ask for additional data sets for each day  Find out bandwidth

3. Loading into R  Merging both internet providers  Changing UNIX timestamp  Removing first row header  Add variable for percentage of bandwidth

5. Future Data Issues  Still have incoming data until Wednesday  Merging into one big data set  Megabytes vs. megabits for max bandwidth

6. What do we want to know?  What does internet usage look like for the average week at Cornell?  When is there the most network traffic? What day? What time?  When is there the least network traffic? What day? What time?  What time slots use the maximum amount of bandwidth?  What percentage of our total bandwidth are we using throughout the day?  How does this compare for different days in the same week?  How does this compare across different months in the year?

7. A First Look at the Data  Noticed spikes at midnight and 9-11 AM  Preliminary graphs

9. Visualizing the Data  Static graphs  Plotting usage over time in one day, using different colors to represent upload/dowload averages and maximums of both primary and secondary providers  Plotting usage over year long time  Plotting usage of many days in the same 24 hour time span  Comparing boxplots of the data usage for different days in the week

10. Advanced Graphics  Animated Graphs  Plotting usage over a two day time period, where the area under the line fills over time  Interactive Graphs  Allow user to set the day and time of day and then show the average incoming and outgoing data usage, and the maximum incoming and outgoing

11. Working as a Team!  Emily  Static visuals  Jeff  Animated visuals, merging the data  Paul  Interactive visuals

12. Questions? Suggestions?