NETWORK TRAFFIC Paul German, Jeffrey Klow, and Emily Andrulis THE IDEA Ben’s proposal Examine Cornell’s Network Traffic How much do we use? When do we use it? What information can we glean? OUR MAIN QUESTIONS What does an average day at Cornell look like in regards to network traffic? Assuming the pattern holds, at what point should we consider getting more bandwidth because we will be frequently coming close to our maximum allotted? GETTING THE DATA The Tims in Network Services Log data files for primary and secondary internet provider, and internal network traffic Log files include upload and download averages and maximums Decreasing time resolution between lines Solution: Collect data for 1 week around same time each day DATA CLEANING Create scripts in R log file -> data frames in R Update already made data frames with new log data Add different time variables UNIX -> CST, date, time, weekday, decimal time Add % of bandwidth variables Helper functions getSelectedIndices modifyDataResolution TELLING THE STORY Use static, animated, and interactive graphs to display data Go back to our focus questions: Average day at Cornell? Frequency of reaching 85% bandwidth? What does the future usage look like? EXPLAINING THREE TYPES Log files from primary internet provider, secondary internet provider, and internal network traffic Cap differences: 300 Mb/sec vs. 100 Mb/sec Internal weird AVERAGE USAGE AT CORNELL Static -> Interactive AVERAGE USAGE SECONDARY AVERAGES THROUGH ANIMATION Day of Week compared to Average Day AVERAGE LAST WEEK Average Day compared to Days Last Week AVERAGES SINCE NOVEMBER Average Day compared to all days back to November AVERAGE BLOCK USAGE Showing Usage over Block 4 BLOCK 4 SECONDARY Block 4 Usage on Secondary Provider (Note: peaks) WHERE ARE WE HEADING? FUTURE APPLICATIONS Give code to the Tims Documented and split up by task Interactive graphs with new data Easily replicable Raise awareness about usage in terms of averages and when we’re nearing the cap
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