network traffic paul german, jeffrey klow, and emily andrulis

NETWORK TRAFFICPaul 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