April 2009 doc.: IEEE 802.19-09/xxxxr0 May 2014 IEEE 802.11ax High Efficiency WLAN Packet measurements around Boulder, CO Date: 2014-05-11 Authors: Jim Lansford, CSR Technology Rich Kennedy, Research In Motion

April 2009 doc.: IEEE 802.19-09/xxxxr0 May 2014 Overview 15 Students captured packets using NetworkMonitor + Wireshark – recorded time, data rate, packet size Sorted by data rate and packet size Generated histograms of data rate vs packet size using at least 10,000 packets On campus (Cisco managed network: controller+lightweight APs) Apartment or dormitory Pearl Street (heavy retail/commercial deployment) Raw data available for other analysis Detailed packet information (all header info): Each packet logged with elapsed time, data rate, size, SNR, MAC address, IP address, etc. Freely available on public box.com folder as a zip file Next steps – traffic model based on sum of sorted data models for traffic types Jim Lansford, CSR Technology Rich Kennedy, Research In Motion

Assignment Use Microsoft Network Monitor 3.4 to capture packets. May 2014 Assignment Use Microsoft Network Monitor 3.4 to capture packets. Save the captured data as .cap file and open the file through Wireshark. Export the data from Wireshark and load it into an Excel spreadsheet Using these data, draw a 2-D histogram of packet size vs data rate.   Capture the data and generate the 2-D histograms in three different locations: Residential area (home, apartment, or dorm room) On campus (in an office building if you are an off-campus student) In a mall area, such as Pearl Street or the corner of 28th and Arapahoe in Boulder. Any mall or strip mall with numerous APs and STAs Jim Lansford, CSR Technology

Sample Wireshark trace (Pearl Street) May 2014 Sample Wireshark trace (Pearl Street) Jim Lansford, CSR Technology

Pearl Street – heavy retail/commercial May 2014 Pearl Street – heavy retail/commercial Data rate Jim Lansford, CSR Technology

Heavy retail/commercial May 2014 Heavy retail/commercial Data rate Jim Lansford, CSR Technology

On CU-Boulder campus (managed network) May 2014 On CU-Boulder campus (managed network) Jim Lansford, CSR Technology

Managed enterprise network May 2014 Managed enterprise network Jim Lansford, CSR Technology

Residential neighborhood (apartments) May 2014 Residential neighborhood (apartments) Data rate Jim Lansford, CSR Technology

Residential neighborhood (apartments) May 2014 Residential neighborhood (apartments) Data rate Jim Lansford, CSR Technology

Future work S Use packet traffic to build models May 2014 Future work Generator 1 Generator 2 S Generator 3  Generator N Use packet traffic to build models Packet generator for different data rates Beacons at 1 or 6Mbps: small, periodic packets Video at max rate: large, periodic packets Need to look more closely at distribution of arrivals (not Poisson!) Packet traffic model can be used to evaluate 11ax proposals Jim Lansford, CSR Technology

Acknowledgements & Raw data availability May 2014 Acknowledgements & Raw data availability Several students volunteered to make their raw data available to anyone for additional analysis Box: https://app.box.com/s/zc5sqgccg5aba58y5ur5 Data contributed by: Sagar Sidhpura Sagar.Sidhpura@Colorado.EDU Nadia Yoza Mitsuishi Nadia.YozaMitsuishi@Colorado.EDU Swetha Natham Swetha.Natham@Colorado.EDU Jay Rao Jay.Rao@Colorado.EDU Special thanks to Prof. Doug Sicker and: Jim Lansford, CSR Technology

Summary Mostly what you would expect: Some surprises May 2014 Summary Mostly what you would expect: Heavily congested areas have mostly low rates and small packets Lots of big packets in residential (video?) Some residential environments were more congested than others Some surprises Lots of small, low rate packets (beacons?) in a managed environment A great deal more analysis could be done Raw files allow more detailed analysis Could be used to develop better packet traffic models Raw data freely available without restriction Anyone is welcome to do more analysis or traffic modeling Jim Lansford, CSR Technology