1. technology and computing

May 2014
doc.: IEEE 802.11-14/0546r1
IEEE 802.11ax
High Efficiency WLAN
Packet measurements around Boulder, CO
Date: 2014-05-11
Authors:
Name
Affiliations Address
Jim Lansford
CSR
Technology
Submission
Phone
100 Stirrup Circle
+1 719 286 9277
Florissant, CO 80816
Slide 1
email
Jim.lansford@ieee.org
Jim Lansford, CSR Technology
May 2014
doc.: IEEE 802.11-14/0546r1
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
Submission
Slide 2
Jim Lansford, CSR Technology
May 2014
doc.: IEEE 802.11-14/0546r1
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
– NOTE: The data date seems to get multiplied by two when importing
into Excel!!
• 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
Submission
Slide 3
Jim Lansford, CSR Technology
May 2014
doc.: IEEE 802.11-14/0546r1
Sample Wireshark trace (Pearl Street)
Submission
Slide 4
Jim Lansford, CSR Technology
May 2014
doc.: IEEE 802.11-14/0546r1
Pearl Street – heavy retail/commercial
Submission
Jim Lansford, CSR Technology
May 2014
doc.: IEEE 802.11-14/0546r1
Heavy retail/commercial
Submission
Slide 6
Jim Lansford, CSR Technology
May 2014
doc.: IEEE 802.11-14/0546r1
On CU-Boulder campus (managed network)
Submission
Slide 7
Jim Lansford, CSR Technology
May 2014
doc.: IEEE 802.11-14/0546r1
Managed enterprise network
Submission
Slide 8
Jim Lansford, CSR Technology
May 2014
doc.: IEEE 802.11-14/0546r1
Residential neighborhood (apartments)
Submission
Slide 9
Jim Lansford, CSR Technology
May 2014
doc.: IEEE 802.11-14/0546r1
Residential neighborhood (apartments)
Submission
Slide 10
Jim Lansford, CSR Technology
May 2014
doc.: IEEE 802.11-14/0546r1
Future work
Generator 1
Generator 2
Generator 3
S



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
Submission
Slide 11
Jim Lansford, CSR Technology
May 2014
doc.: IEEE 802.11-14/0546r1
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:
Submission
Slide 12
Jim Lansford, CSR Technology
May 2014
doc.: IEEE 802.11-14/0546r1
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
Submission
Slide 13
Jim Lansford, CSR Technology