Wireless Network Mobility and Visualization

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Wireless Network Mobility and Visualization

• Ola Nordstrom
• Lei Li
• Jamie Booth

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Outline

• Analysis of a Local-Area Wireless Network
• Mobility
• User behaviors
• Metricom Radio Network
• More Mobile Environment
• University of Kansas Signal Strength
• ATT Swift3D
• Lanline realtime visualization

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University Wireless Network

• 12 week trace of Stanford University
• 74 Users (small by todays standards)
• Analysis done by collecting
• MAC and IP headers from APs
• SNMP queries to APs returned MACs of hosts
• Authentication logs enabled MAC to User
  identification

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Stanford Study Goals

• When and how do people use the network
• Utilization
• Applications
• Throughput
• Number of users
• Mobility
• Do people move?
• How do they move (any patters)?

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Average Number of Users
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Mobile vs. Stationary Users
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2b phd student offices
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User Communities

• Users typically fit into groups
• Web and session apps (ssh, telnet) typically run
  together
• Different users differ across time
• No single application mix that fits all the time
• User variety
• One user connected to 5 hosts another to 3054
  over the 12 week period!

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User Communities
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Traffic Characteristics
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Application usage by No. of Pkts
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Packets and bytes (in millions)
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University Study Results

• Most users do not move much within a building
• Few users are Highly Mobile
• Users are best categorized into subgroups
• Regarding movement, activity, traffic load

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Metricom packet radio network

• A Metropolitan-Area Wireless Network
• More mobile environment than campus wireless
  network
• Infrastructure 128kbps
• radio, poletop, repeater, wired AP
• Events logged Registration, Query

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Network Behavior

• When is the network the most active?
• How active does the network get?
• Where is the network the most active?

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When is the network the most active?
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When is the network the most active?
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How active is the network?
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Where is the network the most active?
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Radio Mobility

• How often do radios move?
• How far do they move?
• Can we identify patterns of mobility?

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How often do radios move?
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How far do radios move?
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How far do radios move
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Mobility pattern
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Visualize it

• OK. We have all this data. Now what do we do
  with it?

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Signal Strength Mapping

• University of Kansas
• Collect discrete data points
• Perform interpolation to approximate wireless
  signal field
• Overlay generated field on aerial photos

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Measured Data Values
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Overlay on Aerial Photo
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Final Version
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Mapping Multiple Access Points
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ATT Swift3D

• Landline Network
• Real Time Visualization
• Run on a cluster of SGI Origin 2000s
• Generate both 2D and 3D images
• Ability to rotate 3D models

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Usage Graph
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Find effected customers
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Finding Dial-up Internet Usage
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VPN Traffic
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Visualization References

• ATT Swift3D
• http//www.research.att.com/areas/visualization/pr
  ojects_software/swift3d.html
• University of Kansas Wireless Network
  Visualization
• http//www.ittc.ku.edu/wlan/

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Questions?