SelfManagement in Chaotic Wireless Deployments

1
Self-Management in Chaotic Wireless Deployments

• Aditya Akella, Glenn Judd,
• Srini Seshan, Peter Steenkiste
• Presented by
• Farhana Ashraf

2
Wireless Proliferation

• Sharp increase in deployment
• Airports, malls, coffee shops, homes
• 4.5 million APs sold in 3rd quarter of 2004!

3
Change in Wireless Landscape
UNPLANNED and UNMANAGED
PLANNED and MANAGED
CHAOTIC NETWORK!!!
4
Outline

• Quantify characteristics of chaotic wireless
  deployment
• Impact on end-user performance
• Initial work on mitigating negative effects
• Conclusion

5
Characterizing Current Deployments
6
1. AP Degree Place Lab
City
Max.degree
AP
A
B
C
7
Degree Distribution Place Lab
8
2. Unmanaged APs WifiMaps
Channel
AP

• Most users dont change default channel
• Channel selection must be automated

9
3. AP Management Support Wardrive
Vendor
AP

• Major vendors dominate
• Incentive to reduce vendor self interference

10
Outline

• Quantify characteristics of chaotic wireless
  deployment
• Impact on end-user performance
• Initial work on mitigating negative effects
• Conclusion

11
Impact on Performance Globosim Trace-driven
simulation on Wardrive Data set

• 20 APs in topology
• Each AP has D clients
• Each client runs HTTP/FTP workloads
• Vary stretch s ? scaling for inter-AP distances

12
Impact on HTTP Performance
3 clients per AP. 2 clients run FTP sessions.
All others run HTTP.300 seconds
5s sleep time
Degradation
20s sleep time
Max interference
No interference
13
Optimal Channel Allocation vs.Optimal Channel
Allocation Tx Power Control
Channel Only
Channel Tx Power Control
14
Impact of Joint Transmit Power and Rate Control
Objective given ltload, txPower, dclientgt
determine dmin
APs
15
Impact of Transmit Power Control

• Minimum distance decreases dramatically with
  transmit power
• High AP densities and loads requires transmit
  power lt 0 dBm
• Highest densities require very low power ? cant
  use 11Mbps!

16
Outline

• Quantify characteristics of wireless deployment
• Impact on end-user performance
• Initial work on mitigating negative effects
• Conclusion

17
Power and Rate Selection Algorithms

• Fixed-Power Rate Selection
• Auto Rate Fallback ARF
• Based on probe
• Estimated Rate Fallback ERF
• Based on SNR

DATA
If ACK fails, Decrease rate
If success, Increase rate
B
A
ACK
18
Power and Rate Selection Algorithms

• Adaptive-Power Rate Selection
• Sender reduces power as long as rate is not
  reduced
• Extension to Fixed-Power Rate selection
• Power Auto Rate Fallback PARF
• Power Estimated Rate Fallback PERF

19
Lab Interference Test
Topology
Results
20
Conclusion

• Significant densities of APs in many metro areas
• Many APs not managed
• High densities could seriously affect performance
• Static channel allocation alone does not solve
  the problem
• Transmit power along with adaptive rate control
  effective at reducing impact