WiFox: Scaling WiFi Performance
for Large Audience Environments
Arpit Gupta,
Jeongki Min and Injong Rhee
NC State University
Interesting ??
WiFox:
AP-only S/W
solution
Faster WiFi !!
Manageable
solution !!
Large Audience Environments (LAEs)
Large Audience Environments
• Any location with a large WiFi user
population
• WBA projected a growth rate of
350% per year for such WiFi
deployments
• Various successful deployment
models such as Boingo-Google,
Mobily-Aruba etc. already exist
Source: WBA(Wireless Broadband Alliance)
Source: Wireless Broadband Alliance (WBA)
What about User Experience ?
As number of active clients increases, user experience
diminishes significantly
Problem Anatomy
Well Known Factors
• Contention and collision
– Increases with growing competition
• Rate Diversity
– Slower STA slows down all other STAs
– Various fairness realizations like WFQ, TBR
etc.
• Random Losses and TCP performance
– TCP treats packet losses as congestion signals
– Usage of TCP ECN and proxy servers isolate
wired and wireless networks
• Traffic Asymmetry
Traffic Asymmetry
Downlink Traffic dominates
for 90% of data traces
Traffic Asymmetry
Downlink Traffic dominates compared to uplink
Majority of data traffic
is Web based
Majority of data packets are for HTTP based web activities
Traffic Asymmetry
• In scope of our problem it is:
– Downlink/Uplink Asymmetry
– Channel Access Asymmetry
• Implications:
– Packets spend more time at AP’s TxQ
– Frequent packet drops
Channel access for uplink traffic is more
Wireless Channel
Uplink Traffic
Downlink Traffic
Performance Bottleneck
TxQ saturates as associated
clients increase
Associates Users
Goodput Performance
Traffic Asymmetry causes TxQ saturation
resulting in poor goodput performance
Possible Solutions
Wireless Channel
Uplink Traffic
Downlink Traffic
Equal Channel Access for Uplink/Downlink
Wireless Channel
Uplink Traffic
Downlink Traffic
Statically Assign Higher Priority to Downlink
Traffic
Wireless Channel
Uplink Traffic
Downlink Traffic
Dynamically Assign Higher Priority to Downlink
Traffic
Our Solution
Priority Control
STA A
STA B
Packet A
Class
CWmin ACK
CWmax
AP
STAs
1
5
DIFS
Busy medium
5
10
AIFS
TXOP Limit
1
64
N/A
N/A
N Slots
Wins
Contention
Smaller IFS
STA C
Busy medium
DIFS H
N Slots
Channel Access
Linear Scaling Priority Model
35
Goodput (Mbps)
30
25
Linear20relationship between Goodput and Priority Level
15
10
Priority Level
5
0
0
2
4
6
8
Number of Slots with High Priority
10
Adaptive Prioritization
Decision Points
100 ms
Time
Default Priority
D
H
D
H
D
D
High Priority
D
Priority Level 3
H
D
D
Evaluation
Test Bed
• 2600 Sqft Area with multiple APs, 45 STAs
• Netgear 802.11 b/g wireless cards with Atheros chipsets
and MADWIFI drivers
• Latency emulation using DummyNet
• Modified SURGE for web traffic generation
• Requests inter-arrival closely follows the ones observed
for SIGCOMM traces
• Uplink UDP traffic using Iperf to emulate Background
Traffic
Performance
Downlink: N/W Goodput
W/O WiFox
Significant improvement in Network’s Downlink Goodput
WiFox
Performance
• Experiment involves sending 25 requests and observe
response for 4 minutes duration
• Request Serving rate is 4 times better than NPC
Robustness
WiFox
Performance in presence of Multiple Aps ??
w/o WiFox
Robustness
w/o WiFox
Unfair Distribution
Fairness Realization ??
WiFox
Performance: TxQ Dynamics
w/o WiFox
WiFox
Conclusion
• WiFox Delivers:
– Deployment Ready Solution
– Enhanced user experience with
• 400-700% Downlink Goodput improvements
• 40-60% faster response time
• Open Problems:
– Characterizing asymmetry problem for 802.11n
– Support for real time applications like chats
etc.
– QoS
Merci !!
30
Multi AP Scenario
D
D
D
D
D
D
AP 1 ( Priority Level 4)
D
D
D
100 ms
D
D
D
D
AP 2 ( Priority Level 3)
time
D
D
D
D
D
D
AP 1 ( Priority Level 3)
D
D
D
D
D
AP 2 ( Priority Level 5)
D
Performance: Insight
• Enables AP to switch to HIGH priority state under heavy load
• Avoids TxQ saturation
• Significant reduction in ReTx rate compared to stock WiFi
implementation
Robustness: Uplink Traffic
• Scenarios where few users indulge in heavy uplink activities like video uploading,
cloud synchronization etc.
Observations
Source: Rodrig et al.