Optimal Collaborative
Access Point Association
In Wireless Networks
Ouldooz Baghban Karimi
School of Computing Science
Simon Fraser University
Jiangchuan Liu
School of Computing Science
Simon Fraser University
INFOCOM 2014
Jennifer Rexford
Department of Computer Science
Princeton University
Increase in Mobile Data Usage

Not Enough Wireless Resources

Increase in Mobile Traffic
 52% Increase over a period of a year

More offloading from cellular
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Popularity of Wireless Local Area Networks

Dense availability of WiFi resources
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Data collected in Greater Vancouver urban residential area
High availability of resources
Low availability of owned resources

Wasting excess/unused resources
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WiFi Popularity: Real-World Example
20
25
15
15
Usage
Access Points
20
10
10
5
5
0
54
65
130
144
150
300
0
1
2
3

Insights on Collected Data




Number of access points
Co-channel access points
Ineffective association based on highest
signal quality
Interference and collision
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5
6
7
8
9 10 11
Channels
Maximum Rate

Same Upstream Internet Service Provider


Collaboration: sharing excess WiFi Capacity

Private Access Point + Hot Spot
Optimal collaborative access point association

Centralized
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Centralized Access Optimization
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Association Problem

System Components

Users

Access Points


Local access point
 Provides access to its registered devices

Host access point
 Provides access to external nodes
 Services quality for local users
Shared upstream provider

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Opportunity



Centralized access optimization
Clustering
Reduced billing complexity
Limitations

No central control over


Deployment
Sharing limits
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Example
(a) Link Capacities
(c) Optimal Collaborative Association
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(b) Non-collaborative
(d) Optimal Collaborative
with Concurrent Associations
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Proportional Fair Access Point Association


Network Utility Maximization (NUM) Framework

Proportional Fairness [Li et al., 2008]
Maximize throughput: Proportional fair
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Subject to



Time/medium sharing among co-channel access points
Time/medium sharing among users on the same access point
Limit for external users
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PF with Sharing Results

Placement of access points based on measurement data

Increased Overall throughput

Dropped rate experienced only at a few high-rate users
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PF with Sharing Results


Increased throughput with increase in the number of access points


Maintain collision
Concurrent connections
Maintain throughput with increased users per access point
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Unused extra access points
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PF with Sharing Results

Define cost of association

Higher external cost of association solves the dropped rate problem
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Conclusion

Higher mobile data usage requires higher wireless resources

Dense, accessible, and inexpensive WLAN resources

Measurements to confirm

Offload from cellular networks to dense WLAN networks

Challenges & Solutions in WLANS

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Collaborative access
Centralized association optimization in upstream provider
Used measurements for simulations
Up to 140% throughput increase
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Thank you!
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