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Fat Virtual Access Points

Discover how Fat Virtual Access Points overcome bandwidth limitations by aggregating connections from multiple nearby APs, optimizing load balancing for superior network performance. Learn about the challenges, solutions, and design strategies discussed in this thorough research analysis.

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Fat Virtual Access Points

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  1. Fat Virtual Access Points Srikanth Kandula Kate Lin, Tural Badirkhanli and Dina Katabi

  2. State-of-the-art (802.11): Connect to the AP with the highest RSSI

  3. In Homes, Hotspots… Problem 1: AP Uplink ~ 2Mbps (DSL/Cable Modems) Wireless Link ~ 54Mbps (Theoretical Max) 2+2+2+… Uplink Bottleneck Can Aggregate Bandwidth from nearby APs!

  4. At Work … 7Mbps Problem 2: 20Mbps Unnecessary congestion; nearby APs are idle Spread load Individual changes help globally 15Mbps 4Mbps Load Imbalance Divide Total Bandwidth Among Users

  5. 2 Problems, 1 Solution State-of-the-art: Abstraction: Join closest AP Join a Virtual AP, that is the sum of nearby APs User can aggregate bandwidth from all APs Compete for total  balance load across APs

  6. Realize a “fat virtual AP” withonly client-side changes

  7. Basic Operation 2Mbps 2Mbps 20Mbps But, what about receive?

  8. Basic Operation 2Mbps 2Mbps Drop Power-Save Q 20Mbps Pretend in power-save, so AP buffers when disconnected (similar to Chandra et. al. VirtualWiFi) Divide Time and Data Across APs to get “Fat Virtual AP”

  9. Realizing a Fat Virtual AP is Hard • Sustain TCP flows through each AP • Cannot lose packets yet Switch quickly • Which APs to connect to and for how long? • Some APs are more valuable than others • How to divide traffic across the APs? • FatVAP, an 802.11 driver design • divides time across APs to maximize throughput • is transparent to APs and remote ends

  10. FatVAP Overview Scan for available APs Compute a schedule to divide time across APs Switch APs as per schedule Spread traffic by pinning flows to APs Channel 6 Channel 6 Channel 1 Channel 36

  11. How much time to spend at an AP? Useful fraction of time Achievable Bandwidths– end-to-end e, wireless w Subsumes Wireless Link Quality, Contention at AP, APs uplink capacity

  12. How to Divide Time Across APs? Optimal = 7 Mbps 5 Mbps, 100% busy Pick APs Greedily, on End-to-end rate ! more bang for the buck if wireless b/w is large

  13. How to Divide Time Across APs? 5 Mbps, 100% busy Pick APs Greedily, on End-to-end rate Pick APs Greedily, on Wireless rate ! cost to switch is ≈ 5 ms ! can’t linger too long (100ms period) Only 75% usable No Greedy Solution!

  14. Say, fi is fraction of time at APi Let s be switching time and D be the period Value (Bandwidth) Usefulness Constraint Cost (Time) Like Bin Packing, maximize value with bounded cost! (pseudo)-polynomial solution

  15. Wireless Achievable But, How to Estimate Bandwidths? Naively– send-rate of probe burst, APs report load Idea: Use synchronous acks Client TX Queue AP Buffers Time from head of tx queue to end of transmission (ack)

  16. Wireless Achievable End-to-end But, How to Estimate Bandwidths? Naively, send-rate of probe burst or APs report load t Count bytes rcvd in a window Idea: Use synchronous acks Client TX Queue AP Buffers Time from head of tx queue to end of transmission (ack)

  17. Wireless Achievable End-to-end But, How to Estimate Bandwidths? Naively, send-rate of probe burst or APs report load t Count bytes rcvd in a window Idea: Use synchronous acks May not receive data always Idea: only count back-to-back large packets! Client TX Queue AP Buffers Time from head of tx queue to end of transmission (ack)

  18. How to Spread Traffic Across APs?

  19. How to Spread Traffic Across APs? Put flows through all APs virtualize 802.11 state an IP for each interface toggle APs (and channels) By default, kernel sends all traffic to one AP AP1 AP2 MIT 128.30.79.0/24 T-Mobile 192.168.3.0/24 Toggler Hardware (Wireless Card) 802.11 State AP1 State AP2 State Two Interfaces

  20. How to Spread Traffic Across APs? Put flows through all APs virtualize 802.11 state an IP for each interface toggle APs (and channels) By default, kernel sends all traffic to one AP Spread flows to APs Fast header re-writing AP1 AP2 Hardware (Wireless Card) Toggler AP1 State AP2 State Two Interfaces Spreader Distribute load w/o changing APs and applications

  21. Switching Quickly Without Drops A Driver For Each Interface? • warm-up cost on switch • one instance + soft-switch AP1 AP2 One Driver

  22. Switching Quickly Without Drops A Driver For Each Interface? • warm-up cost on switch • one instance + soft-switch 802.11 Control Packets • Isolate Transitions AP1 AP2 Hardware (Wireless Card) AP1 State AP2 State Re-send AUTH Send AUTH

  23. Switching Quickly Without Drops A Driver For Each Interface? • warm-up cost on switch • one instance + soft-switch 802.11 Control Packets • Isolate Transitions Pkts stuck in driver at switch • Private Queues AP1 AP2 • Delay Switch till pkts drain • Drop Packets (madwifi)

  24. Switching Quickly Without Drops A Driver For Each Interface? • warm-up cost on switch • one instance + soft-switch 802.11 Control Packets • Isolate Transitions Pkts stuck in driver at switch • Private Queues AP1 AP2 Attach/Detach Queue = Pointer Swap Enables high-rate TCPs through multiple APs

  25. FatVAP Realizes a Fat Virtual AP • Which APs to connect to and for how long? • Estimate Bandwidths, Solve Optimization • How to divide traffic across the APs? • Virtualize, Pin Flows to APs, rewrite headers • Switch quickly but without losing packets • In-driver, Private Queues, Isolation And, with only client-side changes

  26. Related Work VirtualWiFi (Microsoft Research) AP Selection (Intel Research, U Michigan) SyncScan (UCSD) MadWifi (open-source) • Divide Time across APs to maximize throughput • Sustain TCP flows through multiple APs • Transparently spread traffic across APs

  27. Results

  28. Experimental Setup Compare FatVAP driver with unmodified MadWifi • Scenarios • Testbed built from Cisco, NetGear and MadWifi APs • Residential deployments • Commercial hotspots • Traffic • Long-lived TCP flows • BitTorrent (Azureus client, Planetlab peers) • Mimic Web Browsing (modified WebStone)

  29. Can FatVAP Aggregate Bandwidth? Throughput (Mb/s) Number of APs 6Mbps ~22 Mbps Aggregates end-to-end up to the wireless bottleneck

  30. Can FatVAP Balance Load? 2Mbps 12Mbps C1 C2 C3 C4 C5

  31. Can FatVAP Balance Load? 2Mbps 12Mbps Unmodified MadWifi FatVAP 5 4 3 2 1 0 4.4 3.8 3.5 3.3 3.1 2.9 2.8 2.7 Throughput (Mb/s) .9 .9 C1 C2 C3 C4 C5 C1 C2 C3 C4 C5 C1 C2 C3 C4 C5 Simplifies Network Deployment!

  32. Can FatVAP Adapt to Changes? 5Mbps 15Mbps Throughput (Mb/s) Re-adjusts time@AP as necessary

  33. Contributions A new model for managed 802.11 LANs • Aggregate uplink, Balance load First to realize a fat virtual AP • Divide time and traffic across APs Transparent to APs, applications, servers

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