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CARROM: Client Association, Rate and Redundancy Optimization for Wi-Fi Multicast

CARROM: Client Association, Rate and Redundancy Optimization for Wi-Fi Multicast. Vishnu Navda, Ram Ramjee, Lenin Ravindranath (MSR India) Ranveer Chandra, Jitu Padhye (MSR Redmond). Why Multicast?. Today Live video/audio streaming Potential Windows/Virus Update IPTV

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CARROM: Client Association, Rate and Redundancy Optimization for Wi-Fi Multicast

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  1. CARROM: Client Association, Rate and Redundancy Optimization for Wi-Fi Multicast Vishnu Navda, Ram Ramjee, Lenin Ravindranath (MSR India) Ranveer Chandra, Jitu Padhye (MSR Redmond)

  2. Why Multicast? • Today • Live video/audio streaming • Potential • Windows/Virus Update • IPTV • Application Level Multicast leveraging IP Multicast

  3. Wi-Fi Multicast Issues • Data Sent only using Basic Rates (1/2 Mbps) • Resource under utilization • Rate anomaly • Low rate client => poor throughput for everyone • No back-off after collision • Unicast unfairness • No Retransmissions • High Losses Access Point Data Rate: 1 Mbps Clients Multicast Group

  4. CARROM Architecture Inter-AP optimizer • Optimal Association • Rate Adaptation • Pseudo-Broadcast • Adaptive FEC Intra-AP optimizer Intra-AP optimizer Intra-AP optimizer

  5. Problem - Only basic rates • Multicast sent at only basic rates (1/2Mbps) AP1 1 Mbps 1 Mbps 5.5 Mbps 5.5 Mbps 1 Mbps 5.5 Mbps C1 11 Mbps 11 Mbps C3 C2 5.5 Mbps • Solution • Rate adaptation

  6. Problem - Rate Anomaly Channel X AP2 Channel Y AP1 1 Mbps 11Mbps 1 Mbps 1 Mbps 1 Mbps 11 Mbps C1 C3 1 Mbps C2 1 Mbps • Solution • Control Association

  7. Solution - Optimal Association • Inter-AP optimizer • Collects feedback from clients • Determines optimal association • Inform clients about association • Inform APs about rate Inter-AP optimizer AP1 AP2 C1 C3 C2

  8. Optimal Association • Rate Matrix • Metrics • Minimize sum of multicast air time across APs • Maximize average group throughput AP1 AP2 • Optimized Association • C1 - AP1 • C2 - AP2 • C3 - AP2 C1 C2 C3

  9. Optimal Association • NP Hard problem • Hierarchical Association Algorithm • Min Cut to Partition topology • LP solver • Brute force with N best APs when partition size is small • Greedy Algorithm • Online • Associate clients/groups to that AP which minimizes impact to existing flows

  10. Problem - Unicast unfairness • When unicast and multicast co-exists • Unicast backs-off • Multicast doesn’t • Degrades unicast throughput Ref: MSWIM06 • Solution • Pseudo-Broadcast approach

  11. Solution - Pseudo-Broadcast • AP unicast to one client • Other clients listen in promiscuous mode Listening in promiscuous mode Pseudo-broadcast • Unicast fairness due to back-off

  12. Losses are uncorrelated • Losses are uncorrelated across clients • Solution • Adaptive FEC Correlation between 2 users

  13. Adaptive FEC • Intra-AP optimizer • Pseudo-Broadcast • Packet level feedback • Weighted round-robin among clients • Adapt FEC

  14. Summary • Optimal Association • Increase Multicast Throughput • Pseudo-Broadcast • Unicast Fairness • Multicast Rate Adaptation • Increase Multicast Throughput • Adaptive FEC • Increase Reliability

  15. Results – Optimal Association Optimal Association helps significantly reduce Wireless Utilization

  16. Implementation Issues • No modification • Optimal Association • AP modification • Rate Adaptation • Adaptive FEC • Pseudo broadcast • Missing Windows APIs • Associate to a AP with given BSSID • Listen in promiscuous mode

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