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Enhancing P2P Streaming in WLANs Through Smart Caching Techniques

This paper presents SCAP (Smart Caching in Access Points), a novel approach aimed at alleviating the challenges faced by Peer-to-Peer (P2P) streaming applications over Wireless Local Area Networks (WLAN). With the pervasive use of P2P streaming services, such as PPLive and Joost, the resulting congestion and lowered service quality for Internet peers due to duplicated upstream traffic are significant issues. Our measurements indicate over 75% of upstream traffic is redundant. SCAP effectively minimizes this by implementing smart caching, resulting in a potential throughput improvement of up to 88% and reduced delays.

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Enhancing P2P Streaming in WLANs Through Smart Caching Techniques

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  1. ICDCS’07, Toronto, Canada Enhua Tan1, Lei Guo1, Songqing Chen2, Xiaodong Zhang1 1The Ohio State University 2George Mason University SCAP: Smart Caching in Wireless Access Points to Improve P2P Streaming

  2. Background • Wireless access to Internet is pervasive: • On campus, in offices, at home, and public utilities • Most are supported by Wireless LANs • Peer-to-Peer applications are widely used: • Streaming: PPLive, Joost, etc … • VoIP: Skype, etc … • Large file distribution: BitTorrent, etc … Our Focus: Interaction between wireless users and P2P streaming applications

  3. Wired/wireless Communications Internet WLAN Access Point (AP) Wired users Wireless users

  4. P2P Streaming for Wired/wireless Users:Workflow Internet Source Peer Access Point Viewing Peer Wireless Peer WLAN

  5. P2P Streaming for Wired/wireless Users: Problems Internet Downstream traffic for other wireless users AFFECTED Source Peer WLAN Generating upstream traffic Viewing Peer Streaming content Streaming quality degraded Wireless Peer (Relay/Viewing) Other packets

  6. Problem Summary • Peers in WLAN may relay streaming content by uploading a lot of traffic: • Congest the WLAN due to channel competitions • Provide low quality of service to the Internet peers • Downstreams have lower priority due to upstreams • Extra upstream traffic: • further increase the number of transmission errors • increase the cost of contention window back-off • Major problem source:upstream relay traffic •  Can we minimize upstream traffic with low overhead? • to improve WLAN throughput • to improve service quality for Internet peers

  7. P2P Streaming for Wired/wireless Users:Workflow The same content is transferred twice in the WLAN!  Duplicated traffic Internet Source Peer Access Point Viewing Peer Wireless Peer WLAN

  8. Contributions • Our measurements show that > 75% upstream traffic is duplicated with the downstream traffic for three representative applications • SCAP: Smart Caching in the Access Point for minimizing upstream traffic: design & prototype implementation • Evaluation results show SCAP can improve the throughput of the WLAN by up to 88%: • SCAP also reduces the delay to Internet peers

  9. Outline • Problem Summary and Contributions • Measurement & Analysis of P2P Streaming Traffic • SCAP Design & Implementation • Evaluation • Summary

  10. Measurement & Analysis of P2P Streaming Traffic • Aim to answer two questions: • How much duplicated traffic in practice? • How much overhead in identifying such duplications? • Measurement: • Collect traces of three representative P2P live streaming applications: PPLive, ESM, and TVAnts • In LAN (100Mbps) and WLAN (802.11b)

  11. Workload Statistics • Downstream throughput is typically 300~400Kbps • Upstream traffic to downstream traffic: • Can be as large as10times for PPLive due to its popularity • Between 2 to 4 times for TVAnts • Not too much for ESM • PPLive and ESM: most in TCP • TVAnts: 74% in UDP for WLAN

  12. Duplication Detection Methods:Fixed Hashing • Offline workload analysis: • Fixed Hashing (FH) • Compute only 1 fingerprint (hash value) for a downstream packet; store this fingerprint in a hash table, and cached the packet in FIFO buffer • For each upstream packet, also compute the fingerprint, and look it up in the hash table to locate the duplicated downstream packet; If found the same fingerprint, do further byte-to-byte comparison Lookup Downstream packet fingerprint hash table Upstream packet Downstream packet FIFO buffer Upstream packet fingerprint

  13. Duplication Detection Methods:Rabin Fingerprinting • Rabin Fingerprinting (RF) • A unique hash function: produce fingerprints for a continuous data stream quickly (NSDI’07 BitTyrant) • We scan the whole packet and only store fingerprints ending with 8 zeros over 64 bytes content • averagely 5 fingerprints for a 1400 bytes packet (1/28) • FIFO Buffer: stores latest 50,000 downstream packets • Buffer + hash table: need about 75MB memory totally

  14. Dup Ratio & Tput • Offline analysis processing throughput of RF is less than FH: • Still large enough (> 90Mbps) for process P2P streaming (400 Kbps) • RF can detect more duplications than FH • All the duplication ratios are larger than 75%

  15. Duplication Beginning Offset • FH can only detect the duplication when the offsets for up/downstream packets are the same (no re-packetizing) • ESM does not have any offset differences  FH performs well • TVAnts has a lot of re-packetizing  FH performs the worst

  16. Forwarding Delay 200 seconds 200 seconds • PPLive and TVAnts: most upstream packets forwarded in 200 seconds • <20 seconds for 70% • ESM: within 10 ms • Implies the downstream buffer can be quite small 10 seconds 20 seconds 10 ms

  17. Outline • Problem Summary and Contributions • Measurement & Analysis of P2P Streaming Traffic • SCAP Design & Implementation • Evaluation • Summary

  18. SCAP (Smart Caching in Access Points) Overview Internet Access Point Metadata upstream packet (If duplications found in downstream buffer) Downstreams buffer Downstream buffer Relay/Viewing Peer Original upstream packet WLAN

  19. Design Issues • Buffer size: • Need 7.5MB for storing recent 200 seconds traffic (in 300Kbps rate), which is affordable for a wireless station • But AP will need to buffer for multiple stations: • AP should dynamically adjust the buffer space for each station according to its duplication ratios in order to achieve highest traffic reduction with limited buffer space • Buffer synchronization between AP and station: • If a metadata upstream packet cannot be reassembled on AP due to a cache miss, TCP flow will be stalled • Wireless station caches several copies of recent sent upstream packets and resends the uncompressed packet when needed

  20. Prototype Implementation • Modified HostAP driver in Linux kernel 2.6.16 for the AP and stations • Wireless card is based on Intersil Prism 2.5 chipset (802.11b) • Identification of the downstream packet • For AP to locate the packet in decompressing the upstream packet • Cannot use Sequence Control field (2 bytes) because it is filled by the firmware • Have to use the first fingerprint value (8 bytes)

  21. Outline • Problem Summary and Contributions • Measurement & Analysis of P2P Streaming Traffic • SCAP Overview • Design & Implementation • Evaluation • Summary

  22. Performance Evaluation: LAN Experiment 4.50 8.9 Mbps 4.43 Mbps • Station first receives a file from a server, then sends it back • RF: little overhead for the downstream throughput (1.5% decrease), and 88% improvement for the upstream throughput • FH: cannot have any improvement due to constant TCP re-packetizing 4.7

  23. Performance Evaluation:Internet Experiment • Evaluate PPLive, TVAnts, and ESM • Run the applications in a VMWare-based Windows XP guest OS for HostAP driver to work • Measurement methods: • Because P2P Streaming is a Constant Bit Rate stream: •  Upstream throughput will not change even if we reduces its traffic • Running iperf on another wireless station to observe the impact to WLAN TCP throughput • Running Ping to observe the impact to response time • Run multiple trials to get comparable P2P downstream throughput for comparison • Each trial runs for 600 seconds

  24. Internet Experiment:Evaluation Results • RF/FH performs best for TVAnts since it has the largest volume of upstream traffic: • Increases TCP throughput by 0.95 Mbps (54% of upstream traffic) • Decrease Ping round-trip time by 83 ms (-26%) • Also performs well for PPLive/ESM

  25. Summary • With the increasing popularity of P2P streaming applications and pervasive deployment of 802.11 WLANs, more peers will be connected by wireless • We study the impact of wireless peers to the performance of wireless and Internet users • Without a proper control of P2P traffic, the performance of both parties can be significantly affected • We designed and implemented SCAP (Smart Caching in Access Points) in order to reduce the upstream traffic for P2P live streaming applications • Our prototype based evaluation shows the effectiveness of SCAP: • SCAP improves the throughput of the WLAN by up to 88% • SCAP reduces the response delay to Internet peers as well

  26. Thank you!Enhua Tan:etan@cse.ohio-state.eduhttp://www.cse.ohio-state.edu/hpcs/

  27. SCAP (Smart Caching in Access Points) – Basic Idea • AP stores downstream data in buffer (1) • Station stores downstream data in buffer (2) • Compare upstream packet (3) with (2), upload difference (4) • AP will assemble upstream packet with data in (1) to the Internet

  28. Workflow of SCAP

  29. Rabin Fingerprinting • Rabin Fingerprinting (RF) can produce fingerprints for a continuous data stream quickly: • Advance the fingerprint only requires an addition, a multiplication, and a mask • Lack of this property for other hash functions like MD5/SHA (and they are also more complex)

  30. Some Related Work • XORs in the Air: Practical Wireless Network Coding (Sigcomm’06) • Utilizing the broadcasting nature of wireless networks to improve throughput of multi-hop network (instead of application characteristics) • Our scheme is utilizing the traffic pattern of P2P applications • A Protocol-Independent Technique for Eliminating Redundant Network Traffic (Sigcomm’00) • reduces redundant traffic using Rabin Fingerprinting • A Low-bandwidth Network File System (SOSP’01) • Exploits similarities between different versions of a file to reduce update traffic

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