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SCAP: Smart Caching in Wireless Access Points to Improve P2P Streaming Enhua Tan1, Lei Guo1, Songqing Chen2, Xiaodong Zhang1 1The Ohio State University 2George Mason University ICDCS’07, Toronto, Canada 1 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 2 Wired/wireless Communications Internet WLAN Access Point (AP) Wired users Wireless users 3 P2P Streaming for Wired/wireless Users: Workflow Internet Access Point Source Peer Viewing Peer Wireless Peer WLAN 4 P2P Streaming for Wired/wireless Users: Problems Downstream traffic for other wireless users AFFECTED Internet Source Peer WLAN Generating upstream traffic Streaming content Wireless Peer (Relay/Viewing) Other packets Viewing Peer Streaming quality degraded 5 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: Major problem source: upstream relay traffic further increaseupstream the number of transmission errors Can we minimize traffic with low overhead? to increase cost of contention window back-off improve the WLAN throughput to improve service quality for Internet peers 6 P2P Streaming for Wired/wireless Users: Workflow The same content is transferred twice in the WLAN! Duplicated traffic Internet Access Point Source Peer Viewing Peer Wireless Peer WLAN 7 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 8 Outline Problem Summary and Contributions Measurement & Analysis of P2P Streaming Traffic SCAP Design & Implementation Evaluation Summary 9 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) 10 Workload Statistics Downstream throughput is typically 300~400Kbps Upstream traffic to downstream traffic: Can be as large as 10 times 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 11 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 Upstream packet Upstream packet fingerprint Lookup Downstream packet fingerprint hash table Downstream packet FIFO buffer 12 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 13 100 Dup Ratio & Tput 90 70 Offline analysis processing throughput of RF is less than FH: 60 50 RF FH 40 RF-BufAll 30 20 10 0 PPLLAN PPLWL TVALAN TVAWL ESMLAN ESMWL RF can detect more duplications than FH All the duplication ratios are larger than 75% Still large enough (> 90Mbps) for process P2P streaming (400 Kbps) 450 400 350 Throughput (Mbps) Duplication ratio(%) 80 300 250 RF 200 FH RF-BufAll 150 100 50 0 PPLLAN PPLWL TVALAN TVAWL ESMLAN ESMWL 14 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 repacketizing FH performs the 15 worst Forwarding Delay 200 seconds 200 seconds 10 seconds PPLive and TVAnts: most upstream packets forwarded in 200 seconds 20 seconds 10 ms <20 seconds for 70% ESM: within 10 ms Implies the downstream buffer can be quite small 16 Outline Problem Summary and Contributions Measurement & Analysis of P2P Streaming Traffic SCAP Design & Implementation Evaluation Summary 17 SCAP (Smart Caching in Access Points) Overview Internet Access Point Metadata upstream packet Downstreams buffer (If duplications found in downstream buffer) Relay/Viewing Peer Original upstream packet Downstream buffer WLAN 18 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 19 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) 20 Outline Problem Summary and Contributions Measurement & Analysis of P2P Streaming Traffic SCAP Overview Design & Implementation Evaluation Summary 21 Performance Evaluation: LAN Experiment 4.50 4.43 Mbps 4.5 4 3.5 3 2.5 2 1.5 1 0.5 1MB 7MB 70MB Transfer File Size 8 7 6 4.7 5 Orig Orig RF RF 3FH FH 4 2 1 0 0 8.9 Mbps 9 Upstream Throughput (Mbps) Downstream Throughput(Mbps) 5 140MB 1MB 7MB 70MB 140MB Transfer File Size 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 repacketizing 22 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 23 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 24 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 25 Thank you! Enhua Tan: [email protected] http://www.cse.ohio-state.edu/hpcs/ 26 SCAP (Smart Caching in Access Points) – Basic Idea Inco mi n g oin g t u O g (1) (2) (4) (3) Access Point (AP) Wireless Station 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 27 Workflow of SCAP Downstream Buffer HostAP Driver Downstream packet Decompressing Router Uptream packet Access Point Compressed upstream packet Downstream Buffer Wireless Station Lookup Duplication Detection; Compressing P2P Streaming Application 28 Rabin Fingerprinting Rabin Fingerprinting (RF) A (a1, a2 ,..., am ) can produce fingerprints for a continuous data m1 m2 A ( t ) a t a t ... am stream quickly: 1 2 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) RF ( A) A(t ) mod P(t ) 29 Some Related Work XORs in the Air: Practical Wireless Network Coding (Sigcomm’06) A Protocol-Independent Technique for Eliminating Redundant Network Traffic (Sigcomm’00) 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 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 30