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ICDCS’07, Toronto, Canada 1
SCAP: Smart Caching in Wireless Access Points to Improve P2P
Streaming
Enhua Tan1, Lei Guo1, Songqing Chen2, Xiaodong Zhang1
1The Ohio State University2George Mason University
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
4
P2P Streaming for Wired/wireless Users:Workflow
WLAN
Internet
Source Peer
Wireless Peer
Viewing Peer
Access Point
5
P2P Streaming for Wired/wireless Users: Problems
WLAN
InternetDownstream traffic for other wireless users AFFECTED
Generating upstream traffic
Streaming quality degradedWireless Peer
(Relay/Viewing)
Viewing PeerStreaming content
Other packets
Source Peer
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 trafficupstream relay traffic
Can we minimize upstream traffic with low overhead? to improve WLAN throughput to improve service quality for Internet peers
7
WLAN
Internet
Wireless Peer
Viewing Peer
Access Point
The same content is transferred twice in
the WLAN! Duplicated traffic
P2P Streaming for Wired/wireless Users:Workflow
Source Peer
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 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
12
Downstream packetDownstream packetFIFO bufferFIFO buffer
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
Downstreampacket
fingerprinthash table
Upstreampacket
Upstreampacket fingerprint
Lookup
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
14PPL-
LAN
PPL-
WL
TVA-
LAN
TVA-
WL
ESM-
LAN
ESM-
WL
0
50
100
150
200
250
300
350
400
450
RF
FH
RF-BufAll
Thr
ough
put (
Mbp
s)
PPL-
LAN
PPL-
WL
TVA-
LAN
TVA-
WL
ESM-
LAN
ESM-
WL
0
10
20
30
40
50
60
70
80
90
100
RF
FH
RF-BufAll
Dup
licat
ion
ratio
(%)
RF can detect more duplications than FH
All the duplication ratios are larger than 75%
Offline analysis processing throughput of RF is less than FH:
Still large enough (> 90Mbps) for process P2P streaming (400 Kbps)
Dup Ratio & Tput
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
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
200seconds
200seconds
10 ms
10seconds
20seconds
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
WLAN
Internet
Downstreams buffer
Metadata upstream packet
(If duplications found in downstream buffer)
Relay/Viewing Peer
Access Point
Original upstream packet
Downstream buffer
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
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
1MB 7MB 70MB 140MB0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Orig
RF
FH
Transfer File Size
Dow
nstr
eam
Thr
ough
put(
Mbp
s)
1MB 7MB 70MB 140MB0
1
2
3
4
5
6
7
8
9
Orig
RF
FH
Transfer File SizeU
pstr
eam
Thr
ough
put (
Mbp
s)
4.50
4.43 Mbps
4.7
8.9 Mbps
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
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
Access Point (AP) Wireless Station
(1)
(4)
(2)
(3)
Incoming
Outgoing
28
AccessPoint
WirelessStation
Router
HostAP Driver
Downstream Buffer
Downstream Buffer
P2P Streaming Application
Duplication Detection;
CompressingLookup
Decompressing
Downstream packet
Uptream packet Compressedupstream packet
Workflow of SCAP
29
Rabin Fingerprinting
mmm atatatA ...)( 2
21
1
)(mod)()( tPtAARF
),...,,( 21 maaaA 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