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PPWEB:A Peer-to-Peer Approach for
Web Surfing On the Go
Ling-Jyh Chen, Ting-Kai HuangInstitute of Information Science, Academia Sinica, Taiwan
Guang YangNokia Research Center, Palo Alto, US
Motivation
• Web surfing is part of our life.• How can we surf the Web when we cannot
directly access the web pages?– No connections– Censorship
• Mobile devices are hugely popular.• How can we browse the Web when we are on the
go?– Cellular– Wi-Fi Hotspots
Previous Solutions• Offline-based approaches
– Gnu Wget – Wwwoffle– Well-known web browsers
• Cache-based approaches– Push based (Aalto ‘04, Costa-Montenegro ‘02, Spangler
‘97)– Pull based (Jiang ’98a, Jiang ’98b, Padmanabhan ‘96)
• Infostation-based approaches– Mobile Hotspots (Ho ‘04)– Thedu (Balasubramanian ‘07)
Previous Solutions (Drawbacks)
• Offline-based– manually download web documents– limited number of web pages
• Cache-based– Tremendous storage overhead
• You still need a data plan to surf.
• Infostation-based– Dedicated Infostations needed– Single point of failure
Assumptions We Make
• All peers collaborate.• All peers have local connectivity
– WiFi, Bluetooth, etc.
• All peers are mobile.• Some peers have Internet access.
Internet
HTTP
What We Propose: Scenario 1
Gateway Peer:A peer who can
access the Internet directly
What We Propose: Scenario 2a
Vanilla Peer (A):
Peer that cannot access Internet
directly
Gateway Peer (B)
What We Propose: Scenario 2b
Vanilla Peer (A)
Vanilla Peer (B)
B gets A’s request
Direct forwarding
Collaborative forwarding
IndirectForwarding
Do nothingRequest
Forwarding
The request has been relayed H times
B has the requested web content
B and A are connected
B and A are connected
B is a GPY
Y
N
Y
Y
N
N
N
NY
Direct Forwarding vs. Indirect Forwarding
• B has complete content =>Direct Forwarding algorithm
• B may only have partial content =>Indirect Forwarding algorithm– Further passing the request message
using Request Forwarding algorithm
Cooperative Forwarding Algorithm
• Increase the packet delivery ratio and decrease the request response time
• HEC-PF – Hybrid Erasure Coding Algorithm (H-EC)– Probabilistic Forwarding Algorithm
• Erasure codes increase error tolerance.• Extra caching increases hit ratio in the
future (esp. for popular pages).
Evaluations
• Evaluate the performance of PPWEB scheme against Mobile Hotspots scheme– Service ratio and traffic overhead
• DTNSIM: Java-based simulator• Real wireless traces
– UCSD (campus trace)– iMote (Infocom ‘05)
The Properties of two network scenarios
Trace Name iMote UCSD
Device iMote PDA
Network Type Bluetooth WiFi
Duration (days) 3 77
Devices Participating 274 273
Number of Contacts 28,217 195,364
Avg # Contacts/pair/day 0.25148 0.06834
Parameter Settings
• Number of VPs: – 20% of the other peers
• Number of requests: – first 10% of simulation time with a Poisson rate
of 1800 sec/request.
• The HTTP requests:– top 500 requested web pages, – campus proxy server of NTU, Apr.-Sept. 2006.
Scenario 1: UCSD
γ= 20%
γ= 60%
Scenario 2: iMote
γ= 20%
γ= 60%
Traffic Overhead
γ PPWebMobile
HotspotsNormalized Overhead
iMote
20% 4,298 1,423 3.02
40% 3,986 1,591 2.50
60% 3,938 1,694 2.15
UCSD
20% 211,604 65,723 3.22
40% 189,702 64,858 2.92
60% 163,883 62,663 2.62
Replication factor of erasure coding = 2Aggressive forwarding phase of the HEC-PF: make one more copyThe upper bound of the traffic overhead : 2*2=4
Summary
• PPWEB is a peer-to-peer solution to enable mobile web surfing.
• No constant Internet access is required.• No dedicated servers are required.• It implements a Collaborative
Forwarding algorithm that takes advantage of opportunistic encounters.
Thank You!