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!