1. PPWEB: A Peer-to-Peer Approach for Web Surfing On the Go Ling-Jyh Chen, Ting-Kai Huang Institute of Information Science, Academia Sinica, Taiwan Guang Yang Nokia Research Center, Palo Alto, US

2. 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

3. 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)

4. 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

5. Assumptions We Make All peers collaborate. All peers have local connectivity –WiFi, Bluetooth, etc. All peers are mobile. Some peers have Internet access.

6. Internet HTTP What We Propose: Scenario 1 Gateway Peer: A peer who can access the Internet directly

7. What We Propose: Scenario 2a Vanilla Peer (A): Peer that cannot access Internet directly Gateway Peer (B)

8. What We Propose: Scenario 2b Vanilla Peer (A) Vanilla Peer (B)

9. B gets A’s request Direct forwarding Collaborative forwarding Indirect Forwarding Do nothing Request 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 GP Y Y N Y Y N N N N Y

10. 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

11. 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).

12. Future works Buffer management Cache management –How to ensure content is up-to-date? Dynamic pages Security

13. 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)

14. The Properties of two network scenarios Trace NameiMoteUCSD DeviceiMotePDA Network TypeBluetoothWiFi Duration (days)377 Devices Participating274273 Number of Contacts28,217195,364 Avg # Contacts/pair/day0.251480.06834

15. 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.

16. Scenario 1: UCSD γ = 20% γ = 60%

17. Scenario 2: iMote γ = 20% γ = 60%

18. Traffic Overhead γPPWeb Mobile Hotspots Normalized Overhead iMote 20%4,2981,4233.02 40%3,9861,5912.50 60%3,9381,6942.15 UCSD 20%211,60465,7233.22 40%189,70264,8582.92 60%163,88362,6632.62 Replication factor of erasure coding = 2 Aggressive forwarding phase of the HEC-PF: make one more copy The upper bound of the traffic overhead : 2*2=4

19. 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.

20. Thank You!