A Peer-to-Peer Approach for Mobile File Transfer in Opportunistic People Networks Ling-Jyh Chen and Ting-Kai Huang Institute of Information Science, Academia Sinica, Taiwan

Motivation Internet is part of our lives We can use the Internet “almost” anywhere/ anytime. Cellular Wi-Fi Hotspots Even with Mobility, we have handover solutions.

What will happen when the Internet is not always available?

Previous Solutions Infostation-based approaches But, Mobile Hotspots [19] Ott ’06 [27] But, Dedicated Infostations needed Single point of failure and scalability problems

Our Contribution We proposed M-FTP to improve the effectiveness of FTP application in mobile opportunistic networks. Every peer can access the Internet when parts of them have internet access. Proposed a “Collaborative Forwarding algorithm” to further utilize opportunistic ad hoc connections and spare storage in the network.

Our Assumption All peers are collaborative. All peers have local connectivity WiFi, Bluetooth, etc. All peers are mobile. Some peers have Internet access.

A peer who can access the Internet directly M-FTP: Scenario 1 Internet FTP Gateway Peer: A peer who can access the Internet directly

Peer that cannot access Internet directly M-FTP : Scenario 2a Gateway Peer (B) Vanilla Peer (A): Peer that cannot access Internet directly

M-FTP : Scenario 2b Vanilla Peer (A) Vanilla Peer (B)

B rcv A’s request B is a GP Y N B and A are connected B has the Requested file Y N Y N Direct forwarding The request has been relayed H times B and A are connected N N Collaborative forwarding Y Y Indirect Forwarding Do nothing Request Forwarding

Collaborative Forwarding Algorithm Goal: Increase the packet delivery ratio and decrease the request response time Method: PROPHET [22] Based on Epidemic Routing Scheme [26] Delivery predictability Caching improves hit rate in the future (esp. for popular pages).

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

Evaluations Evaluate the performance of M-FTP scheme against Mobile Hotspots scheme Service ratio and traffic overhead DTNSIM: Java-based simulator Real-world wireless traces UCSD (campus trace) iMote (Infocom ‘05)

The Properties of two network traces Trace Name iMote UCSD Device 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 GPs Number of requesters: γ mobile peers Number of requesters: 20% of the other peers (VPs) Number of requests: first 10% of simulation time with a Poisson rate of 1800 sec/request. The FTP requests: top 100 requested iTunes songs , As report as in iTune store on Sep. 7 2007.

UCSD scenario γ= 20% γ= 60%

iMote scenario γ= 20% γ= 60%

Traffic Overhead γ M-FTP (A) Mobile Hotspots (B) Normalized Overhead (A/B) iMote 20% 22,170 5,866 3.78 40% 23,932 6,613 3.62 60% 24,696 7,197 3.43 UCSD 1,425,943 269,834 5.28 1,510,094 261,653 5.77 1,535,310 261,820 5.86

Conclusion We propose the solution, M-FTP, that can provide effective data transfer on the go. Peer to peer No dedicated devices M-FTP implements a Collaborative Forwarding algorithm that takes advantage of opportunistic encounters.

Thank You! 22