Transcript A Peer-to-Peer Approach for Mobile File Transfer in Opportunistic People Networks Ting-Kai Huang

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
– 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.
M-FTP: Scenario 1
Internet
FTP
Gateway Peer:
A peer who can access
the 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
Y
B is a GP
N
Y
B and A are
connected
B has the
Requested file
N
N
Y
Indirect
Forwarding
Direct forwarding
The request has been
relayed H times
B and A are
connected
N
Y
Do nothing
Y
N
Collaborative
forwarding
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
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 GPs
– 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
iMote
UCSD
γ
M-FTP
(A)
Mobile Hotspots
(B)
Normalized Overhead
(A/B)
20%
22,170
5,866
3.78
40%
23,932
6,613
3.62
60%
24,696
7,197
3.43
20%
1,425,943
269,834
5.28
40%
1,510,094
261,653
5.77
60%
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!