Opportunistic Routing Based on Daily Routines
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Transcript of Opportunistic Routing Based on Daily Routines
Waldir Moreira, Paulo Mendes, and Susana Sargento [email protected]
June 25th, 20126th IEEE WoWMoM Workshop on Autonomic and Opportunistic Communications (AOC 2012)
San Francisco, USA
Opportunistic Routing Based on Daily Routines
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Agenda
• Introduction
• Motivation
• Our Proposal: dLife
• Evaluation
• Results
• Conclusions and Future Work
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Introduction
• Powerful devices
• Spontaneous networks
• Opportunistic contacts
- Intermittent connectivity
• Many routing solutions
- epidemic, encounter history, social aspects ...
• Instability of the created proximity graphs
• Dynamism of users’ behavior
• Daily life routines
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Motivation
• To capture the dynamics of the network represented by time-evolving social ties between pair of nodes
• Two utility functions
- Time-Evolving Contact Duration (TECD)
- TECD Importance (TECDi)
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Our Proposal: dLife
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Our Proposal: dLife
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Our Proposal: dLife
A Bw(B,x)
A B
If Mx Buffer(B) and w(B,x) > w(A,x)
Mx
A BI(B)
A B
If I(B) > I(A)Mx
(1)
(2)
(3)
(4)
Otherwise
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Our Proposal: dLifeComm
A Bw(B,x)
A B
If Mx Buffer(B) and B.sameComm(x) and w(B,x) > w(A,x)
Mx
A BI(B)
A B
If I(B) > I(A)Mx
(1)
(2)
(3)
(4)
Otherwise
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Evaluation
Parameters Values
Simulator Opportunistic Network Environment (ONE)
Routing Proposals Bubble Rap, dLife and dLifeComm
Scenarios Heterogeneous Mobility Trace Cambridge (CRAWDAD)
Simulation Time 1036800 sec 1000000 sec
# of Nodes 150 (people/vehicles) 36 (people)
Mobility Models Working Day, Bus, Shortest Path Map Based Human
Node Interface Wi-Fi (Rate: 11 Mbps / Range: 100 m) Bluetooth
Node Buffer 2 MB
Message TTL 1, 2, 4 days, 1 and 3 weeks
Message Size 1 – 100 kB
Generated Messages 6000
K-Clique, k 5 (Bubble Rap and dLifeComm)
K-Clique, familiarThreshold 700 sec (Bubble Rap and dLifeComm)
Daily Samples 24 (dLife and dLifeComm)
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Results
Heterogenous scenario
- dLife up to 39.5% - dLifeComm up to 31.2%- Bubble Rap (Global centrality)- Few nodes (~17%) high centrality
Cambridge traces
- dLife up to 31.5% - dLifeComm up to 31.3%- Network dynamics (daily routines)- Local centrality
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Results
Heterogenous scenario
- dLife up to 78% less- dLifeComm up to 68% less- High social strength/importance- Bubble rap further replicates
Cambridge traces
- dLife up to 55% less- dLifeComm up to 50.5% less- Variable patterns of contacts- Forwarders not often available
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Results
Heterogenous scenario
- dLife up to 48.3% less - dLifeComm up to 46.1% less- Smarter forwarding decisions- Bubble Rap (weak ties to destin.)
Cambridge traces
- dLife up to 83.7% less- dLifeComm up to 84.7% less- Smaller, well connected groups- Bubble Rap (Centrality not real)
• Dynamism of users’ social daily behavior => wiser forwarding decisions
• Centrality presented higher impact => does not capture reality
• Next steps
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Conclusions andFuture Work
Internet-Draft DTNRG Meeting
Vancouver, July 2012
Information-Centric version of dLife
To FCT for financial support via PhD grant (SFRH/BD/62761/2009) and UCR project (PTDC/EEA-TEL/103637/2008)
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Acknowledgements
Waldir Moreira, Paulo Mendes, and Susana Sargento [email protected]
June 25th, 20126th IEEE WoWMoM Workshop on Autonomic and Opportunistic Communications (AOC 2012)
San Francisco, USA
Opportunistic Routing Based on Daily Routines