opportunistic routing based on daily routines
DESCRIPTION
Opportunistic routing is being investigated to enable the proliferation of low-cost wireless applications. A recent trend is looking at social structures, inferred from the social nature of human mobility, to bring messages close to a destination. To have a better picture of social structures, social-based opportunistic routing solutions should consider the dynamism of users’ behavior resulting from their daily routines. We address this challenge by presenting dLife, a routing algorithm able to capture thedynamics of the network represented by time-evolving social ties between pair of nodes. Experimental results based on synthetic mobility models and real human traces show that dLife has better delivery probability, latency, and cost than proposals based on social structures. This presentation was given in the 6th IEEE WoWMoM Workshop on Autonomic and Opportunistic Communications (AOC 2012), on June 25th, 2012 in San Francisco, USA.TRANSCRIPT
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
3
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
4
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