opportunistic routing based on daily routines

Waldir Moreira, Paulo Mendes, and Susana Sargento waldir.junior@ulusofona.pt

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 waldir.junior@ulusofona.pt

June 25th, 20126th IEEE WoWMoM Workshop on Autonomic and Opportunistic Communications (AOC 2012)

San Francisco, USA

Opportunistic Routing Based on Daily Routines