Routing on Roles - TU Dresden

Routing on RolesAn Adaptive Approach for DTN Routing

José Irigon de IrigonNovember 30, 2018

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Table of contents

1. DTN Introduction

2. Challenges in DTN routing

3. The need for adaptation

4. Adaptation by means of Roles

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DTN Introduction

End-to-end connectivity

Figure 1: End-to-end Connectivity Figure 2: No end-to-end Connectivity

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A communication between static stations

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SBSA

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Wireless range do not allow end-to-end connectivity• Contact opportunity

• Knowledge about the topology

• Nodes, Stations, Mobile


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Wireless range do not allow end-to-end connectivity

• Contact opportunity




DST:SB

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DST:SB

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Wireless range do not allow end-to-end connectivity

• Contact opportunity




DST:SB

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DST:SB

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DST:SBDST:SB

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Challenge networks

Pictures [1, 2, 3, 4]

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Ring Road[5]: latency insensitive services with LEO satellitesThe village: DakNet[5], KioskNet[6], TrainNet[7], the Sámis[8, 9, 10, 11, 12]Wild life[13] and Smart Farming [14]The Mars rover communication network

Challenge networks

Pictures [1, 2, 3, 4]

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Ring Road[5]: latency insensitive services with LEO satellites

The village: DakNet[5], KioskNet[6], TrainNet[7], the Sámis[8, 9, 10, 11, 12]Wild life[13] and Smart Farming [14]The Mars rover communication network

Challenge networks

Pictures [1, 2, 3, 4]

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Ring Road[5]: latency insensitive services with LEO satellites

The village: DakNet[5], KioskNet[6], TrainNet[7], the Sámis[8, 9, 10, 11, 12]

Wild life[13] and Smart Farming [14]The Mars rover communication network

Challenge networks

Pictures [1, 2, 3, 4]

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Ring Road[5]: latency insensitive services with LEO satellitesThe village: DakNet[5], KioskNet[6], TrainNet[7], the Sámis[8, 9, 10, 11, 12]

Wild life[13] and Smart Farming [14]

The Mars rover communication network

Challenge networks

Pictures [1, 2, 3, 4]

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Ring Road[5]: latency insensitive services with LEO satellitesThe village: DakNet[5], KioskNet[6], TrainNet[7], the Sámis[8, 9, 10, 11, 12]Wild life[13] and Smart Farming [14]

The Mars rover communication network

Challenges in DTN routing

A concrete use-case

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• Rovers move over defined paths

A concrete use-case

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A concrete use-case

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A concrete use-case

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Bob wants to send a picture to Alice

A concrete use-case

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A concrete use-case

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Routing in DTNMessage Forwarding:

• Whom to forward?• Single or multiple copies

What are the priorities?• energy consumption?• assure delivery?

Knowledge about the network• How much?• How accurate?

The routing decision

ObjectiveRouting

AlgorithmContext

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Based on the available topological information, a routing protocolis chosen that uses the network objectives as priorities to decideupon conflicting decisions.

What is known about the topology?


Contact

Capability

Historical

InformationPrediction

Contact

Plan (CP)

Latency

Energy

efficiency

Number

of hops

Queueing

delay. . .

Delivery

probability

Replication

Based

Probability

Based

CP Based

ObjectiveRouting

AlgorithmContext

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Based on the available topological information, a routing protocolis chosen that uses the network objectives as priorities to decideupon conflicting decisions.

What is known about the topology?


Contact

Capability

Historical


Contact

Plan (CP)

Latency

Energy

efficiency

Number

of hops

Queueing

delay. . .

Delivery

probability

Replication

Based

Probability

Based

CP Based

ObjectiveRouting

AlgorithmContext

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What are the rover priorities?


Contact

Capability

Historical


Contact

Plan (CP)

Latency

Energy

efficiency

Number

of hops

Queueing

delay. . .

Delivery

probability

Replication

Based

Probability

Based

CP Based

ObjectiveRouting

AlgorithmContext

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To which peers should the bundle be forwarded?

The routing decision - Replication Based

Contact

Capability

Historical


Contact

Plan (CP)

Latency

Energy

efficiency

Number

of hops

Queueing

delay. . .

Delivery

probability

Replication

Based

Probability

Based

CP Based

ObjectiveRouting

AlgorithmContext

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• Bundle is replicated at every contact

• Every node is using the same algorithm


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• Bundle is replicated at every contact

• Every node is using the same algorithm


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SummaryPositive

• Context independentNegative

• Waste resources• Congestion prone• Poor performance under loador network density

The routing decision - Probability Based

Contact

Capability

Historical


Contact

Plan (CP)

Latency

Energy

efficiency

Number

of hops

Queueing

delay. . .

Delivery

probability

Replication

Based

Probability

Based

CP Based

ObjectiveRouting

AlgorithmContext

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elivery predictability is the transitive likelihood of encounter13

• Bundle is replicated to peers that arelikely to encounter the destination



ProPHETv2Routing decision based on:

• Peer delivery predictability• Transitive delivery predictability• Aging



ProPHETv2Routing decision based on:

• Peer delivery predictability• Transitive delivery predictability• Aging





SummaryPositive

• Smaller amount of replicas

• Better performance under loadNegative

• Requires a well defined pattern

The routing decision - Deterministic

Contact

Capability

Historical


Contact

Plan (CP)

Latency

Energy

efficiency

Number

of hops

Queueing

delay. . .

Delivery

probability

Replication

Based

Probability

Based

CP Based

ObjectiveRouting

AlgorithmContext

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Contact Plan from all devices available


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Contact Plan from all devices availableBuild a multigraph*


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Contact Plan from all devices availableBuild a multigraph*Calculate shortest path


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The process repeats at every device for each bundle


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SummaryPositive

• Smallest amount of replicas

• Best performance under loadNegative

• Requires a contact plan

A word about congestion in DTN

ObjectiveRouting

AlgorithmContext

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• Definition• Why do we care?• What can be done?

”... congestion occurs when resource demands fromusers/applications exceed the network’s available capacity.” [15]

”Generally, it (congestion) occurs when the nodes in the networkbecome overloaded.” [16]

A word about congestion in DTN

ObjectiveRouting

AlgorithmContext

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”... congestion occurs when resource demands fromusers/applications exceed the network’s available capacity.” [15]

”Generally, it (congestion) occurs when the nodes in the networkbecome overloaded.” [16]

Congestion Mitigation

Congestion

ControlCongestion

ControlSelfishness

FairnessQueueing

Dely/Jitter

ObjectiveRouting

AlgorithmContext

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The need for adaptation

Routing adaptation

• At boot up, historical information is not available

• Probabilistic approach provide better results on predictable networks

• A contact plan may be available later on

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Routing adaptation




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Routing adaptation




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Routing adaptation

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Routing adaptation

SA SB SC SD SE

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An accurate contact plan

...is no assurance against topology changes

Routing adaptation

SA SB SC SD SE

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An accurate contact plan...is no assurance against topology changes

Routing adaptation

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• An alternative path is found

• Contact plan becomes invalid

• Historical information is currently useless

• Switch to a replication-based variant

Routing adaptation

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Routing adaptation

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Routing adaptation

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• The way become free

• Switch to replication-based followed byprobabilistic or schedule-based approach

Adaptation by means of Roles

Why Roles for this use-case?

• DTN routing algorithms as roles may be implemented andtested in isolation as standalone building blocks

• Constraints can be applied between roles

• Algorithms can be added/extended incrementally

• Test and comparison of new algorithms made easier

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Routing and roles

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Routing and roles

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Routing and roles

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Routing and roles

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Routing and roles

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Routing and roles

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Routing and roles

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Routing and roles

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Routing and roles

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Summary

• Adaptability in DTN is needed at least on start up (learning phase) andunder topology changes

• Choosing the right routing algorithm and respective congestionmitigation mechanism in run time is critical to maximize networkutilization, and should be done based in the current network context.

• The concept of roles offers key features to be used in an adaptiverouting framework:

• possibility to add behavior to unrelated objects• constraints between roles and role groups• run time adaptation

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Thank you

Questions?

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References i

Montry, “Smart Farm.” https://www.wespeakiot.com/robust-sensors-and-the-power-of-the-cloud-the-perfect-recipe-for-smart-farming/,2017.A. Pentland, R. Fletcher, and A. Hasson, “DakNet: RethinkingConnectivity in Developing Nations,” Computer, vol. 37, no. 1, 2004.

B. Rabtsevich and Shutterstock, “Leo Sats.”https://spacewatchme.com/2017/02/geo-leo-hybrid-multigrid-network/.M. D. L. NASA/JPL/Cornell University, “Mars Rover.” https://en.wikipedia.org/wiki/Mars_Exploration_Rover,2003.

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https://www.wespeakiot.com/robust-sensors-and-the-power-of-the-cloud-the-perfect-recipe-for-smart-farming/

https://www.wespeakiot.com/robust-sensors-and-the-power-of-the-cloud-the-perfect-recipe-for-smart-farming/

https://spacewatchme.com/2017/02/geo-leo-hybrid-multigrid-network/

https://spacewatchme.com/2017/02/geo-leo-hybrid-multigrid-network/

https://en.wikipedia.org/wiki/Mars_Exploration_Rover

https://en.wikipedia.org/wiki/Mars_Exploration_Rover

References ii

S. C. Burleigh and E. J. Birrane, “Toward a communicationssatellite network for humanitarian relief,” Proceedings of the 1stInternational Conference on Wireless Technologies forHumanitarian Relief - ACWR ’11, p. 219, 2011.

S. H. Watson, A. A. Thobhani, O. G. Drive, and B. B. Chan, “Designand Implementation of the,” pp. 1633–1644, 2001.

M. Zarafshan-Araki and K. W. Chin, “TrainNet: A transport systemfor delivering non real-time data,” Computer Communications,vol. 33, no. 15, pp. 1850–1863, 2010.

A. Lindgren and A. Doria, “Experiences from deploying a real-lifeDTN system,” 2007 4th Annual IEEE Consumer Communicationsand Networking Conference, CCNC 2007, pp. 217–221, 2007.

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References iii

S. Grasic, Development and Deployment of Delay TolerantNetworks: An Arctic Village Case.2014.K. Heimerl and E. Brewer, “The village base station,” Proceedingsof the 4th ACM Workshop on Networked Systems for DevelopingRegions - NSDR ’10, pp. 1–2, 2010.

A. Lindgren, A. Doria, J. Lindblom, and M. Ek, “Networking in theland of northern lights,” Proceedings of the 2008 ACM workshopon Wireless networks and systems for developing regions -WiNS-DR ’08, pp. 1–7, 2008.

S. Grasic and A. Lindgren, “Revisiting a remote village scenarioand its DTN routing objective,” Computer Communications,vol. 48, pp. 133–140, 2014.

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References iv

P. Juang, H. Oki, Y. Wang, M. Martonosi, P. Peh Li-Shiuan, andD. Rubenstein, “Energy-Efficient Computing for Wildlife Tracking:Design Tradeoffs and Early Experiences with ZebraNet,”Proceedings of the 10th International Conference onArchitectural Support for Programming Languages andOperating Systems (ASPLOS 2002), pp. 96–107, 2002.

C. Kulatunga, L. Shalloo, W. Donnelly, E. Robson, and S. Ivanov,“Opportunistic Wireless Networking for Smart Dairy Farming,” ITProfessional, vol. 19, no. 2, pp. 16–23, 2017.

A. P. Silva, S. Burleigh, C. M. Hirata, and K. Obraczka, “A survey oncongestion control for delay and disruption tolerant networks,”Ad Hoc Networks, vol. 25, no. PB, pp. 480–494, 2015.

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References v

A. Roy, T. Acharya, and S. DasBit, “Quality of service in delaytolerant networks: A survey,” Computer Networks, vol. 130,pp. 121–133, 2018.

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