Routing on Roles - TU Dresden
Transcript of Routing on Roles - TU Dresden
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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
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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
M1
4
Wireless range do not allow end-to-end connectivity• Contact opportunity
• Knowledge about the topology
• Nodes, Stations, Mobile
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A communication between static stations
. .
.
.
.
.
SBSA
M1
4
Wireless range do not allow end-to-end connectivity
• Contact opportunity
• Knowledge about the topology
• Nodes, Stations, Mobile
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A communication between static stations
DST:SB
. .
.
.
.
.
SBSA
M1
4
Wireless range do not allow end-to-end connectivity• Contact opportunity
• Knowledge about the topology
• Nodes, Stations, Mobile
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A communication between static stations
DST:SB
. .
.
.
.
.
SBSA
M1
4
Wireless range do not allow end-to-end connectivity
• Contact opportunity
• Knowledge about the topology
• Nodes, Stations, Mobile
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A communication between static stations
DST:SB
DST:SB
. .
.
.
.
.
SBSA
M1
4
Wireless range do not allow end-to-end connectivity• Contact opportunity
• Knowledge about the topology
• Nodes, Stations, Mobile
![Page 10: Routing on Roles - TU Dresden](https://reader030.fdocuments.in/reader030/viewer/2022012713/61abe2eb640eba1934397202/html5/thumbnails/10.jpg)
A communication between static stations
DST:SB
DST:SB
. .
.
.
.
.
SBSA
M1
4
Wireless range do not allow end-to-end connectivity• Contact opportunity
• Knowledge about the topology
• Nodes, Stations, Mobile
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A communication between static stations
DST:SBDST:SB
DST:SB
. .
.
.
.
.
SBSA
M1
4
Wireless range do not allow end-to-end connectivity• Contact opportunity
• Knowledge about the topology
• Nodes, Stations, Mobile
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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
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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
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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
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Challenge networks
Pictures [1, 2, 3, 4]
5
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
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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
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Challenges in DTN routing
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A concrete use-case
SA SB SC SD SE
SH
SI
SK
SJ
SG
SF
SL
M1
6
• Rovers move over defined paths
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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
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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?
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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?
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The routing decision
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?
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The routing decision
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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What are the rover priorities?
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The routing decision
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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To which peers should the bundle be forwarded?
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The routing decision - Replication Based
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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The routing decision - Replication Based
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• Bundle is replicated at every contact
• Every node is using the same algorithm
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The routing decision - Replication Based
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• Bundle is replicated at every contact
• Every node is using the same algorithm
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The routing decision - Replication Based
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The routing decision - Replication Based
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SummaryPositive
• Context independentNegative
• Waste resources• Congestion prone• Poor performance under loador network density
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The routing decision - Probability Based
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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The routing decision - Probability Based
elivery predictability is the transitive likelihood of encounter13
• Bundle is replicated to peers that arelikely to encounter the destination
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The routing decision - Probability Based
elivery predictability is the transitive likelihood of encounter13
ProPHETv2Routing decision based on:
• Peer delivery predictability• Transitive delivery predictability• Aging
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The routing decision - Probability Based
elivery predictability is the transitive likelihood of encounter13
ProPHETv2Routing decision based on:
• Peer delivery predictability• Transitive delivery predictability• Aging
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The routing decision - Probability Based
elivery predictability is the transitive likelihood of encounter13
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The routing decision - Probability Based
elivery predictability is the transitive likelihood of encounter13
SummaryPositive
• Smaller amount of replicas
• Better performance under loadNegative
• Requires a well defined pattern
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The routing decision - Deterministic
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
.
.
14
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The routing decision - Deterministic
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The routing decision - Deterministic
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Contact Plan from all devices available
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The routing decision - Deterministic
15
Contact Plan from all devices availableBuild a multigraph*
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The routing decision - Deterministic
15
Contact Plan from all devices availableBuild a multigraph*Calculate shortest path
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The routing decision - Deterministic
15
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The routing decision - Deterministic
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The process repeats at every device for each bundle
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The routing decision - Deterministic
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The routing decision - Deterministic
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SummaryPositive
• Smallest amount of replicas
• Best performance under loadNegative
• Requires a contact plan
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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]
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A word about congestion in DTN
ObjectiveRouting
AlgorithmContext
.
.
16
”... 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]
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Congestion Mitigation
Congestion
ControlCongestion
ControlSelfishness
FairnessQueueing
Dely/Jitter
ObjectiveRouting
AlgorithmContext
.
.
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The need for adaptation
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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
• 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
• 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
SA SB SC SD SE
SH
SI
SK
SJ
SG
SF
SL
.
.
.
.
M1
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Routing adaptation
SA SB SC SD SE
SH
SI
SK
SJ
SG
SF
SL
.
.
.
.
M1
19
An accurate contact plan
...is no assurance against topology changes
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Routing adaptation
SA SB SC SD SE
SH
SI
SK
SJ
SG
SF
SL
.
.
.
.
M1
19
An accurate contact plan...is no assurance against topology changes
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Routing adaptation
SA SB SC SD SE
SH
SI
SK
SJ
SG
SF
SL
.
.
.
.
M1
19
• An alternative path is found
• Contact plan becomes invalid
• Historical information is currently useless
• Switch to a replication-based variant
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Routing adaptation
SA SB SC SD SE
SH
SI
SK
SJ
SG
SF
SL
.
.
.
.
M1
19
• An alternative path is found
• Contact plan becomes invalid
• Historical information is currently useless
• Switch to a replication-based variant
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Routing adaptation
SA SB SC SD SE
SH
SI
SK
SJ
SG
SF
SL
.
.
.
.
M1
19
• An alternative path is found
• Contact plan becomes invalid
• Historical information is currently useless
• Switch to a replication-based variant
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Routing adaptation
SA SB SC SD SE
SH
SI
SK
SJ
SG
SF
SL
.
.
.
.
M1
19
• The way become free
• Switch to replication-based followed byprobabilistic or schedule-based approach
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Adaptation by means of Roles
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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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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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