Low Power, Low Delay: Opportunistic Routing meets Duty Cycling

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Low Power, Low Delay: Opportunistic Routing meets Duty Cycling Olaf Landsiedel 1 , Euhanna Ghadimi 2 , Simon Duquennoy 3 , Mikael Johansson 2 1 Chalmers University of Technology, Sweden 2 KTH Royal Institute of Technology, Sweden 3 Swedish Institute of Computer Science (SICS), Sweden IPSN 2012 Presenter: SY

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Low Power, Low Delay: Opportunistic Routing meets Duty Cycling. Olaf Landsiedel 1 , Euhanna Ghadimi 2 , Simon Duquennoy 3 , Mikael Johansson 2 1 Chalmers University of Technology, Sweden 2 KTH Royal Institute of Technology, Sweden 3 Swedish Institute of Computer Science (SICS), Sweden - PowerPoint PPT Presentation

Transcript of Low Power, Low Delay: Opportunistic Routing meets Duty Cycling

Page 1: Low Power, Low  Delay: Opportunistic  Routing meets Duty Cycling

Low Power, Low Delay: Opportunistic Routing meets Duty Cycling

Olaf Landsiedel 1, Euhanna Ghadimi2, Simon Duquennoy3, Mikael Johansson2

1Chalmers University of Technology, Sweden2KTH Royal Institute of Technology, Sweden

3Swedish Institute of Computer Science (SICS), SwedenIPSN 2012

Presenter: SY

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This Paper

• Opportunistic Routing for wireless sensor network– Duty cycled nodes

• Benefits– Improve energy efficiency– Reduce end-to-end delay– Increase resilience to link dynamics

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Unicast Routing in Duty Cycled WSNs‐• Routing protocol: selects next hop• MAC: wait for next hop to wakeup– Assume: no synchronization

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Unicast Routing in Duty Cycled WSNs‐• Routing protocol: selects next hop• MAC: wait for next hop to wakeup– Assume: no synchronization

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Opportunistic Forwarding

• The node that– Wakes up first– Successflly receives the packet– Provides routing progress

• Forward the packet

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Outline

• System design• Evaluation• Conclusion

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DODAG

• Topology: DODAG– Destination oriented directed acyclic graph

• Requirements of routing metric– Builds loop free DODAG– Minimize energy: radio-on time– Minimize delay

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Expected Duty Cycled Wakeups (EDC)

• Single hop EDC: 1/(sum of neighbors link quality) – Left case: A has a single neighbor with a perfect link, its single hop

EDC is 1/1 = 1;– Right case: A has two neighbors both having perfect links, its

single hop EDC is 1/(1 + 1) = 0:5;– Middle case: A has two neighbors with link qualities 1 and 0.25.

Its single hop EDC is 1/(1 + 0:25) = 0:8.

Single hop EDC

Link quality

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Overall EDC

• Overall EDC– Sum of single hop EDC and neighbors’ EDC

• Which neighbors to include?– Forwarder set

Single hop EDCEDC of neighbor

Weight

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Forwarders Set

• Sort neighbor nodes by EDC• Add one by one (from lowest)• Find minimum EDC

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Forwarding Cost

• Forwarding cost w– Constant value, transmission penalty– Increase w decrease forwarders set• Fewer hops to destination• Increase delay and energy consumption

– Too low: increase the risk of routing loop• To balance delay and energy with routing

progress and stability

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Link Estimation

• Link quality = (Rate of packet overheard)/(forwarding rate)

• Rate of packet overheard– Wakeup, listen to the radio, record packet overheard

• Forwarding rate– Header field contain the average forwarding rate

• Bootstrap– Probing during initialization

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Unique Forwarder

• Make sure only one node forward the packet1. Majority of cases only one receiver

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Unique Forwarder – Cont.

• Coordination algorithm– Demand a single ACK• If (sender) receives multiple ACK

– Resend the packet• If (receiver) detect link-layer duplicate

– Send second ACK with 50% probability

– Data transmission overhearing• If overhears same packet, cancels transmission

– Network-layer duplication detection• Detect duplication at network layer

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Outline

• System design• Evaluation• Conclusion

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Setup• Testbed

– Indriya(Singapore): 120 nodes– Twist(Berlin): 96 nodes

• Compare– CTP

• Metrics– Delay, Duty cycle, # of TX nodes, Reliability

• Implementation– TinyOS, default MAC– Wakeup every 2s (optimal for CTP)– Randomly generate a packet every 4 minutes

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System Calibration

• Choose w=0.1

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Indriya, 0 dBm Tx Power

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Indriya, -10 dBm Tx Power

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Twist, 0 dBm Tx Power

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Impart of Churn

• Remove average 10 nodes every 15 minutes• Reduce from 120 to 30 nodes

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Convergence

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Wakeup Interval

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Outline

• System design• Evaluation• Conclusion

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Discussion And Limitation

• Works best at high network density• Optimal at lower wakeup rates– Compare to CTP

• At high wakeup rate– CTP and ORW are similar

• Not well suited for high throughput applications

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Conclusion

• New routing metric– Taken energy into account

• Real implementation– Previous works mostly analytical and simulation

• Paper writing– A bit harder to get the big picture