Opportunistic Flooding in LowDutyCycle Wireless Sensor Networks with Unreliable Links

1
Opportunistic Flooding in Low-Duty-Cycle Wireless
Sensor Networks with Unreliable Links

• Shuo Guo, Yu Gu, Bo Jiang and Tian He
• University of Minnesota, Twin Cities

2
Background

• Why a low-duty-cycle WSN is needed?
• Growing need for sustainable sensor networks
• Slow progress on battery capacity

3
Background

• Sleep latency in low-duty-cycle wireless sensor
  networks

Sender
t
Receiver

t
Active State
Dormant State
Low Duty Cycle gt Long Network Lifetime
4
Motivation

• Why is Flooding in low-duty-cycle WSNs different?
• No longer consists of a number of broadcasts.
• Instead, it consists a number of unicasts.

C
B
D
C
B
D
B
C
D
A
t
A
Active State
Dormant State
5
Motivation

• Existing solutions are not suitable to be
  directly applied to low-duty-cycle wireless
  sensor networks

• X. Chen, M. Faloutsos, and S. Krishnamurthy.
  Power Adaptive Broadcasting with Local
  Information in Ad Hoc Networks. ICNP03.
• J. W. Hui and D. Culler. The Dynamic Behavior of
  a Data Dissemination Protocol for Network
  Programming at Scale. SenSys04.
• P. Kyasanur, R. R. Choudhury, and I. Gupta. Smart
  Gossip An Adaptive Gossip-based Broadcasting
  Service for Sensor Networks. MASS06.
• P. Levis, N. Patel, D. Culler, and S. Shenker.
  Trickle A Self-Regulating Algorithm for Code
  Propagation and Maintenance in Wireless Sensor
  Networks. NSDI04.
• L. Li, R. Ramjee, M. Buddhikot, and S. Miller.
  Network Coding-Based Broadcast in Mobile Ad-hoc
  Networks. INFOCOM07.
• M. J. Miller, C. Sengul, and I. Gupta. Exploring
  the Energy-Latency Trade-Off for Broadcasts in
  Energy-Saving Sensor Networks. ICDCS05.
• F. Stann, J. Heidemann, R. Shroff, and M. Z.
  Murtaza. RBP Robust Broadcast Propagation in
  Wireless Networks. SenSys06

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Network Model and Assumptions

• Local synchronization of sensor nodes
• Pre-determined working schedules shared with all
  neighbors.
• Unreliable wireless links
• The probability of a successful transmission
  depends on the link quality q
• Flooding packets are only forwarded to a node
  with larger hop-count to avoid flooding loops

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Design Goal

• Fast data dissemination shorter flooding delay
• Less transmission redundancy less energy cost

Two challenging issues

• Redundant transmissions
• Collisions

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Tree-based Simple Solution

• Energy-Optimal Tree
• No redundant transmissions
• Long flooding delay

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Main Idea

• Adding opportunistically early links into the
  energy-optimal routing tree

• Early Packets
• Help reduce delay
• SEND

Decision Making

• Late Packets
• Redundant
• DO NOT SEND

for each neighbor

• Early packets are forwarded to reduce delay
• Late packets are not forwarded to reduce energy
  cost

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How to Determine Early Packets?
Q1When will B receive As packet? Q2Is this
time early enough?

• Flooding delay distribution (pmf) at node B
• Delay threshold Dp based on a threshold
  probability p
• Expected Packet Delay (EPD) the packet delay
  when B receives As packet

By the time Dp, the probability that B has
received the packet is p
Bs delay distribution
p-quantile
EPD lt Dp, SEND EPD gt Dp, DO NOT SEND
t
Dp
Delay distribution that B receives packets from
its parent!
Early Packets EPD
Late Packets EPD
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How to Determine Early Packets?

• Flooding delay distribution (pmf) at node B
• Delay threshold Dp based on a threshold
  probability p
• Expected Packet Delay (EPD) the packet delay
  when B receives As packet

Bs delay distribution
p-quantile
t
Dp
Early Packets EPD
Late Packets EPD
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12
Delay Distribution Computation
0.9
0.8
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How to Determine Early Packets?
v

• Flooding delay distribution (pmf) at node B
• Delay threshold Dp based on a threshold
  probability p
• Expected Packet Delay (EPD) the packet delay
  when B receives As packet

Bs delay distribution
p-quantile
t
Dp
Early Packets EPD
Late Packets EPD
13
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Expected Packet Delay Computation
EPD 24
As second try to B
A receives packet
As first try to B
A is expected to transmit twice!
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How to Determine Early Packets?
v

• Flooding delay distribution (pmf) at node B
• Delay threshold Dp based on a threshold
  probability p
• Expected Packet Delay (EPD) the packet delay
  when B receives As packet

v
Bs delay distribution
p-quantile
t
Dp
Early Packets EPD
Late Packets EPD
15
16
Final Decision Making
Dp 16
EPD 24

• For p 0.8
• Dp 16lt EPD 24.
• A will not start the transmission to B!

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How early an early packet should be?
Delay Distribution
p-quantile
Dp
t
Late Packets EPD
Early Packets EPD

• Small p value smaller Dp, fewer early packets,
  longer flooding delay, less energy cost gt
  Energy-Sensitive
• Large p value larger Dp, more early packets,
  shorter flooding delay, more energy cost gt
  Time-Sensitive

18
Evaluation

• Test-bed Implementation
• 30 MicaZ nodes form a 4-hop network
• Randomly generated working schedules
• Duty cycle from 1 to 5
• Simulation Setup
• Randomly generated network, 2001000 nodes
• Randomly generated working schedules
• Duty cycle from 120

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Evaluation

• Baseline 1 optimal performance bounds
• Delay optimal collision-free pure flooding
• Energy optimal tree-based solution
• Baseline 2 improved pure flooding
• Two techniques are added to avoid collisions
• Link-quality based back-off scheme
• p-persistent back-off scheme

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Simulation Results
Improved Pure Flooding
Flooding delay vs. Duty Cycle
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Simulation Results
Improved Pure Flooding
Improved Pure Flooding
Opportunistic Flooding
Flooding delay vs. Duty Cycle
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Simulation Results
Improved Pure Flooding
Improved Pure Flooding
Improved Pure Flooding
Opportunistic Flooding
Opportunistic Flooding
Optimal Delay Bound
Flooding delay vs. Duty Cycle
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Simulation Results
Improved Pure Flooding
Energy Cost vs. Duty Cycle
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Simulation Results
Improved Pure Flooding
60
Opportunistic Flooding
Energy Cost vs. Duty Cycle
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Simulation Results
Improved Pure Flooding
60
Opportunistic Flooding
Optimal Energy Bound
Energy Cost vs. Duty Cycle
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Test-bed Performance
Improved Pure Flooding
Opportunistic Flooding
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Flooding delay vs. Duty Cycle
Energy Cost vs. Duty Cycle
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Test-bed Performance
Ratio of Opportunistically Early Packets

• Hop Count 2

• Hop Count 4

• Hop Count 1

• Hop Count 3

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Test-bed Performance
Improved Pure Flooding
Opportunistic Flooding
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Flooding delay vs. Duty Cycle
Energy Cost vs. Duty Cycle
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Summary

• The flooding process in low-duty-cycle networks
  consists of a number of unicasts. This feature
  calls for a new solution
• Opportunistically early packets are forwarded
  outside the energy-optimal tree to reduce the
  flooding delay
• Late packets are not forwarded to reduce energy
  cost
• Evaluation reveals our design approaches both
  energy- and delay-optimal bounds

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Decision Conflict Resolution

• The selection of flooding senders
• Only a subset of neighbors are considered as a
  nodes flooding packet senders.
• Flooding senders have a good enough link quality
  between each other.
• Avoid hidden terminal problem without the
  overhead caused by using RTS/CTS control packets

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Decision Conflict Resolution

• Link-quality based back-off scheme
• Better link quality, higher chance to send first
• Further avoids collision when two nodes can hear
  each other and make the same decision
• Further saves energy since the node with the best
  link quality has the highest chance to send