Delay-aware Routing in Low Duty-CycleWireless Sensor Networks

Guodong Sun and Bin Xu

Computer Science and Technology Department

Tsinghua University, Beijing, China

IEEE Wicom 2011

Outline

• Introduction• Network model• Algorithm design• Simulation evaluation• Conclusion

Introduction

• Advances in microelectronics, wireless networking make wireless sensor networks applicable– Civilian–Military

Introduction

• Sensor nodes work relying on– Capacity-small– Unrechargeable batteries

Introduction

• Energy consumption of Sensor nodes– Idle listening– Packet overhearing

Introduction

• To save sensors’ energy and then prolong the system lifetime– Low duty-cycle

active activesleep sleep sleepSensor sleep

Introduction

• Problem experienced by low duty-cycle sensor networks– Long delivery delay caused by the sleep latency of

sensors

• The delay is critical to the performance of systems–Military surveillance– Target tracking–Monitoring

Goal

• Designing a delay-aware routing algorithm for low duty-cycle sensor networks – Reduce the network delay– Data packet drop rate

Network model

• N sensor nodes• L*L square• Communication range = r• Multi-hop

Network model

• Duty cycle of sensor– Active– Sleep

active activesleep sleepSensor A sleep

EX: duty cycle = 40%

(5|1,5)

Network model

• Channel access– CSMA/CA like method• REQ/CLR

– Successful transmission• •

rXX BA

rXX BK

Locations of node A,B and other node K

Network model

• Delay model– Queuing delay– Transmission delay– Propagation delay

Node A’s queue

packet1

packet2

packet3

active active…. ………Sensor B active

Queuing delay:

Algorithm design

• Two phases– Network initializing– Dynamic forwarding

Network initializing

IDWorking schedule

Layer number

A

S

C

D

B

• Broadcast message

Network initializing

• Layered topology

A

S

C

D

B

0

1 1 1

2

Dynamic forwarding

• Forwarding set– FA={S}

– FB={S}

– FC={S}

– FD={B,C}

A

S

C

D

B

0

1 1 1

2

B : (100|5,30,62)

C : (100|3,24,30)

Dynamic forwarding

• Forwarding sequence– SD={C,B,C,C,B,B}

Node D’s queue

packet1

packet2

packet3

C

B

C

C

B

B

A

S

C

D

B

0

1 1 1

2

B : (100|5,30,62)

C : (100|3,24,30)

3

5

24

30

30

62

Performance analysis

• Simulation setup

• Comparison– Static shortest-path routing(SSPR)

parameter value

Square area of side 150

Work schedule length 150τ / 1τ=20ms

Packet generate rate 3 packets / 5minutes

Simulation result

• 150 sensors

Simulation result

• 150 sensors

Simulation result

• 150 sensors

Simulation result

• Duty cycle = 5%

Simulation result

• Duty cycle = 5%

Simulation result

• Duty cycle = 5%

Simulation result

• Sensor density = 8, duty cycle = 5%

Simulation result

• Sensor density = 8, duty cycle = 5%

Simulation result

• Sensor density = 8, duty cycle = 5%

Conclusions

• The authors proposed a delay-aware routing algorithm for low duty-cycle sensor networks– Achieves shorter delay by dynamically selecting

forwarders

• Simulation results demonstrate that our algorithm improves– delivery delay– Reduces the network drop rate– Saving the energy of sensors

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