ATNAC 2010, Auckland, NZ By: Mohd Ezanee Rusli & Richard Harris {m.e.rusli,r.harris}@massey.ac.nz An Adaptive Coordination Scheme for the Opportunistic

ATNAC 2010, Auckland, NZ

By:

Mohd Ezanee Rusli & Richard Harris

{m.e.rusli,r.harris}@massey.ac.nz

An Adaptive Coordination Scheme for the Opportunistic Routing Protocol in

Wireless Sensor Networks

1


• Introduction – Wireless Sensor Networks (WSN)– Opportunistic Routing (OR) Protocol

• WSN System Model & OR Implementation• Enhancement Strategy of OR• Performance Analysis and Numerical Results• Conclusions and Future Work

2

Presentation Outline


• Introduction – Wireless Sensor Networks (WSN) – Opportunistic Routing (OR) Protocol

• WSN System Model and OR implementation• Enhancement Strategy of OR• Performance Analysis and Numerical Results• Conclusions

3



4

Introduction to WSNs - 1• Wireless Sensor Network (WSN) Applications:

4

Structural Monitoring System

Forest/Fire Monitoring System

Environmental Monitoring System


5

Introduction to WSNs - 2

• Properties that describe WSNs include:– Sensor nodes with resource constraints– Suitable for ad-hoc large area deployment– Variable sensor node density– A common communication pattern is between source nodes and sink (base) node– Support multi-hop routing– Dynamic network topology due to intermittent connectivity and node failures

(Courtesy of Wikipedia)


• A method for exploiting spatial and temporal diversity of wireless sensor networks with lossy links– Broadcast/multicast communication (default mode)

• Main objective is to maximise the average distance travelled of a packet per transmission – more energy efficient

• Unique feature: – The final decision to select the next relay node is made after

packet transmission– Next hop is based on connectivity

• Integrates the Network and MAC layers – Cross layer approach

6

Routing - OR Concept


OR Concept – Example (1)

7

DS

ii

i2i2

i1

DS



8

DS

i1

i2

i1

DS


9


Sink

Source


10


Sink

Source


11

Candidate Relay Set (CRS) Region

Sink

Source


• Random and unlimited Candidate Relay Set (CRS)

• Predetermined and limited CRS– Location-based

– Priority/Cost Function (i.e. Distance, Energy)

Variants of OR

12



• WSN System Model & OR Implementation• Enhancement Strategy of OR• Performance Analysis and Numerical Results• Conclusions

13



14

WSN System Model - Assumptions

(5, 90%)

(30, 30%)

(25, 35%)

(10, 85%)(10, 85%)

(15, 50%)

(5, 90%)

Source Destination

(20, 45%)

(25, 35%)

(40, 10%)

Distance

PRR(Link quality)


Selection of the forwarding candidate (CRS)[8]

Prioritisation of the forwarding candidate (CRS)

Coordination of the forwarding candidate (CRS)

15

OR Implementation

[8] K. Zheng, et al., "On Geographic Collaborative Forwarding in Wireless Ad Hoc and Sensor Networks", in International Conference on Wireless Algorithms, Systems and Applications,2007


Operating Flow Chart for OR

19

Receivers/RelaysTransmitter/Source


• Static coordination procedure can lead to a potential of high end-to-end delay in lossy WSN.

• Critical to WSN application with delay-constraint requirement.

Performance Deficiency

20

QoS Aware- OR with Adaptive Coordination Procedure




21



• Modification of OR to include QoS components• Parameters of Interest (POI)

Quality of Service (QoS) - OR

22

Delay (Latency)

Reliability

Coverage

Network/Node Lifetime


• Modification of OR to include QoS components• Parameters of Interest (POI)

Quality of Service (QoS) - OR

23

Delay (Latency)Reliabilit

y

Coverage

Network/Node

Lifetime


• CRS Quality Score (QS)– Utilising the implicit acknowledgement procedure– The ratio of implicit acknowledgement packet from

nodes in CRS over the total number of packets sent– The higher the QS value the better the

quality

Adaptive Coordination Delay

24

tiPjA

CRSjP

AQS

ti

j

i

ti

j

ij

time toup node fromsent packet of total the node frompacket ement acknowledgimplicit ofnumber

,

,

,

)10( QS


• Exponential Weighted Moving Average

• Tuning parameter,

Quality Score Estimation

25

interval timeestimation

)1()1()(

k

kiQSnewQSkiQS

10


Flow Chart for QoS-OR (1)

26

Receivers/RelaysTransmitter/Source


Flow Chart for QoS-OR (2)

27

Transmitter/Source Receivers/Relays


28

Performance Metrics

End-to-end delay

Packet Success Rate

Energy Efficiency




29



• Matlab-based probabilistic wireless sensor network discrete-event simulator, Prowler[14]

• Realistic Lossy Channel model [15]• CSMA/CA model - TinyOS

Simulation

30

[14] G. Simon. Probabilistic wireless network simulator. http://www.isis.vanderbilt.edu/projects/nest/prowler[15] M. Zuniga and B. Krishnamachari, "Analyzing the Transitional Region in Low Power Wireless Links", in First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, IEEE SECON '04., 2004

http://www.isis.vanderbilt.edu/projects/nest/prowler


31

Simulation SetupParameters Values

Path loss exponent,φ 3.5

Log-normal shadowing variance, σ 3.8

Receiver Sensitivity -105dBm

Transmission Power 2.5mW(4dBm)

Data Packet Size 400 bits

MAC Minimum Waiting Time 2.5ms

MAC Minimum Backoff Time 5ms

Delay Coefficient, 20ms

QS Estimation interval 0.5s

QSthreshold 0.3

Voltage 3V

Reception Energy 4.5mA

Idle Energy 0.5mA


50 100 150 200 250 300 350 400 450 5000.2

0.21

0.22

0.23

0.24

0.25

0.26

Time (second)

En

d-t

o-e

nd

De

lay

(sec

on

d)

OR-Static CRS

OR-Adaptive CRS

32

Numerical Results - 1End-to-end delay

• 10 runs• No Retransmission• Alpha, = 0.9• 75 Nodes


50 100 150 200 250 300 350 400 450 5000

0.1

0.2

0.3

0.4

0.5

0.6

Time (second)

Pa

cke

t Su

cce

ss R

ate

OR - Static CRSOR - Adaptive CRS

33

Numerical Results - 2Packet Success Rate



Numerical Results - 3

34

50 100 150 200 250 300 350 400 450 5003

3.2

3.4

3.6

3.8

4

4.2

4.4

4.6

4.8

5x 10

-4

Time (second)

En

erg

y E

ffici

en

cy

OR-Static CRSOR-Adaptive CRS

Energy Efficiency


(pa

cke

t/Jo

ule

)


• OR protocol was adopted with the objective to improve communication efficiency through spatial and temporal diversity especially in lossy wireless sensor network

• The proposed adaptive coordination scheme can improve the overall performance of OR in term of end-to-end delay, packet success rate and energy efficiency

• Our future work will include implementing other strategies to ensure OR can include additional QoS requirements

Conclusions and Future Work

35


Q & A

36

Documents

ATNAC 2010, Auckland, NZ By: Mohd Ezanee Rusli & Richard Harris {m.e.rusli,r.harris}@massey.ac.nz An Adaptive Coordination Scheme for the Opportunistic