This is a new routing protocol for under water sensor network with 1. Energy consumption 2.Better Link Expiration time measurement 3.Fuzzification 3.1.Link Expiration Time(LET) 3.2.Number Of Packets 4.Crisp value of Active node (Activeness Ratio) 5.Late node are at sleep mode with sequence 6.Number of packet forwarding according energy of a node

1. Grid Based Fuzzy Optimized Routing
Protocol for Under Water Sensor Networks
CSE ,MBSTU Defense of Research
Presented By:
Kazi Tiomour Rahman Tamim
ID:CE-10018
A S M Zakaria
ID:CE-10026
Supervised By:
Md. Mahfuz Reza
Lecturer
Dept. Of CSE, MBSTU

2. Contents
• Introduction
• Characteristics of UWSNs
• Challenges of UWSNs
• Contributions to the Work
• Related Works
• Network Architecture of UWSNs
• Proposed Routing Protocol
• Network Architecture of Proposed Routing Protocol
• Protocol Overview
• Protocol Design
• Network area division by Grid
• Energy Estimation of Active Node
• Activate Node Selection Phase with in cell of Grid
• Sequence Calculation of Sleep nodes
• Fuzzy Optimized Active Node
• Flow Chart
• Algorithm
• Conclusion
• Reference

3. Introduction
• Oceanographic data collection , water environment
monitoring
• hidden knowledge and unknown resources in
underwater.
• Marine surveillance, river and sea pollution detection.
• archaeology, seismic and volcanic prediction, oil
monitoring.
.

4. Introduction(Cont…)
• consist of a variable number of sensors.
• Can monitor over a given area.
• Sensor network technology is effective and efficient .
• Sensor nodes can communicate between themselves.
• can sense their residing environment and various
activities.

5. Characteristics of UWSNs
• Low cost
• Computation ,sensing, communication , storage
• Vehicle tracking , Habitat Monitoring ,Structural
Monitoring
• Size small
• Low power
• Multifunctional
• Can easily communicate with shortest distances
• For example
• Thermal, Visual, Light, Pressure, Temperature,
Beacon , Humidity etc…

6. Challenges Of UWSNs
• Low battery power
• No real time monitoring
• Low bandwidth and high error rates
• Limited Storage
• Mobility of nodes
• High propagation delay
• Common errors
• Wireless communication
• Node failure are expected
• Scalability to a large number of sensor nodes
• Survivability in harsh environments
• Experiments are time and space intensive

7. Contribution to the work
• Grid Based Architecture
• Energy consumption
• Better Link Expiration time measurement
• Fuzzification
• Link Expiration Time(LET)
• Number Of Packets
• Crisp value of Active node (Activeness Ratio)
• Late node are at sleep mode with sequence
• Number of packet forwarding according energy of a node

8. Related protocols
• Sector-based Routing
• a node knows its own location
• node predicts the location of the destination node
• Collect the knowledge of destination location
• Delivery ration decreases as node mobile
• Each sector node main desire is to send at sink node
• Fuzzy Logic Optimized Vector Protocol
• Use 3D architecture
• Degrade the average end to end delay occurs at vector
based forwarding
• The Geographic Adaptive Fidelity (GAF) protocol
• energy-aware unicast location-based routing protocol
• is primarily designed for networks with mobile nodes. The network
region is divided into a virtual grid.

9. Related protocols(Cont….)
• Focused Beam Routing Protocol
• No dynamic angle for drawing beam at each stage.
• Use RTS and CTS procedure
• Source node must be aware of its own location , its final destination, but
not those of other nodes.
• Exists an imaginary line.
• Node must relay within imaginary line left and right.
• Power level increase if left side no node available to search at right site.
• Parabola Based Routing in Underwater
• Use parabola to transmit packets from source to destination.
• Best suited node is selected at each time to forward ,to optimize energy.
• Hop by hop acknowledgement process has been devised.
• Directional flooding based
• Node floods around the network ,forward using link quality.

10. Network Architecture Of UWSNS
Figure-1 : Network Architecture UWSNs

11. Network Architecture Of Proposed
Routing Protocol
Figure-2:Network Architecture

12. Network Architecture Of Proposed
Routing Protocol(Cont…)
Grid
One
Figure-3:Network Architecture(Active Node )

13. Proposed Routing Protocol(OverView)
 Total network is divided into different three dimensional grid
 Only one node with in a grid is selected as an Active Node ,remaining nodes
will in sleeping mode having their Activeness sequence
Active Node Selection
Measurement of each node’s residual energy within a grid
Measure Link Expiration Time(LET) of each node
Calculating the Number of packets according to each node’s residual
energy
Fuzzification of Link Expiration Time(LET) ,Number of Packets to
determine Activeness Ratio(AR).
After sorting of Activeness ratio in a (AR) table.
The top node of (AR) table will be selected as active node.

14. Proposed Routing Protocol(Cont….)
• The Active Node will till the number of packet will be zero.
when the number of packets of the Active node will zero in
sends a request to sleep to the next sequence node.
• When Active node will get go to sleep message from the next
sequenced node then it will go to sleep mode and next
sequenced node will be Active Node.
• Node Forwarding phase
• Active node from one cell will forward packets to the
upper cell active node
•
•

15. Illustration the number of packets of each node
 Total Energy of a node N1,
ET(N1)=ET(N1)-[Ep(N1)+Ea];
Here Ep =Energy Cost Per Packet Send/Receive
Ea =Energy Cost Per Hour Activation
For example
Supposed
nodes
Initial
Energy
Number of
initial packets
Ea Ep Number of
packets
send/receive
Activatio
n Hour
ET(Nn)=ET(Nn) -[Ep(Nn)+Ea]
Updated Energy
N1 5j 20 1µj 0.2j 5 5 3.999995=4j
N2 7j 30 1µj 0.2j 4 2 6.2j
N3 6j 25 1µj 0.2j 9 3 4.2j
N4 3j 10 1µj 0.2j 6 1 1.8j

16. Link Expiration Time Measurement and
Architecture
m
monn
t
ontmt
2
4
0
2
22



Link Expiration Time Between Nodes:
Where t is the LET , m , n used to calculate
Distance between two nodes.

17. Fuzzification
Very
little
little medium high higher
1
(0,0)
Numbers of Packets
3 6 9 12 14 15
Degreeof
membership
Very
low
low moderate many more
Degreeof
membership
1
(0,0) 100 200 300 400
Link expiration Time(LET)(sec)
The input and output variables are mapped into fuzzy sets
using appropriate membership function
Membership Function are:

18. Fuzzification(cont…)
Activeness Ratio
Very low
low moderate good best
1
(0,0) 15 40 65 100
Activeness Ratio (%)
Degreeof
membership

19. Rule Evaluation
Numbers Of
Packets
Link
Expiration
Time(Sec)
Activeness
Ratio (%)
Very little Very low Very low
Very little low Very low
Very little medium Moderate
Very little many good
Very little more best
little Very low Very low
little low low
little medium moderate
little many moderate
little more good
medium Very low Very low
medium low low
Numbers Of
Packets
Link
Expiration
Time(Sec)
Activeness
Ratio (%)
medium medium moderate
medium many good
medium more best
High Very low Very low
High low Very low
High medium moderate
High many good
High more best
Higher Very low Very low
Higher low Very low
Higher medium good
Higher many good
Higher more Moderate

20. Center Of Gravity(COF) Value
Measurement of Activeness
Numbers Of
Packets
Link Expiration
Time(Sec)
Activeness Ratio
(%)
N1(7) 300 55.5%
N2(9) 300 55.9%
N3(14) 400 80.1%
N4(10) 100 42.7%
N5(5) 400 65.8%
Activeness Ratio Table
array Of Active Nodes
N3
N5
N2
N1
N4
Sample COF :

21. Algorithm for Active Node
Set up initial nodes in the given grid area
Assign nodes with capability of showing their Activeness ratio
While nodes are being relayed
do
check the Activeness Ratio(AR)
if(current_AR>=Threshold)
then ART[i]++;
else
not enter to the Table array of AR .
end if;
End while;

22. Algorithm for Active Node Selection
1) Initialize j,temp True
2) while(true)
3) loop j< NoOfNode
4) if ActRatio [j-1] < ActRatio [j] then
5) temp ActRatio [j-1]
6) ActRatio [j-1] ActRatio [j]
7) ActRatio [j] temp
8) end if
9) j j+1
10) end loop
11) end while
12) return Sequence of ActRatio

23. Flow Chart of the Proposed Routing protocol(packet
forwarding )
start
Enter Node field of a grid
Is Active node exists
in upper grid
yes
Forward Packet
No
Search at partial upper grid
End
Data Packet
Ensure Forwarding Decision
Assign Active node as forwarding node
Is Active node
exists
yes
No
Discard the Packet

24. Simulation and implementation
Figure: Grid Input

25. Generated Grids

26. Input within Grids and Activeness Sequence
Figure: (a): Sample Input of LET
and No of Packet for 1st Iteration
at grid one
Figure: (a): Activeness Ratio and
sequence of each node at grid one

27. Active node at each grid

28. More iterations
Figure: Input LET ,NOP Figure: Activeness Ratio

29. ghh
Fuzzy Viewer
Simulation With Fuzzy Inference Engine

30. Fuzzy Input(Number Of Packets )

31. Fuzzy Input(Link Expiration Time )

32. Fuzzy Output(Activeness Ratio)

33. Fuzzy Rules

34. Fuzzy Rules Viewer

35. Fuzzy Surface Viewer

36. Performance Evaluation
 Performance metrics:
 Network Life Time
 Total Energy Consumption
 Average End to End Delay

37. Performance Evaluation(cont…)
(a)Total energy consumption of FBR with different node mobility (b)Total energy consumption of GBFOR protocol with different node
mobility
Figure 8: Comparison of total energy consumption of GBFOR protocol with FBR protocol

38. Performance Evaluation(Cont…)
Fig:(a)Comparison of network life time between GBFOR and FBR Fig:(a)Comparison of end to end delay between GBFOR and
FBR

39. Conclusion and Future Plan
GBFOR protocol has been designed keeping in mind the
challenges involved in energy consumptions and
REQ,RES procedure in underwater conditions. As
fuzzy optimized easy to work with different quality nodes
and network life time high. In the future, we plan to
adopt detour mechanism to avoid the void of zone and to
develop better mobility handle method.

40. References
[1]. Josep Miquel Jornet, Milica Stojanovic, Michele Zorzi. “Focused
Beam Routing Protocol for Underwater Acoustic
Networks”,WUWNet’08, September 15, 2008, San Francisco, CA.
[2]. Md.Asraf Uddin and Mamun-or-Rashid, “Link Expiration Time
Aware Routing Protocol for UWSNs”, Hindawi Publishing
Corporation volume:2013, Article ID6252,
http://dx.doi.org/10.1155/2013/625274.
[3]. Daeyoup Hwang, Dongkyun Kim. “DFR: Directional Flooding
Based Routing Protocol for Underwater Sensor Networks”,
978-1-4244-2620-1/08 ©2008 IEEE
[4]. Reza Javidan,Hamideh Rafiee.” A New Energy Efficient and Depth
based routing protocol for underwater sensor network”
British Journal of Science January 2013,vol.8(1).
[5]. Z. Zhou, J.-H. Cui, and S. Zhou. Localization for large-scale
underwater sensor networks. UCONN CSE Technical Report: UbiNet-
TR06-,http://www.cse.uconn.edu/jcui/publications.html, Dec. 2006.

41. References(cont…)
[6]. Sohrab Sarafiabadi , Sara Parvaneh,SeyedKeyvan
Babai,Yashar Sarafiabadi .“Fuzzy Logic Optimized Vector
Protocol for Underwater Sensor Network” , IPCSIT vol. 41 (2012)
© (2012) IACSIT Press, Singapore
[7]. Sanjay K. Dhurandher, Mohammad S. Obaidat .” Optimizing
Energy through Parabola Based Routing in Underwater sensor
network“,IEEE 2011.
[8]. Ian F. Akyildiz, Georgia Institute of Technology, USA.”Wireless
sensor network”.
[9]. P.S.Hiremath, Shrihari M.Joshi .” Energy Efficient Routing
Protocol with Adap Fuzzy Threshold Energy for MANETs ”.
IJCNWC), ISSN: 2250-3501 Vol.2, No.3, June 2012.
[10]. Partha Sarathi Banerjee, Paulchoudhury, S. R. Bhadra
Chaudhuri .” Fuzzy Membership Function in a Trust Based
AODV for MANET ”. October 2013 i (http://www.mecs-
press.org/) DOI: 10.5815/ijcnis.2013.12.04.
[11]. Sinchan Roychowdhury,ChiranjibPatra “The Geographic
Adaptive Fidelity (GAF) protocol (Xu et al. 2001)”.