The WSN is made of nodes from a few to several hundred, where each node is connected to one or several sensors. The basic components of a node are o Sensor and actuator - an interface to the physical world designed to sense the environmental parameters like pressure and temperature. o Controller - is to control different modes of operation for processing of data o Memory - storage for programming data. o Communication - a device like antenna for sending and receiving data over a wireless channel. o Power Supply- supply of energy for smooth operation of a node like battery.

1. Implementation of Fault Node Recovery
Algorithm For a Wireless Sensor Network
Presented By:
Yogesh V K

2. Agenda
 Introduction
 Related Work
 Problem Statement
 Proposed Approach
 System Design
 Detail Design
 Pseudo Code
 Snap Shots
 Conclusion
 Future Enhancement

3. INTRODUCTION
Wireless Sensor Networks
 WSN combines sensing, computation, and
communication into single tiny device called
sensor node.
 Group of sensors nodes linked by wireless media
to perform distributed sensing task
 The main goal of the WSN is to collect data
from the environment and send it to a sink node.

5. Types of wireless sensor networks
Unstructured WSN
 Ad-hoc deployment
Structured WSN
 Pre-planned deployment

6. Related work
 Grade Diffusion algorithm
 Directed Diffusion algorithm

7. Grade Diffusion algorithm
 The source node will broadcast the RREQ packets to
all its neighbors
 The neighbors will broadcast to its neighbors
 The process repeats until the RREQ packet is received
by the destination node.

8. Disadvantages of Grade Diffusion
Algorithm
 Huge transmission of data will consume lot of power.
 Decrease the battery life.

9. Directed Diffusion algorithm
 Overcomes the disadvantages of Grade Diffusion
algorithm.
 Broadcasting the neighbors to only first neighbor set.
 After that nodes are picked up based on hop count.
 The amount of RREQ exchange is reduced.
 Amount of power required is less as compared to Grade
Diffusion.

10. Problem Statement
 In Grade Diffusion Algorithm it creates Multiple
Routing path.
 Consume lot Power and Energy
 Decrease the Battery life
Reasons for fault Node
 Due to low battery power
 Software failure
 Hardware failure

11. Fig1: Wireless sensor node routing.
Fig 2: Wireless sensor node routing path when some
nodes are not functioning.

12. PROPOSED APPROACH
FAULT NODE RECOVERY ALGORITHM
 FNR is based on the Grade Diffusion Algorithm.
 Recharges the sensor nodes which are not functioning.
 Increase the life time of the wireless sensor network.

13.  The process of finding the set of nodes whose
battery power is less than threshold is called
Fault Node Determination.
 The proposed algorithm finds the dead node
and recharge with new battery power.
 Find the Single shortest path.

14. SYSTEM DESIGN
Node
Placement
Algorithm
Routing Table
Formation
Route
Determination
Fault Node
Prediction
Fault Node
Recovery
Analysis as
compared to
Grade
Diffusion

15. Data Flow Diagram – Routing Formation
Algorithm
Node id and
positions of nodes
Create a routing
table for a node
Compute distance
between nodes to
other nodes
Create a map of node
id and distance
Store the map
( node id,
distance)
Node Information

16. Data Flow Diagram – Fault Node
Detection
Battery Threshold,
Rechargeable Battery
Neighbor
Discovery
Compare
Threshold
Battery
Add it to the
Dead Node List
List of Dead Nodes
Neighbor Discovery

17. Detail Design
Grade Diffusion Algorithm

18. Pseudo Code
Like this routing tables are generated for 20 nodes.
Finding the Route from the source to Destination
Source Node=2
Destination Node=8
Coverage Area=20
Grade Diffusion

19. Route Discovery for Route1 using Grade
Diffusion
 Step1:
 The source Node 2 will first find the nodes in its routing table
{1,2,3,4,5,6,7,8,9,10.11,12,13,14,15,16,17,18,19,20}
 Step2: Find the nodes in the coverage area which are within 20 m
 {1,3,4}
 Step3: Check whether the destination node is present in the neighbor
l node list
 {8} is present in {1,3,4} or not
 Step4: Find the nodes in the forward direction towards destination
node {3,4}
 Step5: Pick the first node {3}
 Step6: Now the source node will be {3}
 The route1 that is discovered is given as {2->3->5->6->8}

20. Route Discovery for Route2 using Grade
Diffusion Step1:
 The source Node 2 will first find the nodes in its routing table
{1,2,3,4,5,6,7,8,9,10.11,12,13,14,15,16,17,18,19,20}
 Step2: Find the nodes in the coverage area which are within 20 m
 {1,3,4}
 Step3: Check whether the destination node is present in the neighbor
node list
 {8} is present in {1,3,4} or not
 Step4: Find the nodes in the forward direction towards destination node
{3,4}
 Step5: Pick the second node {4}
 Step6: Now the source node will be {4}
 Step7: The route discovered until now will be {2->4}
 Step8: The source node 4 will fetch nodes in its routing table
………
 The route2 that is discovered is given as {2->4->6->8}

21. Fault Node Route Discovery

22. Min - Hop Routing

23. Snap Shots

27. Conclusion
 The FNR algorithm recharge fewer sensor nodes.
 Reuses the most routing paths.
 Increasing the WSN lifetime
 Reducing the replacement cost.

28. Future Enhancement
The FNR algorithm requires replace fewer
sensor nodes.
Reuses the most routing paths.
Increasing the WSN lifetime

29. REFERENCES
 [1] J. A. Carballido, I. Ponzoni, and N. B. Brignole,
“CGD-GA: A graphbased genetic algorithm for sensor
network design,” Inf. Sci., vol. 177,no. 22, pp. 5091–
5102, 2007.
 [2] F. C. Chang and H. C. Huang, “A refactoring
method for cache-efficient swarm intelligence
algorithms,” Inf. Sci., vol. 192, no. 1, pp. 39–49,Jun.
2012.

30. Thanks …