The slide to improved version of the data which is collected through polling point much fast.

1. An Efficient Cluster Tree Based Data Collection
Scheme for Large Mobile With Polling Point in WSN
PROJECT GUIDE PROJECT SCHOLAR
M. MUTHU RAMALINGAM M.E KAVITHA S
ASSISTANT PROFESSOR (ECE) KAVIPRIYA P
B.E (ECE) – FINAL YEAR

2. OBJECTIVE
 To reduce the work load of cluster head
 To increase the throughput and reduce the energy
consumption

3. ABSTRACT
 The Polling Point in which the DGN is placed and polling
point is common to particular region.
 The designed scheme minimizes the energy exploitation,
reduces the end-to-end delay and traffic in cluster head in
WSNs by effective usage of the DCT.
 Mainly focus on the problem of minimizing the length of
each data-gathering and refer to this as the single-hop data-
gathering problem (SHDGP).

4. EXISTING WORK
 To collect the data from cluster head to sink used to the data
gathering node.
 Here the data gathering node was connected along the
VELCT (Velocity Efficient Link Aware Cluster Tree) scheme.

5. PROPOSED WORK
 We proposed a novel logical topology for data collection
named Spanning Tree Covering Algorithm in which we create
the polling point for data gathering

6. WORK MODULE
 Node Initialization
 Define Data Gathering Node
 Spanning Tree Algorithm
 Define Polling Point
 Data collection
 Send to destination

7. BLOCK DIARAM
Node
initialization
DG Node
selection
Spanning Tree
covering
algorithm
PP
Node
deploy
ment
Data to
PP node
Data to DG
node
Data
to
sink

8. DISCRIPTION
NODE INITIALIZATION
 Organize the sensor nodes into
cluster.
 Each cluster member is
governed by a cluster head.
 Suitable for data fusion.
 Self organizing.

9. POLLING POINT
 Polling Point in the sense of creating center point amongst
cluster head.
SPANNING TREE
 Spanning tree creates the loops to all clustering nodes.
 Find the nearest node.
 It will create as a data set of all information.
 Depends upon the data set the polling point will be create.

10. SPANNING TREE ALGORITHM
Step 0: Pick any vertex as a starting vertex (call it A). Mark it
with any given color, say orange.
Step 1: Find the nearest neighbor of A (call it B). Mark both
vertex and the edge AB orange

11. SPANNING TREE ALGORITHM
Step 2: Find the nearest uncolored neighbor to the orange sub graph.
Mark it and the edge connecting the vertex to the red sub graph in
orange.
Step 3: Repeat the above step until all vertices are marked orange. The
orange sub graph is a minimum spanning tree.

12. SPANNING TREE COVERING
ALGORITHM

13. POLLING POINT INITIALIZATION
 The spanning covering
algorithm initialized current
empty node as a polling point.
 Union current node containing
all sensor nodes and create the
candidate polling points.
 All sensor nodes are covered
by corresponding polling
points in the region.
 Add the corresponding polling
points cover sensor nodes into
current empty polling point.
 Find an approximate shortest
tour on polling point.

14. SIMULATION RESULT
 Polling Point node deployment

15. SIMULATION RESULT
 Sensor nodes ready to access the polling point

16. SIMULATION RESULT
 PP node collects data from sensor nodes

17. SIMULATION RESULT
 DG node collects data from PP nodes

18. SIMULATION RESULT
 DG node sends data to sink

19. PERFORMANCE EVALUATION
ENERGY GRAPH
 The graph between time
and working efficiency in
joule.
 To compare the existing
methods the energy
consumption is increases.

20. PERFORMANCE EVALUATION
THRESHOLD GRAPH
 The threshold graph is
drawn between time and
no. of packets transfer to
the sink.
 The threshold of these
method is increases the
ratio of PDR.

21. PERFORMANCE EVALUATION
DELAY GRAPH
 The delay graph is drawn
between time and delay of
packets.
 The packet delay ratio is
reduces the proposed
method.

22. ADVANTAGES
 By introducing the polling point data gathering becomes
more flexible and adaptable to the unexpected changes
of the network topology.
 Data gathering is perfectly suitable for applications,
where sensors are only partially connected.
 Reduces the number of data gathering node in VELCT.
 Less transmission delay.
 Energy efficient.

23. APPLICATIONS
FIRE BUG
 Wildfire Instrumentation System
Using Networked Sensors.
 Allows predictive analysis of
evolving fire behavior
 Firebugs: GPS-enabled, wireless
thermal sensor motes based on
TinyOS that self-organize into
networks for collecting real time
data in wild fire environments.

24. APPLICATIONS
 Preventive maintenance on an oil
tanker.
 Use of sensor networks to
support preventive maintenance
on board an oil tanker in the
North Sea.
 A sensor network deployment
onboard the ship .
 System gathered data reliably and
recovered from errors when they
occurred.

25. CONCLUSION
 In this paper spanning tree covering algorithm a proficient
method to construct a mobility based auspicious network
management architecture for WSNs
 In this method each cluster member choose the CH with
better connection time and forward the data packets to the
corresponding CH in an allocated time slot.

26. REFERENCES
 E.Callaway,(2001) Cluster Tree Network- IEEE ,P802.15 Wireless
personal Area Networks (WPANs)
 J.Yang, B.Bai and H.Li, “An Energy Efficient Data Gathering
Algorithm for Wireless Sensor Networks”, in proc. Int. conf.
Autom. Controll Artif.Intell. (ACAI), Xiamen china, Mar.2012
 R.Velmani and B.Kaarthick “An Energy Efficient Data Gathering in
Dense Mobile Wireless Sensor Networks”, ISRN sensor
networks.April 2014, Art.ID 51868
 R.Velmani and B.Kaarthick, “An Efficient Cluster Tree Based Data
Collection Scheme for Large Mobile Wireless Sensor Networks,
IEEE sensor journal Vol.15, No.4, April (2015)
 Arezoo Abasi and Hedieh Sajedi, “Fuzzy- Clustering Based Data
Gathering in Wireless Sensor Networks, International journal on
soft computing (IJSC) Vol.7, No.1, Feb (2016)