An Efficient Cluster Tree Based Data Collection Scheme for Large Mobile With Polling Point in WSNs

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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

Transcript of An Efficient Cluster Tree Based Data Collection Scheme for Large Mobile With Polling Point in WSNs

Page 1: An Efficient Cluster Tree Based Data Collection Scheme for Large Mobile With Polling Point in WSNs

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

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OBJECTIVE

To reduce the work load of cluster head

To increase the throughput and reduce the energy consumption

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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).

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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.

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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

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WORK MODULE

Node Initialization

Define Data Gathering Node

Spanning Tree Algorithm

Define Polling Point

Data collection

Send to destination

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BLOCK DIARAM

Node initialization

DG Node selection

Spanning Tree

covering algorithm

PP Node deployment

Data to PP node

Data to DG nodeDat

a to sink

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DISCRIPTION NODE INITIALIZATION

Organize the sensor nodes into cluster.

Each cluster member is governed by a cluster head.

Suitable for data fusion.

Self organizing.

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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.

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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

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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.

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SPANNING TREE COVERING ALGORITHM

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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.

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SIMULATION RESULT

Polling Point node deployment

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SIMULATION RESULT

Sensor nodes ready to access the polling point

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SIMULATION RESULT

PP node collects data from sensor nodes

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SIMULATION RESULT

DG node collects data from PP nodes

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SIMULATION RESULT

DG node sends data to sink

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PERFORMANCE EVALUATION

ENERGY GRAPH

The graph between time and working efficiency in joule.

To compare the existing methods the energy consumption is increases.

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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.

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PERFORMANCE EVALUATION

DELAY GRAPH

The delay graph is drawn between time and delay of packets.

The packet delay ratio is reduces the proposed method.

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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.

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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.

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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.

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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.

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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)

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THANK YOU