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By Naeem Amjad DREEM-ME: Distributed Regional Energy Efficient Multi-hop Routing Protocol based on Maximum Energy in WSNs 1

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DREEM-ME: Distributed Regional Energy Efficient Multi-hop Routing Protocol based on Maximum Energy in WSNs. By Naeem Amjad. Challenges Introduction Motivation First Order Radio Model Proposed Scheme Simulations And Results Conclusion. Outline. Energy efficiency - PowerPoint PPT Presentation

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Page 1: By  Naeem Amjad

By Naeem Amjad

DREEM-ME: Distributed Regional Energy Efficient Multi-hop Routing Protocol based on MaximumEnergy in WSNs

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Page 2: By  Naeem Amjad

Challenges IntroductionMotivation First Order Radio ModelProposed Scheme Simulations And ResultsConclusion

Outline

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Energy efficiencyMaximum Network LifetimeCoverage Ability Increased Throughput Low delayEfficient routingCluster Head selection technique

Challenges

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Wireless Sensor Network is a collection of small randomly dispersed devices that provide the ability to monitor physical and environmental conditions in real time.

WSNs are independent when deployed into the field because they have the ability of self-configuration and survival.

Introduction

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There are two types of Clustering:Clusters once constructed and never be changed

throughout network lifetime, are called Static Clusters. Clusters based on some sort of network characteristics

and are changing during network operation are known as Dynamic Clusters.

DREEM-ME is based upon static clustering.

Introduction

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All the nodes are homogeneous All nodes are proactive (continuously

monitoring data). Base station is in the center of the network.Maximum energy based cluster head selection

is used.

Introduction

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Clustering technique of LEACH does not assure a fix number of CHs in each round.

In LEACH protocol, the number of CHs selected are not optimum.

We select the nodes as CHs which carry maximum energy in a particular region. So, this technique assures the optimum number of cluster heads in every round.

Motivation

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For efficient use of energy and improvement of coverage, DREEM-ME divides the total area into small sub-regions

These sub-regions are treated separately for the nodes distribution.

Motivation

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Here, k= length of message in bitsd= distance of transmissionEelec= Energy to run the transmitter or receiver’s circuitryEamp= Energy to amplify the signal

First Order Radio Model

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The target is to maximize the network coverage.There exists a trade off between coverage and the

energy. So we have localized the whole network and divided the

network into sub-regions that helps in avoiding the coverage hole.

Proposed Scheme : DREEM-ME

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In DREEMME, the CH selection is entirely based upon the maximum energy.

In a particular region, the node with maximum energy is selected as the CH for that region in the current round.

CH Selection

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Total Nodes = 90Nodes in each Region = 10

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All non-CH nodes of outer regions (6, 7, 8, 9) check their distances from CHs of six regions which are close to them.

For example, each node of Region 6 checks its distance from CHs of its nearby regions (2, 3, 5, 6, 7, 9) and then finds the minimum of these six distances.

So every non-CH node of outer regions sends its data to the CH which is at minimum distance.

Association Of Nodes

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In DREEMME, all nodes of Region 1 are using Direct communication because they are at smaller distance to the BS as compared to the nodes of other regions.

All the other regions are considered as static clusters.

Routing

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Multi-hop technique is used for CH-CH communication. CH of region 9 CH of region 5 BS CH of region 8 CH of region 4 BSCH of region 7 CH of region 3 BSCH of region 6 CH of region 2 BS

Means sending the data

Routing

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We take a 100m x 100m area for our network Total nodes are 90. We divided the area into three concentric circles with

20m, 35m and 50m radii. Simulations are done in MATLAB.Packet Drop Model is also implemented.Average of 5 simulations is plotted in the results.

SIMULATIONS AND RESULTS

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Simulation Parameters

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The results fluctuate to-and-fro around a mean value in every simulation.

Confidence interval is the interval in which we are pretty confident about our results.

We have observed the range of variance of our desired results and then defined their upper and lower values and the mean.

Confidence Interval

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Nodes of regions of outermost circle die first

because area of each outer region is greater than middle or inner circle..

Then nodes of regions of middle circle start to die.And the Direct Communication nodes die in the

last because they are much closer to the BS.

Dead Nodes

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According to our network strategy packets sent to the BS per round should ideally follow the explanation below:

Packets sent to BS by 1st Region DT nodes 10 Packets Sent to BS by 2nd Region CH Node 1 Packets Sent to BS by 3rd Region CH Node 1 Packets Sent to BS by 4th Region CH Node 1 Packets Sent to BS by 5th Region CH Node 1 Total Packets Sent to BS per round 14 As long as all the nodes are alive the packets sent

remain 14.

Packets Sent To BS

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In DREEM-ME, Packet Drop concept is used which makes it more close to the reality situation.

In reality the wireless links are not perfect or ideal.There is always a probability that some of packets

may be dropped on their way.

Packet Drop Technique

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We calculated the dropped packets with the probability of dropping as 0.3 out of 1.

But it is also practically possible that the probability of packet loss is less than 0.3.

Packets received are not the same as the packets sent in each round because of the packet drop technique.

Packets Dropped

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In this paper, we have proposed a new clustering technique for WSNs.

DREEM-ME uses static clustering and maximum energy based CH selection.

Multi-hop route is used for the CHs at long distance to sink. The network field is divided evenly into circles and sectors to

reduce the distance between CHs and BS. In MATLAB simulations we compared our results with LEACH and

LEACH-C. CH selection technique of DREEM-ME provides better results

than its counterparts, in terms of network lifetime, stability period, area coverage and throughput.

Conclusion

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