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Performance Evaluation of Performance Evaluation of LEACH Routing Algorithm in LEACH Routing Algorithm in

Wireless Mobile Sensor Wireless Mobile Sensor NetworksNetworks

Arash Tavakkol,Arash Tavakkol,

Advanced Network Course ProjectAdvanced Network Course Project

Computer Engineering Department,Computer Engineering Department,

Sharif University of Technology,Sharif University of Technology,

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• Introduction Introduction

• A Quick Safari Through Wireless Sensor Networks (WSNs)A Quick Safari Through Wireless Sensor Networks (WSNs)

• The Important Role of Mobility in WSNsThe Important Role of Mobility in WSNs

• Xmulator Xmulator ( Novel Object Oriented Based Framework for Modeling WSNs)( Novel Object Oriented Based Framework for Modeling WSNs)

• Simulation Preparation and ResultsSimulation Preparation and Results

• Proposed Solution (New Versions of LEACH Routing Algorithm)Proposed Solution (New Versions of LEACH Routing Algorithm)

• Future Works and ConclusionsFuture Works and Conclusions

Outline

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Introduction

• Recent advances in technology enable us to use small sensor nodes for environment monitoring.

• Example : Smart Building, Smart Hospitals, Disastrous Environment Monitoring, Factory Monitoring, Battle Fields.

• The available techniques for current networks do not support this kind of networks.

• Designing protocol stack for this kind of new network is a challanging problem for engineers and researchers.

• We can use some of the Ad Hoc Network techniques for the design of sensor networks but they differ from each other according to the following facts

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• Difference to Ad Hoc Networks:• Number and density of sensor nodes.

• Sensor nodes are prone to failure.

• Topology of the network is changing rapidly (because of mobility, lose of power and …).

• Limit in power of sensor nodes.

• Sensor nodes usually don’t have global ID.

So we must search for new techniques of the So we must search for new techniques of the design.design.

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A Quick Safari Through A Quick Safari Through Wireless Sensor Network Wireless Sensor Network

System (WSN)System (WSN)

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Wireless Sensor Network ArchitectureWireless Sensor Network Architecture

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Designing Factor and Metrics

1.1. Fault Tolerant Fault Tolerant : The failure of sensor nodes must not affect heavily the network functionality.

2.2. Scalability Scalability : We can easily change the size of network.

3.3. Low Power Low Power : We must extend the life time of the system.

4.4. Mobility Mobility : Our design must support mobile nodes.

5.5. Task Management Task Management : We must efficiently distribute task among the sensors, so efficient distributed algorithms.

6.6. Product Cost Product Cost : Each sensor must be sufficiently low cost.

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Designing sensor network protocol stack according to some of it

performance metrics.

•In each layer of sensor network we face optimization problem according to the described metrics.

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Network Layer

• Usually the power spent for information transmition is higher than computational power (Pcomp << PTran).

• The model for path loss are Free-Space and Multipath Fading.

• The key point in wireless sensor networks is MultihopMultihop routing.

baba )( 42

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Classification of Routing Algorithms for WSNs

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Low Energy Adaptive Clustering Hierarchy (LEACH)

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Low Energy Adaptive Clustering Hierarchy (LEACH)

• In this approach WSN is divided into clusters.

• Each cluster collects and compresses the data form cluster members and sends to base station.

• Each cluster member sends its data to clusterhead periodically according to TDMA table.

• After specific time, the configuration of the WSN will be changed and new cluster head will be selected.

• LEACH algorithm has the following 3 phases:

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Cluster Head Selection Phase:• The aim is to have in average K clusterhead in each round.

• Suppose we are in round=r+1.

• Each node generates uniform random variable R.

• If R<T(n) then the node presents itself as cluster head.

• The threshold is computed as follow:

• In this equation G is the set of nodes that are not selected as clusterhead in recent N/K round.

else 0

Gn )/mod()( KNrKN

K

nT

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LEACH AlgorithmsLEACH Algorithms

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Setup Cluster Phase:• Each cluster head broadcasts ClusterHeadIDClusterHeadID message with its

IDID in network (CSMA).

• Each non cluster head listens to these messages and selects appropriate cluster head with respect to its received signal energy.

• Selecting appropriate cluster head, each node broadcast its ID and ID of cluster head with message JIONTOCHJIONTOCH in network (CSMA).

• After each clusterhead finds its members, it makes TDMA table for data transmission for each member and send to them.

• Each cluster member finds its time and turns off its radio till its turn and sends data.

• After each time slot each clusterhead compresses data and sends it to base station.

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• After certain period of time the clusterhead changes and new nodes become cluster head.

LEACH: At the end of steady phase

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LEACH in one GlanceLEACH in one Glance

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MobilityMobility

• One of the most critical characteristics of WSNs is Mobility.

• Concurrent usage of Wireless Network Wireless Network and Mobile NetworkMobile Network in the literature illustrates the importance of this attribute.

• Mobility affects different layers like MAC and Network and usually leads to complexity in the algorithms:• For example: the more the nodes change their position the

more routing tables become invalid.

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• PhysicalPhysical studies: Investigating nodes displacement from physical point of view and without any consideration to signaling effects.• Abstract modeling of nodes displacement.• Very important for simulation studies

• Middle Performance Models:Middle Performance Models: Analytical modeling of the effect of mobility on the routing protocols and topology control protocols.

• Mobility in Topology Control and Routing Algorithm:Mobility in Topology Control and Routing Algorithm: Investigating the effect of mobility on different layers of WSNs and proposing solutions to prevent performance degradation.

Research Areas About MobilityResearch Areas About Mobility

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• Proposes an AnalyticalAnalytical model for mobility.

• The model should have following properties to be useful:• Having enough simplicity to be implemented in simulation

studies

• Does not have great difference to real values.

• Currently two types of models used in simulations:• Trace based models: In this method realistic mobility patterns

used for simulation

• Analytical models

Physical StudiesPhysical Studies

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Analytical Mobility ModelsAnalytical Mobility Models

• Random Walk Model: Each node changes its current position with choosing two parameters: Velocity and degree of displacement.• The movement continues till a predefined time or distance.

• At the end of movement a new velocity and degree will be selected for new movement.

• This models has no memory which leads to instantaneous stop or great direction changes.

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Analytical Mobility Models (cont’d)Analytical Mobility Models (cont’d)

• Random Way Point: In this model we have Pause Time, which means a node can have certain periods without any movement.• Each nodes waits for a specific period and at the end of this

period selects a destination and moves toward it.

• The displacement speed is chose from a limited interval.

• After arrival this process will be repeated.

• This model has been used in many academic researches and we have used it in our investigation for LEACH.

• It is very simple but the results will be stabled very late. So the simulation time will be too long.

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Analytical Mobility Models (cont’d)Analytical Mobility Models (cont’d)

• Group Mobility Models: Used for modeling the mobility of a group of objects. The most famous models in this category are:• Exponential Correlated Random Mobility Model: A

probabilistic function used for all nodes to give correlation.

• Column Mobility Model: Used for displacements like a column of soldiers. Te members of the column move in a same direction with same speed.

• Nomadic Community Mobility Model

• Reference Point Group Mobility Model

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Other Physical Models

• Random direction model: Provided uniform distribution of nodes.

• Boundless simulation area: solving the problem of instantaneous change in speed and direction.

• Gauss-Markov model

• City Section Mobility Model

• Manhattan Mobility Model

• Highway Mobility Model

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Xmulator Xmulator ( Novel Object Oriented Based ( Novel Object Oriented Based Framework for Modeling WSNs)Framework for Modeling WSNs)

Motivation for Developing a Modeling Platform for WSNs:• Possibility of defining details of algorithms with

performance considerations.• There is a lack of good simulators( J-Sim, NS, OpNetJ-Sim, NS, OpNet).

• Using new software architecture paradigms (OOD).

• Using OO programming languages (C# , Java).

Xmulator=XML+Simulator.

• Using XML format for defining topologies, parameters, and outputs.

• Ease of developing new packages, new tools for existing packages.

• Possibility of debugging even into the core of simulator.

• Logging capabilities.

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Principles of Simulation• Time slice Method

• In this method we divide the time to small time slices and run the program (Master Clock)

• Small time slices reduction in performance• Large time slices reduction the accuracy

• Process based Method• In this method each part of the real system is modeled

with a process. • easy of defining the behaviors of the components.• low performance.

• Event based Method• Record the events to simulate the system behavior. • Xmulator using this method in this version.

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Simulation PreparationSimulation Preparation

• We have simulated under two size for networks:• 200 nodes• 500 nodes• 1000 nodes• 2000 nodes

• Maximum Transmission Power: 0.6 * 10-3 Wat.

• Path Loss: 1 / d2

• Listening Threshold: 10-8 Wat.

• Uniform distribution of nodes along each axes.

• Percent of Cluster Nodes: 10% , 20%

• Initial Platform Size: 400 * 400 meter to 1000*1000 meter

• Message Length: 1024 bit

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Simulation Results

(Throughput)

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25

40

55

70

85

100

0 10 20 30 40 50 60 70

Speed (m/sec)

Th

rou

gh

pu

t Node=100, Clusters=10%

Node=500, Clusters=10%

Node=100, Clusters=20%

Node=500, Clusters=20%

Random Way Point Model

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Exponential Correlated Random Mobility Model

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40

55

70

85

100

0 10 20 30 40 50 60 70

Throughput

Sp

eed

(m

/sec

)

Node=100, Clusters=10%

Node=500, Clusters=10%

Node=100, Clusters=20%

Node=500, Clusters=20%

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Simulation Results

(Energy)

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Random Way Point

0

0.5

1

1.5

2

2.5

3

0 10 20 30 40 50 60 70

Speed (m/sec)

To

tal

En

erg

y D

issi

pat

ed i

n

Sys

tem

(Jo

ule

s)

Node=100, Clusters=10%

Node=500, Clusters=10%

Node=100, Clusters=20%

Node=500, Clusters=20%

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Conclusions And Future Works• Mobility is one of the most important properties of Wireless

Sensor Networks and should be considered in design of each layer of network.

• The simulation results depict that LEACH routing algorithm is not mobility tolerant and its performance is highly sensitive to mobility.

• The Exponential Correlated Random Mobility Model has less degradation effect on the performance of LEACH in comparison to Random Way Point Mobility Model.

• The energy dissipation of LEACH grows too much under the random way point mobility model. This is another fact that shows this algorithm is not mobility tolerant.

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• Future Work:• Investigating the effect of other mobility models on LEACH.

• Comparison of LEACH to other routing algorithms from mobility point of view.

• Proposing solutions/revisions for LEACH to make it mobility tolerant.

THE ENDTHE END