Presentation2 2000

ZONE ROUTING PROTOCOL IN MOBILE AD HOC NETWORK USING ESTIMATION OF DISTRIBUTION ALGORITHM

Presented By

Mst. Farhana Rahman050203Iqbal Hossain Shuvo050214

Presentation Overview

Introduction Motivation Objectives Literature survey Existing System Drawbacks of Existing System Proposed Method Conclusion

Introduction

Mobile Ad hoc Network (MANET)

An ad hoc network is a collection of mobile nodes that dynamically form

a temporary network.

Zone routing protocol

Zone Routing Protocol or ZRP was the first hybrid routing protocol with

both a proactive and a reactive routing component[1].

Estimation of distribution Algorithm

Estimation of Distribution Algorithms (EDA) , sometimes called Probabilistic Model-Building Genetic Algorithms (PMBGA), are an outgrowth of genetic algorithms[3].

[1] H J Haas, “A new routing protocol for the reconfigurable wireless networks”, in proceeding. of IEEE 6th International Conference on Universal Personal Communications 97, 1997.

[3] M Pelikan , D Goldberg, F Lobo,” A Survey of Optimization by Building and Using Probabilistic Models”, Illinois: Illinois Genetic Algorithms Laboratory (IlliGAL), University of Illinois at Urbana-Champaign

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Motivation

The unwanted delay and lack of reliability of existing network[6]. Cost & complexity of linear search for large number of nodes[5]. The unnecessary wastage of network resources and of time[5]. Find multiple shortest or near shortest paths instead of rediscovering the path

to the destination every time on failure of the existing path. In case where there is no feasible solution EDA converges faster. The benefit of random search over linear search.

[5] C S R Marthy , B S Manoj, ”Ad Hoc Wireless Networks Architecture & Protocols, ISBN 81-297-0945-7, Pearson Education Pte. Ltd, Singapore”

[6] M Frank, M Gerome, P Don, S Steve, ”The Performance of Ad hoc Networking Protocols in Highly Mobile Environments”, Spring 2000, Washington.

Objectives

To implement the traditional Zone Routing Protocol. To implement and compare the Genetic Zone Routing Protocol with the

traditional Zone Routing Protocol. To survey the scope of using Estimation of Distribution Algorithms as an

alternative of Genetic algorithm. To compare and analyze the performance of EDA and GA in ZRP. To find the reasonable solution that stands for the comparison result of GA and

EDA.

Literature survey

Zone Routing ProtocolBased on the concept of zones. First introduced by Haas in 1997 [1].Routing zone is defined for each node separately.Proactive routing protocol Intra-zone Routing Protocol (IARP)

used inside routing zones. Reactive routing protocol Inter-zone Routing Protocol (IERP )

used between routing zones[5].

Figure 1: The routing zone of node S



Literature survey (cont….)

Genetic Algorithm (GA)

GA is a type of searching algorithm[2][4].

Creates a "population" of possible solutions.

Two individuals are selected at random .

Cross-over the two individuals to produce two new individuals .

Each individual have a random chance to mutate .

Select individual with highest fitness as the solution to the problem.

Figure 2: Example of crossover

[2] J M Kin, T H Cho, “Genetic Algorithm Based Routing Method for Efficient Data Transmission in Sensor Networks”, in proceeding of ICIC 2007.

[4] P S Kumar, S Ramachandram , C R Rao, “Effect of Transmission Range on the Performance of Zone Routing Protocol in MANETs”, In Proceedings of ICACC, 2007.

Chromosome 1 10010 | 00100110110

Chromosome 2 11011 | 11000011110

Offspring 1 10010 | 11000011110

Offspring 2 11011 | 00100110110


Estimation of Distribution Algorithm (EDA)Interrelations are expressed through the joint probability distribution

Neither crossover nor mutation has been applied in EDA.

In UMDA , There is no interrelation among the variables of the problems[3].

n-dimensional joint probability distribution of n univariate and independent variable is:

Each univariate marginal distribution is estimated from marginal frequencies:

If in the jth case of , Xi=xi

[3] M Pelikan , D Goldberg, F Lobo,” A Survey of Optimization by Building and Using Probabilistic Models”, Illinois: Illinois

Genetic Algorithms Laboratory (IlliGAL), University of Illinois at Urbana-Champaign

n

iil

sell xpDpp

11 )()|()( xx

withN

DxXxp

N

j

seliij

il

1 1)|(

)(

1)|( 1 seliij DxX


Figure 3: Flow chart of EDA

Existing System

Proactive or table-driven protocols- -Open Shortest Path First (OSPF) protocol

-Distance-Vector routing (DSDV) protocol

Reactive or on-demand protocols -On-demand Distance Vector (AODV) protocol

-Dynamic Source Routing (DSR) protocol

The Zone Routing Protocol (ZRP) -Intra-zone Routing Protocol (IARP)

-Inter-zone Routing Protocol (IERP)

-Border cast Resolution Protocol (BRP)

Drawbacks of Existing System

Drawbacks of Ad hoc network Unwanted delay and lack of reliability[6]. For large number of nodes linear search will become costly.

Drawbacks of proactive routing protocol High requirement on the resource. Cannot easily adapt for dynamic updates[5]. They cannot scale to large network.

Drawbacks of reactive routing protocol Sometimes causes unnecessary wastage of network resources and also wastage of time[5]. A node has to wait until a route is discovered and a route discovery is expensive .

Drawbacks of zone routing protocol Decision on the zone radius has significant impact on the performance [1]. linear searching on the nodes is time consuming and searching complexity arises as number of node

involves increases.




Proposed Method

There are various types of EDA both in discrete and continuous domain. We will consider the discrete domain in our case.

- For GA one-point crossover and mutation,

- For EDA, it will be the probability model.

Proposed Method (cont….)

Research Approach

Encoding of Chromosome

Crossover and Mutation &Probabilistic Model

Initial Population

Fitness Function

Selection

Comparison parameters


Research Focus

Find a good encoding strategy that will represent the chromosome as the contents of source to destination routing.

To solve the increasing complexity of time, delay and congestion for large number of nodes in ZRP.

To solve the source to destination routing where the destination is outside the zone.

To compare the performance of EDA and GA and traditional ZRP for large number of nodes.


Our proposed method can be summarized as follows:

To find a good encoding strategy that will represent the ad hoc network.

To randomly generate the initial population.

To calculate the fitness value for each chromosome. Use the same fitness function for both GA and EDA.

To perform crossover and mutation for GA to generate new population.

To perform Probabilistic model for EDA to generate new population.

Select the subpopulation with elitism and without elitism.

Continue until the result converges.

Conclusion

We did not calculate the cost analysis and computation difficulties so far. These things are to be solved before implementation. We need to find a good selection mechanism that will cope with ad hoc network. With the help of our supervisor, we will be able to solve the problems of the research area.

Reference


[2] J M Kin, T H Cho, “Genetic Algorithm Based Routing Method for Efficient Data Transmission in Sensor Networks”, in proceeding of ICIC 2007.

[3] M Pelikan , D Goldberg, F Lobo,” A Survey of Optimization by Building and Using Probabilistic Models”, Illinois: Illinois Genetic Algorithms Laboratory (IlliGAL), University of Illinois at Urbana-Champaign

[4] P S Kumar, S Ramachandram , C R Rao, “Effect of Transmission Range on the Performance of Zone Routing Protocol in MANETs”, In Proceedings of ICACC, 2007.

[5] C S R Marthy , B S Manoj, ”Ad Hoc Wireless Networks Architecture & Protocols, ISBN 81-297-0945-7, Pearson Education Pte. Ltd, Singapore”.


Thanks To All.

Technology

Presentation2 2000