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ZONE ROUTING PROTOCOL IN MOBILE AD HOC NETWORK
USING ESTIMATION OF DISTRIBUTION ALGORITHM
Presented By
Mst. Farhana Rahman
050203
Iqbal Hossain Shuvo
050214
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
+
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 Protocol
Based 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
[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.
[5] C S R Marthy , B S Manoj, ”Ad Hoc Wireless Networks Architecture & Protocols, ISBN 81-297-0945-7, Pearson
Education Pte. Ltd, Singapore”
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
Literature survey (cont….)
 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
i
il
se
ll xpDpp
1
1 )()|()( xx
with
N
DxX
xp
N
j
se
liij
il
∑ = −=
= 1 1)|(
)(
δ
1)|( 1 == −
se
liij DxXδ
Literature survey (cont….)
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.
[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.
[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.
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
Proposed Method (cont….)
 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.
Proposed Method (cont….)
 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
[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.
[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”.
[6] M Frank, M Gerome, P Don, S Steve, ”The Performance of Ad hoc Networking Protocols in
Highly Mobile Environments”, Spring 2000, Washington.
Thanks To All.

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Presentation2 2000

  • 1. ZONE ROUTING PROTOCOL IN MOBILE AD HOC NETWORK USING ESTIMATION OF DISTRIBUTION ALGORITHM Presented By Mst. Farhana Rahman 050203 Iqbal Hossain Shuvo 050214
  • 2. Presentation Overview  Introduction  Motivation  Objectives  Literature survey  Existing System  Drawbacks of Existing System  Proposed Method  Conclusion
  • 3. 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 +
  • 4. 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.
  • 5. 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.
  • 6. Literature survey  Zone Routing Protocol Based 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 [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. [5] C S R Marthy , B S Manoj, ”Ad Hoc Wireless Networks Architecture & Protocols, ISBN 81-297-0945-7, Pearson Education Pte. Ltd, Singapore”
  • 7. 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
  • 8. Literature survey (cont….)  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 i il se ll xpDpp 1 1 )()|()( xx with N DxX xp N j se liij il ∑ = −= = 1 1)|( )( δ 1)|( 1 == − se liij DxXδ
  • 9. Literature survey (cont….) Figure 3: Flow chart of EDA
  • 10. 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)
  • 11. 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. [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. [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.
  • 12. 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.
  • 13. Proposed Method (cont….)  Research Approach Encoding of Chromosome Crossover and Mutation &Probabilistic Model Initial Population Fitness Function Selection Comparison parameters
  • 14. Proposed Method (cont….)  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.
  • 15. Proposed Method (cont….)  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.
  • 16. 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.
  • 17. Reference [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. [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”. [6] M Frank, M Gerome, P Don, S Steve, ”The Performance of Ad hoc Networking Protocols in Highly Mobile Environments”, Spring 2000, Washington.