A NEAR-OPTIMAL MULTICAST SCHEME FOR MOBILE ADHOC NETWORK USING GENETIC ALGORITHM

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ABSTRACT
Multicast routing is an effective way to communicate among multiple hosts in a network. It outperforms the basic broadcast strategy by sharing resources along general links, while sending information to a set of predefined multiple destinations concurrently. However, it is vulnerable to component failure in ad hoc network due to the lack of redundancy, multiple paths and multicast tree structure. Tree graph optimization problems (GOP) are usually difficult and time consuming NP-hard or NP-complete problems. Genetic algorithms (GA) have been proven to be an efficient technique for solving the GOP, in which well-designed chromosomes and appropriate operators are key factors that determine the performance of the GAs. Limited link, path constraints, and mobility of network hosts make the multicast routing protocol design particularly challenging in wireless ad hoc networks. Encoding trees is a critical scheme in GAs for solving these problems because each code should represent a tree. Prufer number is the most representative method of vertex encoding, which is a string of n-2 integers and can be transformed to an n-node tree. However, genetic algorithm based on Prufer encoding (GAP) does not preserve locality, while changing one element of its vector causes dramatically change in its corresponding tree topology.


TABLE OF CONTENT
TITLE PAGE                                   
CERTIFICATION                               
APPROVAL                               
DEDICATION                                   
ACKNOWLEDGEMENT                       
ABSTRACT                                   
TABLE OF CONTENT                               

CHAPTER ONE
1.0    INTRODUCTION                           
1.1    STATEMENT OF PROBLEM                       
1.2    PURPOSE OF STUDY                           
1.3    AIMS AND OBJECTIVES                        
1.4    SCOPE/DELIMITATIONS                       
1.5    LIMITATIONS/CONSTRAINTS                       
1.6    DEFINITION OF TERMS                       

CHAPTER TWO
2.0    LITERATURE REVIEW                           

CHAPTER THREE
3.0    METHODS FOR FACT FINDING AND DETAILED DISCUSSIONS OF THE SYSTEM
3.1     METHODOLOGIES FOR FACT-FINDING
3.2    DISCUSSIONS            

CHAPTER FOUR
4.0    FUTURES, IMPLICATIONS AND CHALLENGES OF THE SYSTEM
4.1    FUTURES
4.2    IMPLICATIONS
4.3    CHALLENGES

CHAPTER FIVE
5.0    RECOMMENDATIONS, SUMMARY AND CONCLUSION       
5.1    RECOMMENDATION                           
5.2    SUMMARY                               
5.3    CONCLUSION                               
5.4    REFERENCES                       

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APA

17, 2017) .A NEAR-OPTIMAL MULTICAST SCHEME FOR MOBILE ADHOC NETWORK USING GENETIC ALGORITHM. http://dubz-by-dan.co.uk. Retrieved 17, 2017, from http://dubz-by-dan.co.uk/works/a-near-optimal-multicast-scheme-for-mobile-adhoc-network-using-genetic-algorithm-3173/read

MLA

"A NEAR-OPTIMAL MULTICAST SCHEME FOR MOBILE ADHOC NETWORK USING GENETIC ALGORITHM"

MLA7

"A NEAR-OPTIMAL MULTICAST SCHEME FOR MOBILE ADHOC NETWORK USING GENETIC ALGORITHM" http://dubz-by-dan.co.uk, 17, 2017. Web. 17, 2017. from http://dubz-by-dan.co.uk/works/a-near-optimal-multicast-scheme-for-mobile-adhoc-network-using-genetic-algorithm-3173/read.

Chicago

"A NEAR-OPTIMAL MULTICAST SCHEME FOR MOBILE ADHOC NETWORK USING GENETIC ALGORITHM" http://dubz-by-dan.co.uk. 17, 2017. Accessed 17, 2017. from http://dubz-by-dan.co.uk/works/a-near-optimal-multicast-scheme-for-mobile-adhoc-network-using-genetic-algorithm-3173/read