A Multicast Genetic Routing Protocol Neural Network Approach
P. Arora. International Journal on Recent and Innovation Trends in Computing and Communication, 3 (3):
1145--1148(März 2015)
DOI: 10.17762/ijritcc2321-8169.150356
Zusammenfassung
Multicast Zone Routing Protocol (GMZRP) is the most promising and widely accepted and well proved hybrid routing protocol in Mobile Ad-hoc Networks (MANETs) for its excellent results when compared in order to load balance the network. with table-driven demand protocols. Improvement of DPMRP is considered using GA and NN approach is considered in this paper. These enhanced protocols are compared with DPMRP and also with each other for same metrics. From the results it is concluded that MGRP (DPMRP), enhanced using GA approach, provides best results. This study is aimed to provide a set of available paths to the destination using the concept of genetic algorithm This gives us the reduction in the overhead, less jitter and better delivery of packets. We call this new routing protocol as Genetic Routing Protocol (GMZRP). Finally, the implementation of proposed genetic GMZRP is compared with Genetic GMZRP, i.e., GMZRP and the result demonstrates better performance from the proposed protocol. Since the method provides a set of paths from nodes to the destination, it results in load balance to the network.
%0 Journal Article
%1 Arora_2015
%A Arora, Preeti
%D 2015
%I Auricle Technologies, Pvt., Ltd.
%J International Journal on Recent and Innovation Trends in Computing and Communication
%K Ad Algorithm GMZRP Genetic Hybrid MANET Network On-Demand Protocol Table-Driven ZRP hoc
%N 3
%P 1145--1148
%R 10.17762/ijritcc2321-8169.150356
%T A Multicast Genetic Routing Protocol Neural Network Approach
%U http://dx.doi.org/10.17762/ijritcc2321-8169.150356
%V 3
%X Multicast Zone Routing Protocol (GMZRP) is the most promising and widely accepted and well proved hybrid routing protocol in Mobile Ad-hoc Networks (MANETs) for its excellent results when compared in order to load balance the network. with table-driven demand protocols. Improvement of DPMRP is considered using GA and NN approach is considered in this paper. These enhanced protocols are compared with DPMRP and also with each other for same metrics. From the results it is concluded that MGRP (DPMRP), enhanced using GA approach, provides best results. This study is aimed to provide a set of available paths to the destination using the concept of genetic algorithm This gives us the reduction in the overhead, less jitter and better delivery of packets. We call this new routing protocol as Genetic Routing Protocol (GMZRP). Finally, the implementation of proposed genetic GMZRP is compared with Genetic GMZRP, i.e., GMZRP and the result demonstrates better performance from the proposed protocol. Since the method provides a set of paths from nodes to the destination, it results in load balance to the network.
@article{Arora_2015,
abstract = {Multicast Zone Routing Protocol (GMZRP) is the most promising and widely accepted and well proved hybrid routing protocol in Mobile Ad-hoc Networks (MANETs) for its excellent results when compared in order to load balance the network. with table-driven demand protocols. Improvement of DPMRP is considered using GA and NN approach is considered in this paper. These enhanced protocols are compared with DPMRP and also with each other for same metrics. From the results it is concluded that MGRP (DPMRP), enhanced using GA approach, provides best results. This study is aimed to provide a set of available paths to the destination using the concept of genetic algorithm This gives us the reduction in the overhead, less jitter and better delivery of packets. We call this new routing protocol as Genetic Routing Protocol (GMZRP). Finally, the implementation of proposed genetic GMZRP is compared with Genetic GMZRP, i.e., GMZRP and the result demonstrates better performance from the proposed protocol. Since the method provides a set of paths from nodes to the destination, it results in load balance to the network.},
added-at = {2015-08-06T09:21:11.000+0200},
author = {Arora, Preeti},
biburl = {https://www.bibsonomy.org/bibtex/21f0cd0861de9522eaed2389df8b6f149/ijritcc},
doi = {10.17762/ijritcc2321-8169.150356},
interhash = {f6ec80ff857f372154641f0e3c9323c3},
intrahash = {1f0cd0861de9522eaed2389df8b6f149},
journal = {International Journal on Recent and Innovation Trends in Computing and Communication},
keywords = {Ad Algorithm GMZRP Genetic Hybrid MANET Network On-Demand Protocol Table-Driven ZRP hoc},
month = {march},
number = 3,
pages = {1145--1148},
publisher = {Auricle Technologies, Pvt., Ltd.},
timestamp = {2015-08-06T09:21:11.000+0200},
title = {A Multicast Genetic Routing Protocol Neural Network Approach},
url = {http://dx.doi.org/10.17762/ijritcc2321-8169.150356},
volume = 3,
year = 2015
}