Scheduling of routing table calculation schemes in open shortest path first using artificial neural network

Internet topology changes due to events such as router or link goes up and down. Topology changes trigger routing protocol to undergo convergence process which eventually prepares new shortest routes needed for packet delivery. Real-time applications (e.g. VoIP) are increasingly being deployed in in...

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Main Author:	Abu Yazid, Mohamad Haider
Format:	Thesis
Language:	English
Published:	2013
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/37980/1/MohamadHaiderAbuYazidMFSKSM2013.pdf
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spelling	my-utm-ep.379802018-04-12T05:39:40Z Scheduling of routing table calculation schemes in open shortest path first using artificial neural network 2013-01 Abu Yazid, Mohamad Haider TK Electrical engineering. Electronics Nuclear engineering Internet topology changes due to events such as router or link goes up and down. Topology changes trigger routing protocol to undergo convergence process which eventually prepares new shortest routes needed for packet delivery. Real-time applications (e.g. VoIP) are increasingly being deployed in internet nowadays and require the routing protocols to have quick convergence times in the range of milliseconds. To speed-up its convergence time and better serve real-time applications, a new routing table calculation scheduling schemes for Interior Gateway Routing Protocol called Open Shortest Path First (OSPF) is proposed in this research. The proposed scheme optimizes the scheduling of OSPF routing table calculations using Artificial Neural Network technique called Generalized Regression Neural Network. The scheme determines the suitable hold time based on three parameters: LSA-inter arrival time, the number of important control message in queue, and the computing utilization of the routers. The GRNN scheme is tested using Scalable Simulation Framework (SSFNet version 2.0) network simulator. Two kind of network topology with several link down scenarios used to test GRNN scheme and existing scheme (fixed hold time scheme). Results shows that GRNN provide faster convergence time compared to the existing scheme. 2013-01 Thesis http://eprints.utm.my/id/eprint/37980/ http://eprints.utm.my/id/eprint/37980/1/MohamadHaiderAbuYazidMFSKSM2013.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computing Faculty of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Abu Yazid, Mohamad Haider Scheduling of routing table calculation schemes in open shortest path first using artificial neural network
description	Internet topology changes due to events such as router or link goes up and down. Topology changes trigger routing protocol to undergo convergence process which eventually prepares new shortest routes needed for packet delivery. Real-time applications (e.g. VoIP) are increasingly being deployed in internet nowadays and require the routing protocols to have quick convergence times in the range of milliseconds. To speed-up its convergence time and better serve real-time applications, a new routing table calculation scheduling schemes for Interior Gateway Routing Protocol called Open Shortest Path First (OSPF) is proposed in this research. The proposed scheme optimizes the scheduling of OSPF routing table calculations using Artificial Neural Network technique called Generalized Regression Neural Network. The scheme determines the suitable hold time based on three parameters: LSA-inter arrival time, the number of important control message in queue, and the computing utilization of the routers. The GRNN scheme is tested using Scalable Simulation Framework (SSFNet version 2.0) network simulator. Two kind of network topology with several link down scenarios used to test GRNN scheme and existing scheme (fixed hold time scheme). Results shows that GRNN provide faster convergence time compared to the existing scheme.
format	Thesis
qualification_level	Master's degree
author	Abu Yazid, Mohamad Haider
author_facet	Abu Yazid, Mohamad Haider
author_sort	Abu Yazid, Mohamad Haider
title	Scheduling of routing table calculation schemes in open shortest path first using artificial neural network
title_short	Scheduling of routing table calculation schemes in open shortest path first using artificial neural network
title_full	Scheduling of routing table calculation schemes in open shortest path first using artificial neural network
title_fullStr	Scheduling of routing table calculation schemes in open shortest path first using artificial neural network
title_full_unstemmed	Scheduling of routing table calculation schemes in open shortest path first using artificial neural network
title_sort	scheduling of routing table calculation schemes in open shortest path first using artificial neural network
granting_institution	Universiti Teknologi Malaysia, Faculty of Computing
granting_department	Faculty of Computing
publishDate	2013
url	http://eprints.utm.my/id/eprint/37980/1/MohamadHaiderAbuYazidMFSKSM2013.pdf
_version_	1747816517694652416

Scheduling of routing table calculation schemes in open shortest path first using artificial neural network

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