Enhancement of mobile IPV6 for handover latency using robust regression model

The recent applications of wireless networks demand high Quality of Service (QoS) and mobility management between access networks. For this reason, emergent advances in IEEE 802.11 standards have been witnessed to achieve seamless communication between mobile nodes. However, since existing handover...

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Main Author: Hares Wady, Shakhawan
Format: Thesis
Published: 2012
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id my-utm-ep.30772
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spelling my-utm-ep.307722020-08-30T08:16:22Z Enhancement of mobile IPV6 for handover latency using robust regression model 2012 Hares Wady, Shakhawan TA Engineering (General). Civil engineering (General) The recent applications of wireless networks demand high Quality of Service (QoS) and mobility management between access networks. For this reason, emergent advances in IEEE 802.11 standards have been witnessed to achieve seamless communication between mobile nodes. However, since existing handover mechanisms have shortcomings in terms of mobility handover cost and latency, more robust handover decision approach should be considered. To this end, this research proposed a decision approach to accurately trigger handover process between current and next access point. The proposed approach incorporates robust regression model is to predict the received signal strength (RSS) of the wireless channel between the Mobile Node (MN) and the access point. Thus, theMN makes an accurate handover decision as well as layer 3 handover process occurs in advance to the one in layer 2. Our theoretical analysis and simulation results show that the proposed handover decision approach performs the best compared to the existing handover decision schemes in terms of handover latency and cost. 2012 Thesis http://eprints.utm.my/id/eprint/30772/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:70359?site_name=Restricted Repository masters Universiti Teknologi Malaysia, Faculty of Civil Engineering Faculty of Civil Engineering
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
topic TA Engineering (General)
Civil engineering (General)
spellingShingle TA Engineering (General)
Civil engineering (General)
Hares Wady, Shakhawan
Enhancement of mobile IPV6 for handover latency using robust regression model
description The recent applications of wireless networks demand high Quality of Service (QoS) and mobility management between access networks. For this reason, emergent advances in IEEE 802.11 standards have been witnessed to achieve seamless communication between mobile nodes. However, since existing handover mechanisms have shortcomings in terms of mobility handover cost and latency, more robust handover decision approach should be considered. To this end, this research proposed a decision approach to accurately trigger handover process between current and next access point. The proposed approach incorporates robust regression model is to predict the received signal strength (RSS) of the wireless channel between the Mobile Node (MN) and the access point. Thus, theMN makes an accurate handover decision as well as layer 3 handover process occurs in advance to the one in layer 2. Our theoretical analysis and simulation results show that the proposed handover decision approach performs the best compared to the existing handover decision schemes in terms of handover latency and cost.
format Thesis
qualification_level Master's degree
author Hares Wady, Shakhawan
author_facet Hares Wady, Shakhawan
author_sort Hares Wady, Shakhawan
title Enhancement of mobile IPV6 for handover latency using robust regression model
title_short Enhancement of mobile IPV6 for handover latency using robust regression model
title_full Enhancement of mobile IPV6 for handover latency using robust regression model
title_fullStr Enhancement of mobile IPV6 for handover latency using robust regression model
title_full_unstemmed Enhancement of mobile IPV6 for handover latency using robust regression model
title_sort enhancement of mobile ipv6 for handover latency using robust regression model
granting_institution Universiti Teknologi Malaysia, Faculty of Civil Engineering
granting_department Faculty of Civil Engineering
publishDate 2012
_version_ 1747815744581664768