FRGS-13-081-0322/ design and modelling of novel dynamic bandwidth aggregation scheme in heterogeneous wireless network (hwn) for mission critical applications

This research aims to model and analyze the RAT section methods, resource allocation policy and packet reordering pattern. A multi criteria selection based method, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been applied to select the most suitable RAT in HWN. The TO...

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Bibliographic Details
Main Authors: Anwar, Farhat, Huda Adibah, Mohd
Format: Monograph
Language:English
Published: 2018
Subjects:
Online Access:http://irep.iium.edu.my/66276/
http://irep.iium.edu.my/66276/3/66276%20FRGS%20Final%20Report.pdf
Description
Summary:This research aims to model and analyze the RAT section methods, resource allocation policy and packet reordering pattern. A multi criteria selection based method, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been applied to select the most suitable RAT in HWN. The TOPSIS method achieved to select the most appropriate RATs based on the types of services like voice calls, file downloading and video streaming according to their priority settings. The resource allocation has been modeled based on the game theoretic approach, namely; Shapley Value. The amount of bandwidth has been calculated to transmit 600Kbps data over the three networks where 225Kbps, 141Kbps and 233.33Kbps have been transmitted through, WiFi, Cellular and WiMAX networks respectively. An algorithm has been proposed to measure the associated delay and reordering entropy caused due to packet reordering in HWN and it has been compared to the Earlies Delivery Path First (EDPF) method both for CBR and VBR applications on NS3 simulator. A video clip for 1800 seconds have been transmitted from sender to receiver to analyze the performance in HWN. Based on the simulation results, the proposed method shows around 40% improvement over the EDPF method both for CBR and VBR applications in terms of packet reordering delay.