Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

A centralized architecture for autonomic quality of experience oriented handover in dense networks

Aldhaibani, OA, AL-Jumaili, MH, Raschella, A, Kolivand, H and Preethi, AP (2021) A centralized architecture for autonomic quality of experience oriented handover in dense networks. Computers and Electrical Engineering, 94. ISSN 0045-7906

A Centralized Architecture for Autonomic Quality of Experience Oriented Handover in Dense Networks.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (992kB) | Preview


This paper presents an Optimised Handover (HO) Algorithm for Dense Wireless Local Area Networks (WLANs) based on a novel architecture of Software Defined Wireless Network (SDWN). The work has been designed to be effective in large network environments with a high density of Access Points (APs) and stations, which increase the chances of the Ping-Pong HO effect. Specifically, it considers Quality of Experience (QoE) by applying an optimised HO algorithm for WLANs, which relies on Fuzzy Logic Control Theory (FLCT) combined with Adaptive Hysteresis Values (AHVs). SDWN allows to monitor and manage the networks and to autonomously programme the APs through a centralized controller. The paper includes also a detailed performance analysis of the algorithm developed in an SDWN-based simulator implemented through OPNET. Specifically, our algorithm achieved promising performance results compared to the state of the art in terms of QoE, throughput, delay and reduction of the ping-pong HO effect.

Item Type: Article
Uncontrolled Keywords: 0803 Computer Software, 0805 Distributed Computing, 0906 Electrical and Electronic Engineering
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Divisions: Civil Engineering & Built Environment
Computer Science & Mathematics
Publisher: Elsevier
Date Deposited: 03 Sep 2021 09:14
Last Modified: 10 Aug 2022 00:50
DOI or ID number: 10.1016/j.compeleceng.2021.107352
URI: https://researchonline.ljmu.ac.uk/id/eprint/15438
View Item View Item