Enhanced Resource Allocation Algorithm for Heterogeneous Wireless Networks
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Published:2020-11-20
Issue:6
Volume:24
Page:763-773
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ISSN:1883-8014
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Container-title:Journal of Advanced Computational Intelligence and Intelligent Informatics
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language:en
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Short-container-title:JACIII
Author:
Mathonsi Topside E., ,Tshilongamulenzhe Tshimangadzo Mavin,Buthelezi Bongisizwe Erasmus
Abstract
In heterogeneous wireless networks, service providers typically employ multiple radio access technologies to satisfy the requirements of quality of service (QoS) and improve the system performance. However, many challenges remain when using modern cellular mobile communications radio access technologies (e.g., wireless local area network, long-term evolution, and fifth generation), such as inefficient allocation and management of wireless network resources in heterogeneous wireless networks (HWNs). This problem is caused by the sharing of available resources by several users, random distribution of wireless channels, scarcity of wireless spectral resources, and dynamic behavior of generated traffic. Previously, resource allocation schemes have been proposed for HWNs. However, these schemes focus on resource allocation and management, whereas traffic class is not considered. Hence, these existing schemes significantly increase the end-to-end delay and packet loss, resulting in poor user QoS and network throughput in HWNs. Therefore, this study attempts to solve the identified problem by designing an enhanced resource allocation (ERA) algorithm to address the inefficient allocation of available resources vs. QoS challenges. Computer simulation was performed to evaluate the performance of the proposed ERA algorithm by comparing it with a joint power bandwidth allocation algorithm and a dynamic bandwidth allocation algorithm. On average, the proposed ERA algorithm demonstrates a 98.2% bandwidth allocation, 0.75 s end-to-end delay, 1.1% packet loss, and 98.9% improved throughput performance at a time interval of 100 s.
Funder
Tshwane University of Technology
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
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