Bandwidth Optimization Of Wireless Networks Using Artificial Intelligence Technique

• Author(s): Tamuno-omie Joyce Alalibo ; Sunny Orike ; Promise Elechi
• Paper ID: 1702018
• Page: 125-130
• Published Date: 23-03-2020
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 3 Issue 9 March-2020

Abstract

Bandwidth allocation and management play a vital role in satisfying the Quality of Service (QoS) requirements for applications and promote the move to user-centric network models. As bandwidth is a scarce resource, conventional methods for bandwidth allocation are gradually been swapped with artificial intelligence methods for better bandwidth utilization. In this study, the Whale Optimization Algorithm (WOA) was investigated for the provision of optimum allocation of bandwidth in wireless networks. WOA is a recent swarm intelligence method that copies the foraging pattern of humpback whales. In this study, the bandwidth was allocated to real-time users (RTUs) and non-real-time users while reserving bandwidth for future users. The simulations were implemented in MATLAB and the results were discussed in terms of connection probability with a focus on available bandwidth and the numbers of RTUs on the network. From the results, the proposed WOA technique efficiently optimized the bandwidth allocated to users and showed bandwidth management of the small amount of bandwidth.

Keywords

Whale Optimization Algorithm, bandwidth allocation, quality of service, wireless network, connection probability

Citations

IRE Journals:
Tamuno-omie Joyce Alalibo , Sunny Orike , Promise Elechi "Bandwidth Optimization Of Wireless Networks Using Artificial Intelligence Technique" Iconic Research And Engineering Journals Volume 3 Issue 9 2020 Page 125-130

IEEE:
Tamuno-omie Joyce Alalibo , Sunny Orike , Promise Elechi "Bandwidth Optimization Of Wireless Networks Using Artificial Intelligence Technique" Iconic Research And Engineering Journals, 3(9)