Optimal channel selection for tri-band Wi-Fi in a residential scenario
Main Author: | |
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Publication Date: | 2023 |
Format: | Master thesis |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10773/41965 |
Summary: | The widespread adoption of Internet of Things devices and the increasing demand for high-speed, reliable, and secure wireless connectivity pose significant challenges for existing wireless networking solutions in modern smart homes. As such, there is an increasing urgency for the development of advanced and effective wireless technologies that can fulfill the ever-growing requirement for interconnected devices and services deployed in households. In this context, the use of Wi-Fi 6E offers several compelling advantages, over previous generations of Wi-Fi, critical for ensuring a seamless and efficient wireless experience for end users. Furthermore, the deployment of mesh networks by means of tri-band Wi-Fi 6E equipment, as opposed to traditional Wi-Fi setups, holds the potential to significantly improve wireless coverage, minimize network downtime, and achieve scalable network growth, coupled with an expanded spectrum access, leveraging the 2.4, 5 and 6 GHz frequency bands. However, mismanagement of the different bands can be detrimental to the network’s health, leading to higher interference levels and bottlenecks. In fact, the static method of locking devices to a specific band still remains as the most adopted setup deployed in domestic networks. This dissertation provides a dynamic Wi-Fi link orchestration solution that, by gathering relevant metrics from the Wi-Fi devices, determines the optimal layout for the network and assigns the correct channel for each link, ensuring that a balance is struck between minimizing the interference and maximizing the link capacity. This is done through a proposed model that relies on heuristics to guide the decision making of the algorithm. To facilitate the metrics collection and client steering process, the EasyMesh specification is employed in the network, providing an easy setup, management and scalability of multiple wireless Access Points. Finally, the created model is put into action by deploying it into a real domestic network in a star and daisy chain configuration. In light of the testbed outcomes, it is evident that connections degrade with increased channel sharing and the presence of more obstacles between devices. Additionally, keeping channels in the backhaul connections minimally occupied, even at the expense of fronthaul links, enables the backhaul to support higher traffic volumes and lower delays for multiple fronthaul clients. The results show that the algorithm implementing the model was capable of altering the network topology to improve the overall capacity, adapting the link channels to the existing traffic flowing through the network. |
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Optimal channel selection for tri-band Wi-Fi in a residential scenarioEasymeshIEEE 802.11IEEE 802.11axOptimizationTri-bandWi-FiWi-Fi 6Wi-Fi 6eWLANWireless mesh networkThe widespread adoption of Internet of Things devices and the increasing demand for high-speed, reliable, and secure wireless connectivity pose significant challenges for existing wireless networking solutions in modern smart homes. As such, there is an increasing urgency for the development of advanced and effective wireless technologies that can fulfill the ever-growing requirement for interconnected devices and services deployed in households. In this context, the use of Wi-Fi 6E offers several compelling advantages, over previous generations of Wi-Fi, critical for ensuring a seamless and efficient wireless experience for end users. Furthermore, the deployment of mesh networks by means of tri-band Wi-Fi 6E equipment, as opposed to traditional Wi-Fi setups, holds the potential to significantly improve wireless coverage, minimize network downtime, and achieve scalable network growth, coupled with an expanded spectrum access, leveraging the 2.4, 5 and 6 GHz frequency bands. However, mismanagement of the different bands can be detrimental to the network’s health, leading to higher interference levels and bottlenecks. In fact, the static method of locking devices to a specific band still remains as the most adopted setup deployed in domestic networks. This dissertation provides a dynamic Wi-Fi link orchestration solution that, by gathering relevant metrics from the Wi-Fi devices, determines the optimal layout for the network and assigns the correct channel for each link, ensuring that a balance is struck between minimizing the interference and maximizing the link capacity. This is done through a proposed model that relies on heuristics to guide the decision making of the algorithm. To facilitate the metrics collection and client steering process, the EasyMesh specification is employed in the network, providing an easy setup, management and scalability of multiple wireless Access Points. Finally, the created model is put into action by deploying it into a real domestic network in a star and daisy chain configuration. In light of the testbed outcomes, it is evident that connections degrade with increased channel sharing and the presence of more obstacles between devices. Additionally, keeping channels in the backhaul connections minimally occupied, even at the expense of fronthaul links, enables the backhaul to support higher traffic volumes and lower delays for multiple fronthaul clients. The results show that the algorithm implementing the model was capable of altering the network topology to improve the overall capacity, adapting the link channels to the existing traffic flowing through the network.A ampla adoção de dispositivos da Internet das Coisas e o aumento do interesse por ligações sem fios de alta velocidade, confiáveis e seguras, representam desafios significativos para as soluções existentes de redes sem fios em casas inteligentes modernas. Como tal, surge a necessidade de desenvolver tecnologias sem fios avançadas e eficazes que possam satisfazer os requisitos cada vez maiores por parte de dispositivos e serviços interligados dentro de uma casa. Neste contexto, o uso do Wi-Fi 6E oferece várias vantagens, em relação às gerações anteriores de Wi-Fi, essenciais para garantir uma experiência sem fios eficiente e contínua para os utilizadores finais. Além disso, a implementação de redes mesh por meio de equipamento Wi-Fi 6E tri-banda, em oposição às configurações Wi-Fi tradicionais, tem o potencial de melhorar significativamente a cobertura sem fios, minimizar o tempo de inatividade da rede e alcançar um crescimento escalável da rede, juntamente com o uso alargado do espectro disponível, aproveitando as faixas de frequência de 2.4, 5 e 6 GHz. No entanto, a má gestão das diferentes bandas pode ser prejudicial ao desempenho da rede, originando níveis de interferência elevados e bottlenecks no desempenho da rede. Na realidade, a configuração típica de uma rede doméstica ainda envolve a atribuição estática de frequências às diferentes ligações. Esta dissertação tem como objetivo fornecer uma solução dinâmica de orquestração de ligações Wi-Fi que, ao reunir métricas relevantes dos dispositivos Wi-Fi, determine o layout ideal para a rede e atribua o canal correto para cada ligação, garantindo que seja alcançado um equilíbrio entre a minimização da interferência e maximização da capacidade da ligação. Este processo é feito por meio de um modelo proposto que se baseia em heurísticas para orientar a tomada de decisão do algoritmo. Para facilitar a recolha de métricas e o processo de direcionamento dos clientes, a rede segue a especificação EasyMesh, proporcionando fácil configuração, administração e escalabilidade de múltiplos Access Points sem fios. Por fim, o modelo criado é colocado em ação numa rede doméstica real com uma configuração em estrela e em cascata. Considerando os resultados observados em cenário real, é evidente que as ligações degradam-se com o aumento da partilha de canais e a presença de mais obstáculos entre os dispositivos. Além disso, manter os canais nas ligações de backhaul minimamente ocupados, mesmo à custa das ligações de fronthaul, permite que o backhaul suporte volumes de tráfego mais elevados e menores atrasos nos pacotes para vários clientes de fronthaul. Os resultados mostram que o algoritmo que implementa o modelo foi capaz de alterar a topologia da rede para melhorar a capacidade global, adaptando os canais das ligações ao tráfego existente na rede.2025-01-03T00:00:00Z2023-12-20T00:00:00Z2023-12-20info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10773/41965engOliveira, Rafael Martinho Fernandesinfo:eu-repo/semantics/embargoedAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-06-10T01:48:23Zoai:ria.ua.pt:10773/41965Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:55:15.623627Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Optimal channel selection for tri-band Wi-Fi in a residential scenario |
title |
Optimal channel selection for tri-band Wi-Fi in a residential scenario |
spellingShingle |
Optimal channel selection for tri-band Wi-Fi in a residential scenario Oliveira, Rafael Martinho Fernandes Easymesh IEEE 802.11 IEEE 802.11ax Optimization Tri-band Wi-Fi Wi-Fi 6 Wi-Fi 6e WLAN Wireless mesh network |
title_short |
Optimal channel selection for tri-band Wi-Fi in a residential scenario |
title_full |
Optimal channel selection for tri-band Wi-Fi in a residential scenario |
title_fullStr |
Optimal channel selection for tri-band Wi-Fi in a residential scenario |
title_full_unstemmed |
Optimal channel selection for tri-band Wi-Fi in a residential scenario |
title_sort |
Optimal channel selection for tri-band Wi-Fi in a residential scenario |
author |
Oliveira, Rafael Martinho Fernandes |
author_facet |
Oliveira, Rafael Martinho Fernandes |
author_role |
author |
dc.contributor.author.fl_str_mv |
Oliveira, Rafael Martinho Fernandes |
dc.subject.por.fl_str_mv |
Easymesh IEEE 802.11 IEEE 802.11ax Optimization Tri-band Wi-Fi Wi-Fi 6 Wi-Fi 6e WLAN Wireless mesh network |
topic |
Easymesh IEEE 802.11 IEEE 802.11ax Optimization Tri-band Wi-Fi Wi-Fi 6 Wi-Fi 6e WLAN Wireless mesh network |
description |
The widespread adoption of Internet of Things devices and the increasing demand for high-speed, reliable, and secure wireless connectivity pose significant challenges for existing wireless networking solutions in modern smart homes. As such, there is an increasing urgency for the development of advanced and effective wireless technologies that can fulfill the ever-growing requirement for interconnected devices and services deployed in households. In this context, the use of Wi-Fi 6E offers several compelling advantages, over previous generations of Wi-Fi, critical for ensuring a seamless and efficient wireless experience for end users. Furthermore, the deployment of mesh networks by means of tri-band Wi-Fi 6E equipment, as opposed to traditional Wi-Fi setups, holds the potential to significantly improve wireless coverage, minimize network downtime, and achieve scalable network growth, coupled with an expanded spectrum access, leveraging the 2.4, 5 and 6 GHz frequency bands. However, mismanagement of the different bands can be detrimental to the network’s health, leading to higher interference levels and bottlenecks. In fact, the static method of locking devices to a specific band still remains as the most adopted setup deployed in domestic networks. This dissertation provides a dynamic Wi-Fi link orchestration solution that, by gathering relevant metrics from the Wi-Fi devices, determines the optimal layout for the network and assigns the correct channel for each link, ensuring that a balance is struck between minimizing the interference and maximizing the link capacity. This is done through a proposed model that relies on heuristics to guide the decision making of the algorithm. To facilitate the metrics collection and client steering process, the EasyMesh specification is employed in the network, providing an easy setup, management and scalability of multiple wireless Access Points. Finally, the created model is put into action by deploying it into a real domestic network in a star and daisy chain configuration. In light of the testbed outcomes, it is evident that connections degrade with increased channel sharing and the presence of more obstacles between devices. Additionally, keeping channels in the backhaul connections minimally occupied, even at the expense of fronthaul links, enables the backhaul to support higher traffic volumes and lower delays for multiple fronthaul clients. The results show that the algorithm implementing the model was capable of altering the network topology to improve the overall capacity, adapting the link channels to the existing traffic flowing through the network. |
publishDate |
2023 |
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2023-12-20T00:00:00Z 2023-12-20 2025-01-03T00:00:00Z |
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