Navegando por Assunto "QoS - Quality of service"

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Acesso aberto (Open Access)
Uma estrategia para alocação eficiente de recursos móveis utilizando sistema fuzzy para um esquema de planejamento e provimento de QoS
(Universidade Federal do Pará, 2019-09-25) DIAS, Suzane Alfaia; CARVALHO, Tássio Costa de; http://lattes.cnpq.br/4772364162256162; FRANCÊS, Carlos Renato Lisboa; http://lattes.cnpq.br/7458287841862567
With mobile data growth and rapid urbanization trends, there will be an extremely high density of wireless communication links in cities, therefore users expect an environment where they can access the Internet to their devices anytime, anywhere. Due to CAPEX/OPEX problems, a small cell deployment is not an economical strategy in scenarios of intense data tra_c, so the use of UAVs to improve network coverage and performance becomes feasible. In order to improve the Quality of Service of the network, a computational system was proposed to perform decision making that receives as input network information such as network throughput, packet loss rate and delay, and returns to network quality for that speci_c type of network. application. The system as a whole veri_es the necessity or not of using Unmanned Aerial Vehicles (UAVs) to improve the quality of the network and the coverage of the area of greatest demand. If UAVs are required, they are shifted to the areas of greatest demand. Otherwise, the UAVs remain in the base station. Through the proposed method there were signi_cant improvements in the Quality of Service (QoS) of the network, allowing a reduction in packet loss and delay, and an increase in the network throughput rate.
Acesso aberto (Open Access)
Estratégia para otimização de offloading entre as redes móveis VLC e LTE baseada em q-learning
(Universidade Federal do Pará, 2018-08-31) SOUTO, Anderson Vinicius de Freitas; OLIVEIRA, Edvar da Luz; http://lattes.cnpq.br/1840754571733900; FRANCÊS, Carlos Renato Lisboa; http://lattes.cnpq.br/7458287841862567
The increase in the consumption of data traffic is motivated by the increasing number of devices like smartphone and tablets, since there is a need to be connected with everything and with everyone. Applications such as streaming video and online games require a higher rate of data transmission, this high demand corroborates the overload of mobile networks based on radio frequency, so as to culminate in a possible shortage of the RF spectrum. Therefore, this work seeks to optimize offloading between LTE and VLC, and for this a methodology based on reinforcement learning called Q-Learning is used. The algorithm uses as input the environment variables that are related to the signal quality, density and speed of the user to learn and select the best connection. Therefore, the results of the simulation show the efficiency of the proposed methodology in comparison with the predominant RSS scheme in the area literature. as it has been proven by QoS metrics to support higher data rates, as well as ensuring an 18% improvement over service interruptions as the number of users increases in the system.
Acesso aberto (Open Access)
Métricas de QoE/QoS de vídeo em redes sem fio para auxilio ao planejamento de ambientes indoor utilizando uma abordagem bayesiana
(Universidade Federal do Pará, 2015-03-30) CARVALHO, André Augusto Pacheco de; CAVALCANTE, Gervásio Protásio dos Santos; http://lattes.cnpq.br/2265948982068382
The evolution of applications on wireless networks has grown in recent years, due to the increased number of smartphone users, tablets and others. The availability of demanding services such as video transmission, affects Quality Experience (QoE) and Quality of Service (QoS) provided to domestic users and trade, this had stimulated the study of new resource management techniques networks, aiming to provide quality services to a customer each increasingly demanding. This thesis presents a methodology Intelligence Artificial using a Bayesian network with a hybrid evaluation strategy analyzing the behavior metrics QoE and QoS in the LAN network design wireless. The diversity of the place of Measurements chosen compound materials such as brick, glass, wood and concrete. It was necessary first to map all the points to be measured before and after deliberately placing each barrier outdated the signal. Metrics as level Receiver Signal Strength Intensity signal (RSSI) Jitter, delay end to end network for the video transmission, PeakSignal-to-NoiseRatio (PSNR) and Structural Similarity (SSIM) were collected during the Measurements. And using the Bayesian Network inferences were made for each metric and could not find satisfactory results for the proposed solution assist the wireless network planning in indoor environments. Enabling demonstrate that up to 10 meters away from the transmitter, the signal has its best power, and delay metrics in order to have more than 65% probability that the lower delay range and following this optimum performance the Jitter has more than 65% probability in this lower range. And the QE metrics, PSRN and SSIM have a similar behavior and has more than 80% probability of getting your greater value, and consequently the video has its best reception. These results show that does not preclude the use of this proposal in other situations.