Traffic demand in wireless communication systems has emerged as a key issue over recent decades. An ever-increasing trend is projected for the next few years, with explosive data traffic expected to materialize and mobile users imposing new quality of service requirements. This growing traffic demand, combined with increasingly complex heterogeneous network (HetNet) scenarios, has presented ever more challenges for mobile network operators in terms of service, coverage, load balancing, and quality of service. Considering the traditional association mechanism based on maximum power received, HetNets tend to remain unbalanced, making it challenging to satisfy mobile users' traffic requirements. In this paper, instead of trying to maximize the achievable downlink rate per user, we couple the cell range expansion (CRE) technique with a particle swarm optimization (PSO) algorithm to maximize the number of users whose downlink requirements are met. The proposed scheme considers both the loads of base stations and the signal-to-interference-plus-noise ratio (SINR) of user equipment to model an objective function that seeks to compute specific CRE bias values per small base station. The proposed scheme is also compared with some classical PSO implementations. Numerical results validate the performance of the proposed schemes, which effectively fulfill users' data traffic requirements by reducing network imbalance.INDEX TERMS Cell range expansion, heterogeneous mobile networks, load balancing, particle swarm optimization, user association.

The modern society is daily becoming more internetconnected. Such a connection requires an unprecedented amount of energy to operate each piece of equipment that is part of the heterogeneous networks (HetNets). The network infrastructure is highly energy-consuming and producing a considerable amount of CO2. One strategy to minimize such energy consumption is making usage of renewable energy, such as solar and wind. This article aims to present a study of the technical, economic, and environmental feasibility for the installation of photovoltaic harvesting systems in the context of HetNet and backhaul networks. This proposal is based on the use of analytical models to scale the deployment of the photovoltaic systems, considering costs associated with acquisition, operation, maintenance, and adopted the energy matrix of this system. The results indicate sustainable and financial viability with the adoption of photovoltaic systems when compared with the energy source mainly considered in the literature. Also, the results highlight that adopted energy matrix and environmental parameters are essential items, which must be highly considered when the overall mobile network infrastructure is planned.

Expanding broadband services represents a significant challenge for broadband operators, especially in light of the requirements related to the total cost of ownership of these technologies. In the last few years, this expansion has advanced significantly, but it still represents a challenge that must be overcome since there is a need to provide low-cost services to rural communities in remote areas. Issues related to geographical location, the low income of residents, and the lack of public infrastructural facilities lead to a disadvantageous relationship between the potential revenue for operators and the high costs of deploying infrastructure. Although there are several research endeavors in the literature aimed at addressing how connectivity can be provided, they do not discuss systems that take account of the specific features of these regions or that have adapted services and network applications to meet the needs of these communities. Thus, using dimensioning systems for the total cost of network ownership and taking into account capital and network operating expenses, this study establishes a technical and economic framework for the deployment of broadband networks in rural and remote areas. It also applies economic feasibility analysis techniques designed to assist decision making by interpreting the effects of any financial investment made and estimating the expected profits of the broadband operators. We also recommend the use of socioeconomic indicators to predict the potential social impact of this framework on the development of these regions. We employ a case study to demonstrate the operational features of the planned framework. Based on real data obtained from a municipality located in the Brazilian Amazon region, we show that it is possible to reduce the cost of subscribing to broadband services for end-users by reducing deployment costs and thus ensure that access to digital services can be equitably obtained.INDEX TERMS Broadband services, rural and remote areas, total cost of ownership, feasibility analysis.

Due to the limited computing resources of drones, it is difficult to handle computation-intensive tasks locally, hence, fog-based computation offloading has been widely adopted. The effectiveness of an offloading operation, however, is determined by its ability to infer where the execution of code/data represents less computational effort for the drone, so that, by deciding where to offload correctly, the device benefits. Thus, this paper proposes MonDroneFog, a novel fog-based architecture that supports image offloading, as well as monitoring and storing the performance metrics related to the drone, wireless network, and cloudlet. It takes advantage of the main machine-learning algorithms to provide offloading decisions with high levels of accuracy, F1, and G-mean. We evaluate the main classification algorithms under our database and the results show that Multi-Layer Perceptron (MLP) and Logistic Regression classifiers achieve 99.64% and 99.20% accuracy, respectively. Under these conditions, MonDrone-Fog works well in dense forests when weather conditions are favorable and can be useful as a support system for SAR missions by providing a shorter runtime for image operations.

Este trabalho apresenta a aplicação de um modelo de Monitoramento Adaptativo da Pesca em conjunto com técnicas de clusterização de dados mistos relativos à registros de atividade pesqueira na bacia Araguaia-Tocantins entre 2016 e 2017. Os registros de dados dos desembarques pesqueiros foram obtidos por meio do Sistema Integrado de Estatística Pesqueira (SIEPE), que se apresenta como uma proposta de ferramenta capaz de dinamizar o processo de coleta e análise de dados das bacias pesqueiras da Região Amazônica. Por meio da interface de exploração de dados do SIEPE diversas variáveis categóricas e numéricas foram extraídas. A partir da aplicação do algoritmo k-prototypes, revelou-se que as variáveis numéricas mais expressivas no estudo foram o rendimento da pesca e potência do motor da embarcação, enquanto que as variáveis categóricas mais expressivas foram, nome popular espécie e ambiente de pesca. Estas variáveis devem ser levadas em consideração em programas de monitoramento da pesca na bacia Araguaia-Tocantins, bem como o uso do SIEPE para apoiar a gestão pesqueira em diferentes escalas.

Com o crescimento do tráfego multimídia, com foco especial nos vídeos de alta resolução, percebe-se a existência de diversos desafios a serem contornados. Um destes pode trazer insatisfação ao usuário final diante do serviço prestado, se refere a qualidade percebida após o recebimento do streaming ou vídeo. Neste sentido, este trabalho realiza a avaliação de desempenho dos vídeos com resoluções em 2K e 4K, em cenário real indoor. Para este estudo empírico, utilizam-se métricas de análise objetiva como PSNR, VQM e SSIM, e uma subjetiva, o MOS, que representa uma opinião média do usuário após reprodução do vídeo. As principais ferramentas utilizadas neste estudo foram os frameworks EvalVid e MSU Video Quality.

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levantamento de métricas para avaliação de desempenho da técnica de offloading com uso de drone e servidor Cloudlet em ambiente de Fog Computing para a transmissão e processamento de imagens através de algoritmo tradicional de detecção e reconhecimento facial em tempo real, em diferentes cenários, visando a análise do consumo energético do drone, ao longo do processo, a intensidade de sinal entre o drone e o orquestrador, e o tempo de processamento gasto em cada entidade, drone e maquinas virtuais.