The recent increase in the volume of services and applications, in addition to the accelerated growth in demand for wireless access, represent significant challenges for the fifth generation (5G) of mobile networks. The daily large-scale migration of people to urban centres is another aspect of this trend, as it entails what is known as the "tidal effec". This effect leads to natural fluctuations in traffic throughout the day and makes it difficult to conduct network dimensioning, control, and management, thus resulting in the inefficient use of network resources. A heuristic with two approaches for provisioning resources (one based on the aggregate throughput and the other on the number of connected users) is proposed in this paper. This is based on data extracted from the mobile subscriber movement in the current network architecture, where a database with geolocation information from the city of New York is used. The aim of this heuristic is to meet the imminent network demands of the future in light of the expected lack of available hardware resources in future mobile networks. Our results suggest that the network provisioning strategy meet the requirements of traffic variability by reducing the number of active antennas by 13% and the network-blocking probability by 3.7%, as well as by maximizing the efficiency of the baseband unit (BBU) and quantifying the small cells (SCs) needed to meet network demands.

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A computação em nuvem, além de promover um modelo de armazena- mento e processamento de dados compartilhados, fortalece o potencial técnico-econômico do CSP (Cloud Service Provider), apresentando inúmeras possibilidades no âmbito computacional. Neste trabalho, é proposto um modelo de custo e um cenário de avaliação com base no TCO (Total Cost of Ownership), avaliando o contexto, aquisição e operação de equipamentos para implantação de infraestruturas em nuvem. Dessa forma, foi possı́vel especificar os principais ativos de infraestruturas tı́picas de nuvem e sobretudo, avaliar seu desempenho financeiro a partir de projeções de custos considerando aspectos que inferem diretamente no retorno de investimentos de um Data Center.

Cloud computing, in addition to promoting a shared data storage and processing model, strengthens the Cloud Service Provider (CSP) technical and economic potential, presenting numerous investment possibilities. This paper proposes a cost model and an evaluation scenario based on Total Cost of Ownership (TCO), evaluating the context of acquisition and operation of equipment for the implementation of cloud infrastructure. Hence, it was possible to specify the main assets of typical cloud infrastructures and, above all, to evaluate their financial performance based on cost projections that took into account aspects that directly infer the return of Data Center investments.