Doutorado em Ciência da Computação
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Navegando Doutorado em Ciência da Computação por Assunto "5G"
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Item Escalonamento de recursos em redes sem fio 5G baseado em otimização de retardo e de alocação de potência considerando comunicação dispositivo a dispositivo(Universidade Federal de Goiás, 2021-10-15) Ferreira, Marcus Vinícius Gonzaga; Vieira, Flávio Henrique Teles; http://lattes.cnpq.br/0920629723928382; Vieira, Flávio Henrique Teles; Madeira, Edmundo Roberto Mauro; Lima, Marcos Antônio Cardoso de; Rocha, Flávio Geraldo Coelho; Oliveira Júnior, Antônio Carlos deIn this thesis, a resources scheduling scheme is proposed for 5G wireless network based on CP-OFDM (Cyclic Prefix - Orthogonal Frequency Division Multiplexing) and f-OFDM (filtered - OFDM) modulations in order to optimize the average delay and the power allocation for users. In the proposed approach the transmission rate value is calculated and the modulation format is defined so that minimize system BER (Bits Error Rate). The algorithm considers, in addition to the transmission modes determined to minimize the BER, the calculation of the system's weighted throughput to optimize the users' average delay. Additionally, it is proposed an algorithm for uplink transmission in 5G wireless networks with D2D (Device-to-device) multi-sharing communication which initially allocates resources for the CUEs (Cellular User Equipments) and subsequently allocates network resources for communication between DUEs (D2D User Equipment) pairs based in the optimization of the delay and power allocation. The proposed algorithm, namely DMCG (Delay Minimization Conflict Graph), considers the minimization of the estimated delay function using concepts of Network Calculus to decide on the allocation of idle resources of the network CUEs for DUEs pairs. In this thesis, the performance of the proposed algorithms for downlink and uplink transmission are verified and compared with others algorithms in the literature in terms of several QoS (Quality of Service) parameters and considering the carrier aggregation and 256-QAM (Quadrature Amplitude Modulation) technologies. In computational simulations they are also considered scenarios with propagation by millimeter waves and the 5G specifications of the 3GPP (3rd Generation Partnership Project) Release 15. The simulation results show that the algorithms proposed for downlink and uplink transmission provide better system performance in terms of throughput and delay, in addition to presenting lower processing time compared to optimization heuristics and other QoS parameters being compatible to those of the compared algorithms.Item Controle de admissão para network slicing considerando recursos de comunicação e computação(Universidade Federal de Goiás, 2023-05-10) Lima, Henrique Valle de; Cardoso, Kleber Vieira; http://lattes.cnpq.br/0268732896111424; Corrêa, Sand Luz; http://lattes.cnpq.br/3386409577930822; Corrêa, Sand Luz; Cardoso, Kleber Vieira; Oliveira Júnior, Antônio Carlos de; Costa, Ronaldo Martins da; Both, Cristiano BonatoThe 5G networks have enabled the application of various innovative and disruptive technologies such as Network Function Virtualization (NFV) and Software-Defined Networking (SDN). Together, these technologies act as enablers of Network Slicing (NS), transforming the way networks are operated, managed, and monetized. Through the concept of Slice-as-a-Service (SlaaS), telecommunications operators can monetize the physical and logical infrastructure by offering network slices to new customers, such as vertical industries. This thesis addresses the problem of tenant admission control using NS. We propose three admission control models for NS (MONETS-OBD, MONETS-OBS, and CAONS) that consider both communication and computation resources. To evaluate the proposed models, we compare the results with different classical algorithms from the literature, such as eUCB, e-greedy, and ONETS. We use data from different applications to enrich the analysis. The results indicate that the MONETS-OBD, MONETS-OBS, and CAONS heuristics perform admission control that approaches the set of ideal solutions. We achieve high efficiency with the MONETS-OBD and MONETS-OBS heuristics in controlling tenant admission, reaching acceptance rates of up to 99% in some cases. Furthermore, the CAONS heuristic, which employs penalties, not only achieves acceptance and reward rates close to the optimal solution but also significantly reduces the number of capacity violations. Lastly, the results highlight that the process of slice admission control should consider both communication and computation resources, which are scarce at the network edge. A solution that considers only communication resources can lead to incorrect and unfeasible interpretations, overestimating the capacity of computation resources.Item Recomendação de conteúdo ciente de recursos como estratégia para cache na borda da rede em sistemas 5G(Universidade Federal de Goiás, 2023-10-03) Monção, Ana Claudia Bastos Loureiro; Corrêa, Sand Luz; http://lattes.cnpq.br/3386409577930822; Cardoso, Kleber Vieira; http://lattes.cnpq.br/0268732896111424; Cardoso, Kleber Vieira; Corrêa, Sand Luz; Soares, Telma Woerle de Lima; Rosa, Thierson Couto; Fonseca, Anelise MunarettoRecently, the coupling between content caching at the wireless network edge and video recommendation systems has shown promising results to optimize the cache hit and improve the user experience. However, the quality of the UE wireless link and the resource capabilities of the UE are aspects that impact the user experience and that have been neglected in the literature. In this work, we present a resource-aware optimization model for the joint task of caching and recommending videos to mobile users. We also present a heuristic created to solve the problem more quickly. The goal is to maximize the cache hit ratio and the user QoE (concerning content preferences and video representations) under the constraints of UE capabilities and the availability of network resources by the time of the recommendation. We evaluate our proposed model using a video catalog derived from a real-world video content dataset (from the MovieLens project), real- world video representations and actual historical records of Channel Quality Indicators (CQI) representing user mobility. We compare the performance of our proposal with a state-of-the-art caching and recommendation method unaware of computing and network resources. Results show that our approach significantly increases the user’s QoE and still promotes a gain in effective cache hit rate.