arXiv subjects

Fillipe Santos

Publications and source records attributed to Fillipe Santos.

3 recordsLinked to original sources

arXiv2022

Multimedia Services Placement Algorithm for Cloud-Fog Hierarchical Environments

With the rapid development of mobile communication, multimedia services have experienced explosive growth in the last few years. The high quantity of mobile users, both consuming and producing these services to and from the Cloud Computing (CC), can outpace the available bandwidth capacity. Fog Computing (FG) presents itself as a solution to improve on this and other issues. With a reduction in network latency, real-time applications benefit from improved response time and greater overall user experience. Taking this into account, the main goal of this work is threefold. Firstly, it is proposed a method to build an environment based on Cloud-Fog Computing (CFC). Secondly, it is designed two models based on Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM). The goal is to predict demand and reserve the nodes' storage capacity to improve the positioning of multimedia services. Later, an algorithm for the multimedia service placement problem which is aware of data traffic prediction is proposed. The goal is to select the minimum number of nodes, considering their hardware capacities for providing multimedia services in such a way that the latency for servicing all the demands is minimized. An evaluation with actual data showed that the proposed algorithm selects the nodes closer to the user to meet their demands. This improves the services delivered to end-users and enhances the deployed network to mitigate provider costs. Moreover, reduce the demand to Cloud allowing turning off servers in the data center not to waste energy

cs.PF↗

arXiv2021

Temporal complex networks modeling applied to vehicular ad-hoc networks

VANETs solutions use aggregated graph representation to model the interaction among the vehicles and different aggregated complex network measures to quantify some topological characteristics. This modeling ignores the temporal interactions between the cars, causing loss of information or unrealistic behavior. This work proposes the use of both temporal graphs and temporal measures to model VANETs applications. To verify the viability of this model, we initially perform a comparative analysis between the temporal and aggregated modeling considering five different real datasets. This analysis shows that the aggregated model is inefficient in modeling the temporal aspects of networks. After that, we perform a network evaluation through a simulation by considering the impact of temporal modeling applied to the deployment of RSUs. First, we compare a solution based on our temporal modeling with a greedy algorithm based on an aggregated model to choose the positions of RSUs. In a scenario with 70 RSUs, we have 77% and 65% of coverage in the temporal and aggregated model (greedy algorithm), respectively. Second, we evaluate the use of aggregated and temporal measures applied as features in a genetic algorithm. The approach with temporal betweenness had the better result with 90% of the coverage area against 61% of aggregated one applied to the same scenario.

cs.SI↗

arXiv2019

Error Tolerant Path Planning for Swarms of Micro Aerial Vehicles with Quality Amplification

We present an error tolerant path planning algorithm for Micro Aerial Vehicle (MAV) swarms. We assume navigation without GPS-like techniques. The MAVs find their path using sensors and cameras, identifying and following a series of visual landmarks. The visual landmarks lead the MAVs towards their destination. MAVs are assumed to be unaware of the terrain and locations of the landmarks. They hold a priori information about landmarks, whose interpretation is prone to errors. Errors are of two types, recognition or advice. Recognition errors follow from misinterpretation of sensed data or a priori information, or confusion of objects, e.g., due to faulty sensors. Advice errors are consequences of outdated or wrong information about landmarks, e.g., due to weather conditions. Our path planning algorithm is cooperative. MAVs communicate and exchange information wirelessly, to minimize the number of recognition and advice errors. Hence, the quality of the navigation decision process is amplified. Our solution successfully achieves an adaptive error tolerant navigation system. Quality amplification is parameterized with respect to the number of MAVs. We validate our approach with theoretical proofs and numeric simulations.

cs.RO↗