SUMMARYThe main objective on this research is the development of finding the optimal parameters for a routing algorithm for network routers based on the ant algorithm described as AntNet. The optimum parameters for this type of algorithm improve a more efficient alternative to those given by the RIP, EIGRP and OSPF routing protocols, to be applied in a data network. This shall be tested in two networks and routers defined, taking the same characteristics for the three groups: RIP, OSPF and by the result provided by the genetic algorithm implemented using a static network. The system recognizes the best path between networks of routers, based on the principle of AntNet networks or networks of ants, which are the best way from exploring almost all roads, using estimergia to go there and make optimal. MatLab was used to detect the best way. Later this road was implemented in a real network data, sending a test file in compressed format. Its efficiency compared with RIP and OSPF protocols are checked. For validation of the network, compressed files, which were sent for ten consecutive times and the results were taken using a server and a network connected by the given client used. The server and client are implemented in Linux, to measure the arrival time of the file and thus the data transfer rate. It was found that the routing algorithm, under the optimal parameters found, provided a reliable alternative for routing data networks. Keywords: ant algorithm, ant colony algorithm, routing protocols, routing simulation. RESUMENEl principal objetivo de la investigación es encontrar los parámetros óptimos para un algoritmo de encaminamiento para una red de routers basado en el algoritmo de la hormiga descrito como Antnet. Los parámetros óptimos para este tipo de algoritmo, mejorará de manera más eficiente a las dadas por los estándares RIP, EIGRP y OSPF, para ser aplicados en una red de datos. Para ello se probará en dos redes de routers ya definidas, tomando características iguales para los tres grupos: RIP, OSPF y por el resultado proporcionado por el algoritmo genético implementado mediante una red estática. El sistema, reconoce el mejor camino entre redes de routers, basándose en el principio de las redes AntNet o redes de hormigas, las cuales encuentran el mejor camino a partir de la exploración de casi todos los caminos, utilizando la estimergia, para recorrerlos y marcar los óptimos. Para la detección del mejor camino se utilizó MatLab. Posteriormente se implementó dicho camino en una red real de datos, enviando un archivo de prueba en formato comprimido. Se comprobó su eficiencia comparándolo con los protocolos RIP y OSPF. Para la validación de la red, se utilizaron archivos comprimidos, los cuales fueron enviados por diez veces consecutivas y se tomaron los resultados con ayuda de un servidor y un cliente conectados por la red dada. El servidor y el cliente se implementaron en Linux, para poder medir el tiempo de llegada del archivo y así la tasa de transferencia de datos. Se comprobó que el algoritmo de enrutamiento, bajo los parámetros óptimos encontrados, brindó una alternativa confiable, para el encaminamiento de redes de datos. Palabras Clave: algoritmo de la hormiga, algoritmo de colonia de hormigas, protocolos de enrutamiento, simulación de enrutamiento.

Due to the increasing threat of network attacks, Firewall has become crucial elements in network security, and have been widely deployed in most businesses and institutions for securing private networks. A Conventional Business firewall is a robust system with a great capacity to manage security and access to other networks, especially the Internet, but is robust in size and requires a large investment by the company that requires it, about $2000USD and only large organizations have the ability to invest in it. The design of an IPv6 Plug and Play business firewall based on Iptables, Nettop and Linux is much smaller in size, but creates a big impact in the productivity and security of the network business for about $400 USD budget. When device is connected will not require reconfiguration of the local network and clients, and also the device can work as proxy mode, router mode, DHCP server, DNS server and other capabilities. In order to improve security and performance, modern enterprises have to deploy and manage their own firewalls.

Aquaculture plays a vital role in meeting global food demands, necessitating technological innovations for sustainable production. This study investigates deep learning-based semantic image segmentation for enhanced monitoring of rainbow trout (Oncorhynchus mykiss) in Puno, Peru. We conducted three experiments using UNET and UNETR architectures, varying image resolution, loss functions, and optimizers on a dataset of 1200 high-resolution images. Experiment 1, with UNET and 256 × 256 pixel images, achieved an IoU of 0.942854 after 20 epochs, using MSELoss and Adam, demonstrating superior segmentation accuracy. Experiment 2, utilizing UNET with 512 × 512 pixel images, resulted in an IoU of 0.803244 after 50 epochs, with L1Loss and Adam, indicating satisfactory performance despite increased complexity. Experiment 3, employing UNETR with 256 × 256 pixel images, yielded lower IoU scores, with a best IoU of 0.253928, highlighting the challenge of training Transformer-based models with limited data. A critical aspect of this study was the use of a coin as a scale reference in all experiments, enabling precise conversion of pixel measurements to physical dimensions. This, combined with OpenCV for contour detection, allowed for accurate fish size estimations, validated by comparisons with real images. The results underscore UNET’s effectiveness for aquaculture image segmentation, while also emphasizing data requirements for UNETR. This approach provides a non-invasive, automated method for monitoring fish growth and health, contributing to sustainable aquaculture practices.