Sustainable cloud computing for cognitive intent based networks

Intent based networks enable auto-configuration and require low latency access to cloud platforms. The use of cloud platforms incurs high operational costs. Low latency access can be realized by siting data centres close to subscribers. This paper proposes aquaria data centers with low operating costs and latency. In LTE, cloud platforms are normally accessed via the packet network gateway reachable via the serving gateway and mobility management entity. Aquaria data centers are sited close to LTE subscribers and accessed via the mobility management entity. This reduces the size of control packets in the LTE network. Simulations show that the proposed architecture reduces the size of control packets by up to 49.7% and 99.3% when header packets are uncompressed and compressed respectively. The delay associated with receiving configuration information is reduced by 50% on average. The channelcapacity is enhanced by up to 22.8% on average. Keywords: Data centers, LTE-Advanced, Peak Age of Information, Channel Capacity, Header (Control) Packe

Diseño e implementación de una red de sensores inalámbricos definidos por software para el monitoreo de un sistema hidropónico NFT

Integrar las redes de sensores inalámbricos y las redes definidas por software mediante la implementación de un controlador SDN enfocado al cultivo hidropónico NFT.En la actualidad las redes de sensores inalámbricos forman parte del internet de las cosas, cuya tecnología es ampliamente investigada por diferentes empresas tecnologías con el propósito de mejorar el funcionamiento de las redes WSN, sin embargo, estas redes presentan limitaciones de hardware como la capacidad de procesamiento, ancho de banda reducido y consumo de energía, estos factores afectan al procesamiento y envío de la información. Ahora con base a este contexto, las redes definidas por software es una alternativa para mejorar las funcionalidades de las wsn debido a su principal característica, es que separar el plano de datos y control, por consiguiente, mejoraría el envío de datos, la escalabilidad y la administración de la red WSN debido a que mantiene un control centralizado a través del controlado SDN. Por medio, investigación bibliográfica se obtuvieron parámetros tales como: protocolos de comunicación, dispositivos, métricas de evaluación, tipo de arquitectura, etc. Estos parámetros ayudaron a determinar una propuesta que integre las dos tecnologías SDN y WSN, que mediante el apoyo de la metodología en cascada permite el despliegue y ejecución del sistema propuesta. La solución que se desarrolló en este trabajo está enfocada a la gestión de flujo de datos, donde se intenta aprovechar el direccionamiento IP local de las redes 6lowpan y el enrutamiento centralizado de las redes SDN, de manera que permita habilitar el flujo de datos por medio de políticas envidas por el controlador SDN. La implementación de las SDN dentro de una red WSN tiene sus beneficios, y así que, de la evaluación realizada se concluye que la gestión de datos a través de la aplicación permitió mejorar el tiempo de respuesta y la entrega de datos entre el servidor y nodo sensor como también contribuye de forma general a la seguridad de la red WSN.Ingenierí

Intent-based service management for heterogeneous software-defined infrastructure domains

One of the main challenges in delivering end-to-end service chains across multiple software-defined networking (SDN) and network function virtualization (NFV) domains is to achieve unified management and orchestration functions. A very critical aspect is the definition of an open, vendor-agnostic, and interoperable northbound interface (NBI) that should be as abstract as possible and decoupled from domain-specific data and control plane technologies. In this paper, we propose a reference architecture and an intent-based NBI for end-to-end service management across multiple technological domains. The general approach is tested in a heterogeneous OpenFlow/Internet-of-Things (IoT) SDN test bed, where the proposed solution is applied to a rather complex service provisioning scenario spanning three different technological domains: an IoT infrastructure deployment, a cloud-based data collection, processing, and publishing platform, and a transport domain over a geographic network interconnecting the IoT domain and the data center hosting the cloud services

Technologies for urban and rural internet of things

Nowadays, application domains such as smart cities, agriculture or intelligent transportation, require communication technologies that combine long transmission ranges and energy efficiency to fulfill a set of capabilities and constraints to rely on. In addition, in recent years, the interest in Unmanned Aerial Vehicles (UAVs) providing wireless connectivity in such scenarios is substantially increased thanks to their flexible deployment. The first chapters of this thesis deal with LoRaWAN and Narrowband-IoT (NB-IoT), which recent trends identify as the most promising Low Power Wide Area Networks technologies. While LoRaWAN is an open protocol that has gained a lot of interest thanks to its simplicity and energy efficiency, NB-IoT has been introduced from 3GPP as a radio access technology for massive machine-type communications inheriting legacy LTE characteristics. This thesis offers an overview of the two, comparing them in terms of selected performance indicators. In particular, LoRaWAN technology is assessed both via simulations and experiments, considering different network architectures and solutions to improve its performance (e.g., a new Adaptive Data Rate algorithm). NB-IoT is then introduced to identify which technology is more suitable depending on the application considered. The second part of the thesis introduces the use of UAVs as flying Base Stations, denoted as Unmanned Aerial Base Stations, (UABSs), which are considered as one of the key pillars of 6G to offer service for a number of applications. To this end, the performance of an NB-IoT network are assessed considering a UABS following predefined trajectories. Then, machine learning algorithms based on reinforcement learning and meta-learning are considered to optimize the trajectory as well as the radio resource management techniques the UABS may rely on in order to provide service considering both static (IoT sensors) and dynamic (vehicles) users. Finally, some experimental projects based on the technologies mentioned so far are presented