Implementation of a platform for analysis and visualization of IoT multi-protocol data in real time on Node-Red

RESUMEN: Los retos que presentan las tecnologías de la Internet de las Cosas (IoT) se incrementan según se incorporan nuevas tecnologías a un ecosistema tremendamente heterogéneo y fragmentado. Cada vez más, los desarrolladores de soluciones deben tratar no solo con la propia lógica de negocio de sus servicios inteligentes basados en la capacidad de medida y monitorización de fenómenos, sino que deben tener una comprensión multidisciplinar dentro del ámbito de la IoT. Desarrollar un sistema extremo-a-extremo donde toman parte sensores, redes inalámbricas, pasarelas (gateway), servidores y la monitorización es extremadamente complejo. Esto hace necesario plantear un sistema fácil y de rápido despliegue para recibir la información de los sensores, almacenarla y visualizarla. Por lo tanto, este Trabajo de Fin de Grado (TFG) pretende desarrollar un sistema de programación visual del lado del servidor que reciba la información de sensores y plataformas IoT heterogéneas, la almacene en una base de datos y la visualice. En particular, se utilizarán diferentes fuentes de datos que provienen de sensores que utilizan cuatro plataformas de gestión de la información IoT distintas. Estos datos se enviarán sobre diferentes protocolos de aplicación y el servidor desplegado usando Node-RED recibirá todos los datos. También se almacenarán los datos en InuxDB a corto o medio plazo, y se utilizará MongoDB como base de datos histórica, para después mostrarse en Grafana usando tableros dinámicos. Los conceptos anteriormente mencionados se validan comprobando el transporte de datos extremo-a-extremo, así como se comprueba el almacenamiento a corto y largo plazo y su visualización dinámica. Se confirma, por lo tanto, que es posible desplegar una red completa de aplicaciones basadas en contenedores en pocos segundos, para ofrecer un entorno de programación visual así como almacenamiento y visualización.ABSTRACT: The more Internet-of-Things (IoT) technologies advance, the more considerable challenges appear. Current IoT developers do not limit themselves to develop a tiny part of sensor and phenomena monitoring services. It is necessary to incorporate a multidisciplinary understanding of all IoT areas. It is challenging to develop an end-to-end system that incorporates sensors, wireless networks, gateways, servers, and a visualization scheme. This fact requires new and easy deployment techniques in order to collect, store and visualize sensor information. Therefore, this thesis pretends to develop and implement a visual programming system that receives, stores and visualizes measurements directly sent from sensors or proxies. In particular, different data sources will be used, which belong to sensors that employ four different IoT data management platforms to handle their observations. The data generated by these sensors will ultimately be sent using different application layer protocols. Still, the server deployed using Node-RED will be able to process it. Data will also be stored in an InuxDB database for the short or medium term, while MongoDB is used as a historical database. Grafana later queries the data stored at InuxDB to show the information received by the server using dynamic dashboards at runtime. The concepts aforementioned will eventually be validated, verifying the end-to-end data transport and checking that data is appropriately stored in short and long-term databases, ultimately using dynamic means of visualization. The thesis demonstrates that it is possible to deploy a complete container-based scenario in a few seconds to offer a visual programming environment, storage, and visualization capabilities.Grado en Ingeniería de Tecnologías de Telecomunicació

Detection of Fog Network Data Telemetry Using Data Plane Programming

Fog computing has been introduced to deliver Cloud-based services to the Internet of Things (IoT) devices. It locates geographically closer to IoT devices than Cloud networks and aims at offering latency-critical computation and storage to end-user applications. To leverage Fog computing for computational offloading from end-users, it is important to optimize resources in the Fog nodes dynamically. Provisioning requires knowledge of the current network state, thus, monitoring mechanisms play a significant role to conduct resource management in the network. To keep track of the state of devices, we use P4, a data-plane programming language, to describe data-plane abstraction of Fog network devices and collect telemetry without the intervention of the control plane or adding a big amount of overhead. In this paper, we propose a software-defined architecture with a programmable data plane for data telemetry detection that can be integrated into Fog network resource management. After the implementation of detecting data telemetry based on In-Band Network Telemetry (INT) within a Mininet simulation, we show the available features and preliminary Fog resource management based on the collected data telemetry and future telemetry-based traffic engineering possibilities

Next-Generation SDN and Fog Computing: A New Paradigm for SDN-Based Edge Computing

In the last few years, we have been able to see how terms like Mobile Edge Computing, Cloudlets, and Fog computing have arisen as concepts that reach a level of popularity to express computing towards network Edge. Shifting some processing tasks from the Cloud to the Edge brings challenges to the table that might have been non-considered before in next-generation Software-Defined Networking (SDN). Efficient routing mechanisms, Edge Computing, and SDN applications are challenging to deploy as controllers are expected to have different distributions. In particular, with the advances of SDN and the P4 language, there are new opportunities and challenges that next-generation SDN has for Fog computing. The development of new pipelines along with the progress regarding control-to-data plane programming protocols can also promote data and control plane function offloading. We propose a new mechanism of deploying SDN control planes both locally and remotely to attend different challenges. We encourage researchers to develop new ways to functionally deploying Fog and Cloud control planes that let cross-layer planes interact by deploying specific control and data plane applications. With our proposal, the control and data plane distribution can provide a lower response time for locally deployed applications (local control plane). Besides, it can still be beneficial for a centralized and remotely placed control plane, for applications such as path computation within the same network and between separated networks (remote control plane)

Towards visual programming abstractions in Software Defined Networking

Since Software-Defined Networking (SDN) emerged, the research community and industry have developed numerous projects and fostered novel use cases. However, engineers now need to learn how to program the control and data planes, which might slow down technology acceptance. To accelerate it, visual programming abstractions facilitate the incorporation of SDN technologies and assist in creating new applications. So far, very little effort has been made in this field. This letter presents an early-stage SDN visual abstraction initiative based on the Scratch/Blockly programming framework, initially aimed at kids. The objective is to illustrate how this work could be extended to provide value-added resources for network programming