Enabling the orchestration of IoT slices through edge and cloud microservice platforms

This article addresses one of the main challenges related to the practical deployment of Internet of Things (IoT) solutions: the coordinated operation of entities at different infrastructures to support the automated orchestration of end-to-end Internet of Things services. This idea is referred to as "Internet of Things slicing" and is based on the network slicing concept already defined for the Fifth Generation (5G) of mobile networks. In this context, we present the architectural design of a slice orchestrator addressing the aforementioned challenge, based on well-known standard technologies and protocols. The proposed solution is able to integrate existing technologies, like cloud computing, with other more recent technologies like edge computing and network slicing. In addition, a functional prototype of the proposed orchestrator has been implemented, using open-source software and microservice platforms. As a first step to prove the practical feasibility of our solution, the implementation of the orchestrator considers cloud and edge domains. The validation results obtained from the prototype prove the feasibility of the solution from a functional perspective, verifying its capacity to deploy Internet of Things related functions even on resource constrained platforms. This approach enables new application models where these Internet of Things related functions can be onboarded on small unmanned aerial vehicles, offering a flexible and cost-effective solution to deploy these functions at the network edge. In addition, this proposal can also be used on commercial cloud platforms, like the Google Compute Engine, showing that it can take advantage of the benefits of edge and cloud computing respectivelyThe work of Ivan Vidal and Francisco Valera was partially supported by the European H2020 5GinFIRE project (grant agreement 732497), and by the 5GCity project (TEC2016-76795-C6-3-R) funded by the Spanish Ministry of Economy and Competitiveness

A microservices-based control plane for time sensitive networking

Time-Sensitive Networking (TSN) is a group of IEEE 802.1 standards that aim at providing deterministic communications over IEEE Ethernet. The main characteristics of TSN are low bounded latency and very high reliability, which complies with the strict requirements of industry and automotive applications. In this context, allocating time slots, configuration paths, and Gate Control Lists (GCLs) to contending TSN streams is often laborious. Software-Defined Networking (SDN) and the IEEE 802.1 Qcc standard provide the basis to design a TSN control plane to face these challenges. However, current SDN/TSN control plane solutions are monolithic applications designed to run on dedicated servers. None of them explores Microservice as a design pattern; these SDN controllers do not provide the required flexibility to escalate when facing increasing service requests. This work presents $\mu$TSN-CP, a microservices-based Control Plane (CP) architecture for TSN/SDN that provides superior scalability in situations with highly dynamic service demands. Using a qualitative approach, we evaluate our $\mu$TSN-CP solution compared to a monolithic solution in terms of CPU usage, RAM usage, latency, and percentage of successfully allocated TSN Streams. Our $\mu$TSN-CP architecture leverages the advantages of microservices, enabling the control plane to scale up or down in response to varying workloads dynamically. We achieve enhanced flexibility and resilience by breaking down the control plane into smaller, independent microservices. The experimental evaluation demonstrates that our TSN-CP outperforms the monolithic solution, with significantly lower CPU and RAM usage, reduced latency, and a higher percentage of successfully allocated TSN Streams. This advancement in TSN/SDN control plane design opens up new possibilities for highly scalable and adaptable networks, catering to the ever-increasing demands of time-sensitive applications in various industries.Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructur

Adapting Microservices in the Cloud with FaaS

This project involves benchmarking, microservices and Function-as-a-service (FaaS) across the dimensions of performance and cost. In order to do a comparison this paper proposes a benchmark framework

Orchestrated Platform for Cyber-Physical Systems

One of the main driving forces in the era of cyber-physical systems (CPSs) is the introduction of massive sensor networks (or nowadays various Internet of things solutions as well) into manufacturing processes, connected cars, precision agriculture, and so on. Therefore, large amounts of sensor data have to be ingested at the server side in order to generate and make the "twin digital model" or virtual factory of the existing physical processes for (among others) predictive simulation and scheduling purposes usable. In this paper, we focus on our ultimate goal, a novel software container-based approach with cloud agnostic orchestration facilities that enable the system operators in the industry to create and manage scalable, virtual IT platforms on-demand for these two typical major pillars of CPS: (1) server-side (i.e., back-end) framework for sensor networks and (2) configurable simulation tool for predicting the behavior of manufacturing systems. The paper discusses the scalability of the applied discrete-event simulation tool and the layered back-end framework starting from simple virtual machine-level to sophisticated multilevel autoscaling use case scenario. The presented achievements and evaluations leverage on (among others) the synergy of the existing EasySim simulator, our new CQueue software container manager, the continuously developed Octopus cloud orchestrator tool, and the latest version of the evolving MiCADO framework for integrating such tools into a unified platform

A WiFi-Based Sensor Network for Flood Irrigation Control in Agriculture

The role of agriculture in society is vital due to factors such as providing food for the population, is a major source of employment worldwide, and one of the most important sources of revenue for countries. Furthermore, in recent years, the interest in optimizing the use of water resources has increased due to aspects such as climate change. This has led to the introduction of technology in the fields by means of sensor networks that allow remote monitoring and control of cultivated lands. In this paper, we present a system for flood irrigation in agriculture comprised of a sensor network based on WiFi communication. Different sensors measure atmospheric parameters such as temperature, humidity, and rain, soil parameters such as humidity, and water parameters such as water temperature, salinity, and water height to decide on the need of activating the floodgates for irrigation. The user application displays the data gathered by the sensors, shows a graphical representation of the state of irrigation of each ditch, and allows farmers to manage the irrigation of their fields. Finally, different tests were performed on a plot of vegetables to evaluate the correct performance of the system and the coverage of the sensor network on a vegetated area with different deployment options.European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) project ERANETMED3- 227 SMARTWATIR, by the “Programa Estatal de I+D+i Orientada a los Retos de la Sociedad, en el marco del Plan Estatal de Investigación Científica y Técnica y de Innovación 2017–2020” (Project code: PID2020-114467RR-C33)“Proyectos de innovación de interés general por grupos operativos de la Asociación Europea para la Innovación en materia de productividad y sostenibilidad agrícolas (AEI-Agri)” in the framework “Programa Nacional de Desarrollo Rural 2014–2020”, GO TECNOGAR.Universitat Politècnica de València through the post-doctoral PAID-10-20 progra