IoT@run-time: a model-based approach to support deployment and self-adaptations in IoT systems

Today, most Internet of Things (IoT) systems leverage edge and fog computing to meet increasingly restrictive requirements and improve quality of service (QoS). Although these multi-layer architectures can improve system performance, their design is challenging because the dynamic and changing IoT environment can impact the QoS and system operation. In this thesis, we propose a modeling-based approach that addresses the limitations of existing studies to support the design, deployment, and management of self-adaptive IoT systems. We have designed a domain specific language (DSL) to specify the self-adaptive IoT system, a code generator that generates YAML manifests for the deployment of the IoT system, and a framework based on the MAPE-K loop to monitor and adapt the IoT system at runtime. Finally, we have conducted several experimental studies to validate the expressiveness and usability of the DSL and to evaluate the ability and performance of our framework to address the growth of concurrent adaptations on an IoT system.Hoy en día, la mayoría de los sistemas de internet de las cosas (IoT, por su sigla en inglés) aprovechan la computación en el borde (edge computing) y la computación en la niebla (fog computing) para cumplir requisitos cada vez más restrictivos y mejorar la calidad del servicio. Aunque estas arquitecturas multicapa pueden mejorar el rendimiento del sistema, diseñarlas supone un reto debido a que el entorno de IoT dinámico y cambiante puede afectar a la calidad del servicio y al funcionamiento del sistema. En esta tesis proponemos un enfoque basado en el modelado que aborda las limitaciones de los estudios existentes para dar soporte en el diseño, el despliegue y la gestión de sistemas de IoT autoadaptables. Hemos diseñado un lenguaje de dominio específico (DSL) para modelar el sistema de IoT autoadaptable, un generador de código que produce manifiestos YAML para el despliegue del sistema de IoT y un marco basado en el bucle MAPE-K para monitorizar y adaptar el sistema de IoT en tiempo de ejecución. Por último, hemos llevado a cabo varios estudios experimentales para validar la expresividad y usabilidad del DSL y evaluar la capacidad y el rendimiento de nuestro marco para abordar el crecimiento de las adaptaciones concurrentes en un sistema de IoT.Avui dia, la majoria dels sistemes d'internet de les coses (IoT, per la sigla en anglès) aprofiten la informàtica a la perifèria (edge computing) i la informàtica a la boira (fog computing) per complir requisits cada cop més restrictius i millorar la qualitat del servei. Tot i que aquestes arquitectures multicapa poden millorar el rendiment del sistema, dissenyar-les suposa un repte perquè l'entorn d'IoT dinàmic i canviant pot afectar la qualitat del servei i el funcionament del sistema. En aquesta tesi proposem un enfocament basat en el modelatge que aborda les limitacions dels estudis existents per donar suport al disseny, el desplegament i la gestió de sistemes d'IoT autoadaptatius. Hem dissenyat un llenguatge de domini específic (DSL) per modelar el sistema d'IoT autoadaptatiu, un generador de codi que produeix manifestos YAML per al desplegament del sistema d'IoT i un marc basat en el bucle MAPE-K per monitorar i adaptar el sistema d'IoT en temps d'execució. Finalment, hem dut a terme diversos estudis experimentals per validar l'expressivitat i la usabilitat del DSL i avaluar la capacitat i el rendiment del nostre marc per abordar el creixement de les adaptacions concurrents en un sistema d'IoT.Tecnologies de la informació i de xarxe

Reactive Microservices - An Experiment

Os microserviços são geralmente adotados quando a escalabilidade e flexibilidade de uma aplicação são essenciais para o seu sucesso. Apesar disto, as dependências entre serviços transmitidos através de protocolos síncronos, resultam numa única falha que pode afetar múltiplos microserviços. A adoção da capacidade de resposta numa arquitetura baseada em microserviços, através da reatividade, pode facilitar e minimizar a proliferação de erros entre serviços e na comunicação entre eles, ao dar prioridade à capacidade de resposta e à resiliência de um serviço. Esta dissertação fornece uma visão geral do estado da arte dos microserviços reativos, estruturada através de um processo de mapeamento sistemático, onde são analisados os seus atributos de qualidade mais importantes, os seus erros mais comuns, as métricas mais adequadas para a sua avaliação, e as frameworks mais relevantes. Com a informação recolhida, é apresentado o valor deste trabalho, onde a decisão do projeto e a framework a utilizar são tomadas, através da técnica de preferência de ordem por semelhança com a solução ideal e o processo de hierarquia analítica, respetivamente. Em seguida, é realizada a análise e o desenho da solução, para o respetivo projeto, onde se destacam as alterações arquiteturais necessárias para o converter num projeto de microserviços reativo. Em seguida, descreve-se a implementação da solução, começando pela configuração do projeto necessária para agilizar o processo de desenvolvimento, seguida dos principais detalhes de implementação utilizados para assegurar a reatividade e como a framework apoia e simplifica a sua implementação, finalizada pela configuração das ferramentas de métricas no projeto para apoiar os testes e a avaliação da solução. Em seguida, a validação da solução é investigada e executada com base na abordagem Goals, Questions, Metrics (GQM), para estruturar a sua análise relativamente à manutenção, escalabilidade, desempenho, testabilidade, disponibilidade, monitorabilidade e segurança, finalizada pela conclusão do trabalho global realizado, onde são listadas as contribuições, ameaças à validade e possíveis trabalhos futuros.Microservices are generally adopted when the scalability and flexibility of an application are essential to its success. Despite this, dependencies between services transmitted through synchronous protocols result in one failure, potentially affecting multiple microservices. The adoption of responsiveness in a microservices-based architecture, through reactivity, can facilitate and minimize the proliferation of errors between services and in the communication between them by prioritizing the responsiveness and resilience of a service. This dissertation provides an overview of the reactive microservices state of the art, structured through a systematic mapping process, where its most important quality attributes, pitfalls, metrics, and most relevant frameworks are analysed. With the gathered information, the value of this work is presented, where the project and framework decision are made through the technique of order preference by similarity to the ideal solution and the analytic hierarchy process, respectively. Then, the analysis and design of the solution are idealized for the respective project, where the necessary architectural changes are highlighted to convert it to a reactive microservices project. Next, the solution implementation is described, starting with the necessary project setup to speed up the development process, followed by the key implementation details employed to ensure reactivity and how the framework streamlines its implementation, finalized by the metrics tools setup in the project to support the testing and evaluation of the solution. Then, the solution validation is traced and executed based on the Goals, Questions, Metrics (GQM) approach to structure its analysis regarding maintainability, scalability, performance, testability, availability, monitorability, and security, finalized by the conclusion of the overall work done, where the contributions, threats to validity and possible future work are listed

Serverless computing for the Internet of Things

Cloud-based services have evolved significantly over the years. Cloud computing models such as IaaS, PaaS and SaaS are serving as an alternative to traditional in-house infrastructure-based approach. Furthermore, serverless computing is a cloud computing model for ephemeral, stateless and event-driven applications that scale up and down instantly. In contrast to the infinite resources of cloud computing, the Internet of Things is the network of resource-constrained, heterogeneous and intelligent devices that generate a significant amount of data. Due to the resource-constrained nature of IoT devices, cloud resources are used to process data generated by IoT devices. However, data processing in the cloud also has few limitations such as latency and privacy concerns. These limitations arise a requirement of local processing of data generated by IoT devices. A serverless platform can be deployed on a cluster of IoT devices using software containers to enable local processing of the sensor data. This work proposes a hybrid multi-layered architecture that not only establishes the possibility of local processing of sensor data but also considers the issues such as heterogeneity, resource constraint nature of IoT devices. We use software containers, and multi-layered architecture to provide the high availability and fault tolerance in our proposed solution

Remote biometrical monitoring system via IoT

Os sistemas de Internet of Things (IoT) estão a experienciar um rápido crescimento devido à sua aplicabilidade em vários domínios, desde cidades inteligentes até aos cuidados de saúde. Nestes sistemas, os dispositivos comunicam entre si, ou com a infraestrutura, recorrendo a comunicações machine-to-machine (M2M). Uma vez que muitos destes dispositivos são simples, com escassa capacidade de processamento, foram desenvolvidos protocolos M2M como o Constrained Application Protocol (CoAP) e o Messaging Queue Telemetry Transport (MQTT), bem como frameworks de suporte de comunicações M2M. Apesar dos desenvolvimentos nesta tecnologia, ainda são encontrados desafios no desenvolvimento de aplicações M2M e IoT a nível da interoperabilidade, escalabilidade e padronização, por exemplo. Consequentemente, vários standards M2M foram desenvolvidos para superar estes desafios, sendo o oneM2M um deles. Atualmente, existem vários dispositivos disponíveis com uma interface WiFi embebida, o que significa que quando inseridos num sistema IoT, não necessitam de uma gateway (GW) para o acesso à Internet, uma vez que o WiFi é uma tecnologia omnipresente na sociedade atual. Esta é uma característica fundamental visto que diminui o custo global do sistema. Além disso, estes dipositivos, como o módulo ESP32, oferecem modos de poupança de energia que permitem explorar recursos de gestão de energia definidos pelo standard IEEE 802.11. As instituições de cuidados de saúde procuram oferecer os melhores serviços em termos de confiabilidade, segurança e conforto aos seus pacientes. Recentemente, tecnologias IoT foram abordadas, desenvolvidas e utilizadas para melhorar o serviço aos pacientes. O trabalho proposto nesta dissertação é um sistema de monitorização contínua via IoT capaz de monitorizar os sinais vitais de um paciente e apresentá-los aos profissionais de saúde. Para além disso, o sistema pode ser utilizado em diversos cenários desde salas de emergência, uso doméstico até à competição desportiva. O sistema possui dois componentes principais: um dispositivo wearable com uma antena WiFi e um sistema de monitorização orientado ao profissional de saúde. O wearable é composto por um sensor fotopletismográfico (PPG) MAX30100/MAX30102 para medir o ritmo cardíaco e os níveis de saturação de oxigénio no sangue, um ESP32 com uma antena WiFi incorporada para processar e enviar os dados do sensor para o sistema de monitorização e, finalmente, uma bateria de Lítio Polímero (LiPo) para fornecer energia aos dois componentes mencionados. No que refere ao sistema de monitorização, este é composto por uma base de dados orientada a eventos temporais para armazenar todos os dados necessários, um software de visualização gráfica para a visualização dos sinais vitais do paciente e, por fim, uma Interface Gráfica com o objetivo de ser um painel de controlo para todo o sistema. Para além disso, o sistema segue a norma oneM2M devido a questões de interoperabilidade relativas à arquitetura, e implementa o modelo de comunicação publisher-subscriber pois este é eficiente em termos de sensorização e monitorização remota. Por último, o objetivo desta dissertação é desenvolver um sistema de monitorização de baixo custo focado na gestão energética e que ao mesmo tempo não comprometa a sua confiabilidade e robustez.Internet of Things (IoT) systems are experiencing rapid growth due to their applicability in several domains, from smart cities to healthcare among many. In these systems, devices communicate with each other, or with infrastructure, resorting to machine-to-machine (M2M) communications. Since many of these devices are simple systems, with weak processing capacity, lightweight M2M protocols were developed such as Constrained Application Protocol (CoAP) and Messaging Queue Telemetry Transport (MQTT) as well as frameworks to support M2M communications. As expected, there are challenges when developing M2M and IoT applications: interoperability, scalability, standardisation, among others. Therefore, several M2M standards were created to overcome these issues, with oneM2M being one of them. Nowadays, there are multiple devices available that have an embedded WiFi interface, thus, when inserted in an IoT system, these devices do not need a gateway (GW) to access the Internet since WiFi is one of the most common technologies at Internet boundary. This is a key feature because it increases the system's pervasiveness as well as the overall cost of the system. Additionally, these devices, such as the ESP32 module, offer sleep modes that allow exploiting the power management features by the IEEE 802.11 standard. Healthcare institutions always strive to provide the best services concerning the reliability, safety and comfort of the patients. To do so, IoT technologies have been embraced and developed in recent years to improve these services. The work proposed in this dissertation is an end-to-end continuous monitoring system via IoT capable of monitoring a patient's vital signs and displaying them to the medical personnel. Moreover, the system can be applied to a wide range of application scenarios from emergency wards and home environment to sports training and competition. The system has two major components, a low-cost and low-power WiFi-enabled wearable device for the user and, at the upper end, a monitoring interface for the medical personnel. The wearable is composed by a MAX30100/MAX30102 PhotoPletysmoGraphy (PPG) sensor to measure the heart rate and oxygen saturation levels, an ESP32 with a built-in WiFi antenna to process and send the sensor data to the monitoring system and, finally, a Lithium Polymer (LiPo) battery to power-up the previous two components. At the upper end, the monitoring interface is composed of a time-series database to store all the data, a graphics visualisation software of patient's vital signs and a Graphic User Interface (GUI) serving as a control panel. Additionally, the system relies on the oneM2M standard for the interoperability concerning the architecture and follows a publish-subscribe communication model due to its efficiency in sensing and remote monitoring. Furthermore, the goal of this dissertation is to develop a low-cost and energy-efficient monitoring system while not compromising the reliability and robustness of traditional machines and systems

Agent-oriented software engineering methodologies : analysis and future directions

The Internet of Things (IoT) facilitates in building cyber-physical systems, which are significant for Industry 4.0. Agent-based computing represents effective modeling, programming, and simulation paradigm to develop IoT systems. Agent concepts, techniques, methods, and tools are being used in evolving IoT systems. Over the last years, in particular, there has been an increasing number of agent approaches proposed along with an ever-growing interest in their various implementations. Yet a comprehensive and full-fledged agent approach for developing related projects is still lacking despite the presence of agent-oriented software engineering (AOSE) methodologies. One of the moves towards compensating for this issue is to compile various available methodologies, ones that are comparable to the evolution of the unified modeling language (UML) in the domain of object-oriented analysis and design. These have become de facto standards in software development. In line with this objective, the present research attempts to comprehend the relationship among seven main AOSE methodologies. More specifically, we intend to assess and compare these seven approaches by conducting a feature analysis through examining the advantages and limitations of each competing process, structural analysis, and a case study evaluation method. This effort is made to address the significant characteristics of AOSE approaches. The main objective of this study is to conduct a comprehensive analysis of selected AOSE methodologies and provide a proposal of a draft unified approach that drives strengths (best) of these methodologies towards advancement in this area.publishedVersio

An agent based approach for improvised explosive device detection, public alertness and safety

One of the security challenges faced by our contemporary world is terror threats and attacks, and this is no doubt posing potential threats to lives, properties and businesses all around us; affecting the way we live and also travel. Terror attacks have been perpetrated in diverse ways whether from organized terror networks through coordinated attacks or by some lone individuals such that it is now a major concern to people and government. Indeed, there are numerous forms of terror attacks. In this proposal, we look at how the explosive substance kind of threats can be perceived and taken care of prior to potential attacks using intelligent agent systems requirement analysis. Thus, the paper demonstrates using an agent-oriented system analysis and design methodology to decompose. Through defined percepts, goals and plans, agents possess capabilities to observe and perform actions. This proposal demonstrates: how agents can be situated in our cities, goal refinement for agents in the detection and rescue of potential terror attacks, and inter-agent communication for the prevention of chemical terror attack

Tram-tastic Cloud Computing

This master’s thesis evaluates the scalability and cost-effectiveness of the AWS cloud platform used to collect and utilize data generated by the 87 digitally equipped trams. The SL-18 Cloud Platform was developed before the trams arrived, and resource configuration estimates were made to handle the data generated by the trams. However, with a few trams currently operational, it is crucial to evaluate the allocation of resources to the services based on actual data. Thus, the thesis's objective is to estimate the data generated by all 87 trams and evaluate the current resource provisioning on the AWS Cloud Platform in terms of scalability and cost. By doing so, this study will provide insights into the optimal resource allocation required for the AWS Cloud Platform to accommodate the data generated by the trams. In this study, we use an existing Digital Twin tool for the trams to evaluate the scalability of the platform, ensuring that it can handle the load while keeping the cost low. To achieve this, the existing Digital Twin is modified to run 87 or more instances concurrently. Using this modified tool, the SL-18 IT platform, which processes real-time data from all 87 trams simultaneously, is evaluated. We monitored the metrics of AWS services to identify any issues. Then based on measurements, we make recommendations for each service's upgrading, downgrading, or keeping the current configuration. Most services are recommended to scale down to reduce costs, while three services require scaling up to be operational. Although our process is well-defined and could be replicated by other studies, it is crucial to have in-depth discussions with the relevant teams for each service and perform repeated validations and evaluations. This is also a necessary protocol in Sporveien to present the results to the various stakeholders and implement the recommended changes. With these changes, Sporveien can save costs and most importantly have a platform capable of handling the data load of 87 SL-18 trams

Hybrid clouds for data-Intensive, 5G-Enabled IoT applications: an overview, key issues and relevant architecture

Hybrid cloud multi-access edge computing (MEC) deployments have been proposed as efficient means to support Internet of Things (IoT) applications, relying on a plethora of nodes and data. In this paper, an overview on the area of hybrid clouds considering relevant research areas is given, providing technologies and mechanisms for the formation of such MEC deployments, as well as emphasizing several key issues that should be tackled by novel approaches, especially under the 5G paradigm. Furthermore, a decentralized hybrid cloud MEC architecture, resulting in a Platform-as-a-Service (PaaS) is proposed and its main building blocks and layers are thoroughly described. Aiming to offer a broad perspective on the business potential of such a platform, the stakeholder ecosystem is also analyzed. Finally, two use cases in the context of smart cities and mobile health are presented, aimed at showing how the proposed PaaS enables the development of respective IoT applications.Peer ReviewedPostprint (published version