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The Internet of Things (IoT) is the latest trend of the current ICT evolution, represented by a huge amount of powerful smart devices that have started to appear on the Internet. By responding to this new trend, many cloud providers have started to offer services for IoT management. Recent advances have already shown that cloud computing can be use...
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... No entanto, a complexidade na modelagem de cenários dinâmicos e heterogêneos foi identificada como uma limitação importante. Já os trabalhos de Kertész et al. 2019e Del-Pozo-Puñal et al. 2023 se destacam ao apresentar simuladores que integram computação em névoa e nuvem com suporte para mobilidade em aplicações sensíveisà latência. As soluções são eficazes na gestão de dispositivos IoT móveis, mas enfrentam desafios na simulação de interações em tempo real entre dispositivos e recursos distribuídos. ...
O avanço das tecnologias de Internet das Coisas (Intelligence of Things – IoT) e Inteligência Artificial (IA) abriu novas possibilidades de aplicações em diversas áreas, incluindo monitoramento em tempo real. Este trabalho apresenta o desenvolvimento de um simulador de aplicações de Inteligência Artificial das Coisas (Artificial Intelligence of Things – AIoT) para monitoramento de áreas rurais utilizando Veículos Aéreos Não Tripulados (VANTs). A proposta integra uma arquitetura edge/fog/cloud, onde VANTs equipados com câmeras e algoritmos de IA realizam a detecção de animais em tempo real. O sistema distribui a carga de processamento entre os dispositivos de borda e o servidor fog, otimizando a eficiência e a precisão das detecções. A interface gráfica desenvolvida permite a visualização e gerenciamento de simulações, facilitando a análise e a tomada de decisões. Os resultados demonstram a viabilidade e eficácia do sistema para monitoramento de ambientes de difícil acesso, contribuindo para uma gestão eficiente de recursos e resposta rápida a eventos da aplicação.
... OPNET, desarrollado por OPNET Technology Corporation, permite el análisis detallado de redes informáticas y de comunicación, soportando múltiples protocolos como VoIP y IPv6 (Nie & Hu, 2019). Boson Netsim, aunque con una curva de aprendizaje larga, ofrece virtualización de routers, switches y protocolos de comunicación en entornos de capacitación virtual (Podsadnikov et al., 2021;Kertesz et al., 2019). ...
Este estudio compara el simulador Cisco Packet Tracer y el emulador GNS3 en la implementación de la topología HSRP para prácticas de redes de computadoras en entornos de laboratorio. El objetivo es determinar cuál herramienta es más adecuada para estudiantes universitarios. El estudio se estructura en cinco fases: búsqueda de información, selección de herramientas, configuración de la topología, implementación en simulador y emulador, y evaluación según parámetros clave. Los resultados indican que ambos sistemas son eficaces en la configuración y el envío de paquetes, pero difieren significativamente en usabilidad, consumo de recursos y licenciamiento. Se concluye que Cisco Packet Tracer es más accesible para principiantes debido a su interfaz intuitiva y bajo requerimiento de recursos, mientras que GNS3 ofrece flexibilidad avanzada y control detallado sobre configuraciones de red más complejas. Esta investigación proporciona una guía práctica para educadores y estudiantes al seleccionar la herramienta más apropiada según las necesidades específicas del curso y los objetivos de aprendizaje.
... In recent years, IoT and edge, fog, and cloud computing technologies have been developed to store, analyze, and monitor data quickly and stably. Research is being actively conducted on various methods for monitoring patient conditions using such technologies [20][21][22]. For example, IoT-based smart healthcare systems collect patient information from various sensors and medical equipment to enable medical practitioners to monitor patients' conditions in real time. ...
Edge computing can provide core functions such as data collection and analysis without connecting to a centralized server. The convergence of edge computing and IoT devices has enabled medical institutions to collect patient data in real time, improving the efficiency of short- and long-term patient management. Medical equipment measures a large amount of biosignal data for analyzing diseases and patient health conditions. However, analyzing and monitoring biosignal data using a centralized server or cloud limit the medical institutions’ ability to analyze patients’ conditions in real time, preventing prompt treatment. Therefore, edge computing can enhance the efficiency of patient biosignal data collection and analysis for patient management systems. Analyzing biosignals using edge computing can eliminate the wait time present in cloud computing. Hence, this study aims to develop an IoT pulse oximeter using edge computing for medical institutions and proposes an architecture for providing a real-time monitoring service. The proposed system utilizes five types of raw (IR AC, IR DC, red AC, red DC, AMB), pulse, and SpO2 data measured using IoT pulse oximeters. Edge nodes are installed in every hospital ward to collect, analyze, and monitor patient biosignal data through a wireless network. The collected biosignal data are transmitted to the cloud for managing and monitoring the data of all patients. This system enables medical institutions to collect and analyze raw biosignal data in real time, by which an integrated management system can be established by connecting various types of IoT-based medical equipment.
... In recent years, IoT and edge, fog, and cloud computing technologies have been developed to store, analyze, and monitor data quickly and stably. Research is actively being conducted on various methods for monitoring patient conditions using such technologies [15][16][17]. For example, IoT-based smart healthcare systems collect patient information from various sensors and medical equipment to enable medical practitioners to monitor patients' conditions in real time. ...
Edge computing can provide core functions such as data collection and analysis without connecting to a centralized server. The convergence of edge computing and IoT devices has enabled medical institutions to collect patient data in real-time, which improved the efficiency of short- and long-term patient management. Medical equipment measures a large amount of biosignal data for analyzing diseases and patient health conditions. However, analyzing and monitoring biosignal data using a centralized server or cloud limit the medical institutions’ ability to analyze patients’ conditions in real time, preventing prompt treatment. Therefore, edge computing can enhance the efficiency of patient biosignal data collection and analysis for patient management systems. Analyzing biosignals using edge computing can eliminate the waiting time present in cloud computing. Hence, this study aims to develop an IoT pulse oximeter to use edge computing at medical institutions and proposes an architecture for providing a real-time monitoring service. The proposed system utilizes five types of raw (IR AC, IR DC, red AC, red DC, AMB), pulse, and SpO2 data measured using IoT pulse oximeters. Edge nodes are installed at every ward to collect, analyze, and monitor patient biosignal data through a wireless network. The collected biosignal data are transmitted to the cloud for managing and monitoring the data of all patients. This system enables medical institutions to collect and analyze raw biosignal data in real time, where an integrated management system can be established by connecting various IoT-based medical equipment.
... In this sense, there is a need for the development of frameworks that fill the gap between analytical evaluation and planning, and the evaluation of the expected performance under controlled environments. There are some related works where three tier architecture platforms have been developed such as [22], [23] and [24], but they had some limitations for our purposes. Hence, we decide to develop our own framework tailored for the analysis of computation sharing/offloading in fog/cloud environments. ...
We introduce offloading policies for fog-cloud architectures that consider different performance parameters. We design and develop a three-tier platform, using virtualization techniques, which can be used to deploy different scenarios, with nodes having different features, mimicking fog and cloud characteristics. We then exploit Lyapunov control theory to introduce offloading policies that balance energy consumption at fog nodes and monetary cost of using the cloud. The proposed scheme is able to find a trade-off between these two parameters, while ensuring system stability and so delay requirements. We compare our algorithm with baseline solutions (Round-Robin), and the results evince that it is able to yield a better performance, even under high loads and stringent energy requirements. By tweaking the algorithm operational parameters, we show that it is able to adapt its behavior to different goals, and we assess its performance under realistic configurations.
... The Internet of Things is a new concept in the world of information and communication technology [14,26]. In short, it is a modern technology in which it provides the ability for any creature (human, animal, or object) to send and receive data through communication networks, including the Internet or intranet [18,27]. ...
... After receiving the values, the first cluster head should reconstruct CK using the obtained corresponding {T i , X, EXP_Time} from the database. Then it computes P ′ 2 according to (14) and compares it with the received P 2 according to (15) If these two values not equal, the first cluster head is declared illegal, and the session ends. Otherwise, the first cluster head is authenticated. ...
Internet of Things (IoT) means connecting different devices through the Internet. The Internet of things enables humans to remotely manage and control the objects they use with the Internet infrastructure. After the advent of the Internet of Things in homes, organizations, and private companies, privacy and information security are the biggest concern. This issue has challenged the spread of the Internet of things as news of the user’s theft of information by hackers intensified. The proposed method in this paper consists of three phases. In the first phase, a star structure is constructed within each cluster, and a unique key is shared between each child and parent to encrypt and secure subsequent communications. The second phase is for intra-cluster communications, in which members of the cluster send their data to the cluster head in a multi-hop manner. Also, in this phase, the data is encrypted with different keys in each hop, and at the end of each connection, the keys are updated to ensure data security. The third phase is to improve the security of inter-cluster communications using an authentication protocol. In this way, the cluster heads are authenticated before sending information to prevent malicious nodes in the network. The proposed method is also simulated using NS2 software. The results showed that the proposed method has improved in terms of energy consumption, end-to-end delay, flexibility, packet delivery rate, and the number of alive nodes compared to other methods.
... IoT is already pervasive in several application domains, e.g., emergency response, smart cities, smart agriculture and autonomous vehicles, to name a few. IoT simulation has numerous facets, including simulation of IoT sensors and actuators [3,26,52], simulation of IoT edge devices [25,47] and simulation of IoT networks [4,14,27,36]. Our work in this paper focuses on simulating edge devices and their interactions with cloud applications. ...
The Internet of things (IoT) is increasingly prevalent in domains such as emergency response, smart cities and autonomous vehicles. Simulation plays a key role in the testing of IoT systems, noting that field testing of a complete IoT product may be infeasible or prohibitively expensive. In this paper, we propose a domain-specific language (DSL) for generating edge-to-cloud simulators. An edge-to-cloud simulator executes the functionality of a large array of edge devices that communicate with cloud applications. Our DSL, named IoTECS, is the result of a collaborative project with an IoT analytics company, Cheetah Networks. The industrial use case that motivates IoTECS is ensuring the scalability of cloud applications by putting them under extreme loads from IoT devices connected to the edge. We implement IoTECS using Xtext and empirically evaluate its usefulness. We further reflect on the lessons learned.
... Diverse application domains have been tackled by IoT log generators like mobile devices, wireless sensor networks or cyberphysical systems. For instance, Kertestz et al. [13] propose a simulator for the cloud communication of mobile IoT devices' sensor data. Papadoupolos et al. [15] addressed signal strength of wireless sensor networks. ...
Process mining has gained significant practical usefulness in diverse domains. The input of process mining is an event log, tracking the execution of activities that can be mapped onto a business processes. Thus, the availability and quality of event logs significantly impact the process mining result. The use of process mining in novel use cases or experimental settings is often hampered because no appropriate event logs are available. This paper presents a tool to generate synthetic (sensor) event logs. Compared to existing synthetic log generator tools, the IoT process log generator produces data in a non-deterministic way. Users can add noise in a controlled manner and might enhance the processes with IoT data. In this way, the tool allows generating synthetic data for IoT environments that can be individually configured. Our tool makes a contribution towards an increased use of process mining in settings relying on (IoT) sensor event data.
KeywordsInternet of thingsEvent log simulationSynthetic dataBusiness process simulationProcess mining
... Diverse application domains have been tackled by IoT log generators like mobile devices, wireless sensor networks or cyberphysical systems. For instance, Kertestz et al. [13] propose a simulator for the cloud communication of mobile IoT devices' sensor data. Papadoupolos et al. [15] addressed signal strength of wireless sensor networks. ...
Process mining has gained significant practical usefulness in diverse domains. The input of process mining is an event log, tracking the execution of activities that can be mapped onto a business processes. Thus, the availability and quality of event logs significantly impact the process mining result. The use of process mining in novel use cases or experimental settings is often hampered because no appropriate event logs are available. This paper presents a tool to generate synthetic (sensor) event logs. Compared to existing synthetic log generator tools, the IoT process log generator produces data in a non-deterministic way. Users can add noise in a controlled manner and might enhance the processes with IoT data. In this way, the tool 1 allows generating synthetic data for IoT environments that can be individually configured. Our tool makes a contribution towards an increased use of process mining in settings relying on (IoT) sensor event data.
... SimIoT [9] is a SimIC [10]-based simulation framework. The MobIoTSim [11] scenario is a semi-simulated platform for testing IoT cloud architecture. It uses a mobile simulation environment to replicate the behaviour of IoT sensors and devices. ...
The paper can be found at my profile page:
https://research-portal.uws.ac.uk/en/publications/comparative-analysis-of-simulators-for-iot-applications-in-fogclo
