Flexible Representation of IoT Sensors for Cloud Simulators

In Internet of Things (IoT), sensors, actuators and smart devices are connected to the Internet. Application providers combine this connectivity with novel scenarios involving cloud computing. Some require in depth analysis of the interaction between IoT devices and clouds. Research focuses on questions like how to govern such large cohort of devices (i.e., often over tens of thousands). Distributed systems simulators help in such analysis, but they are problematic to apply in this newly emerging domain. Most simulators are either too detailed (e.g., need extensive knowledge on networking), or not extensible enough to support the new scenarios. This paper introduces our attempt to show how a state of the art simulator could model generic IoT sensors. We show the fundamental properties of IoT entities represented in the simulator. Based on these properties, we present an XML based, declarative modelling language aiming at: (i) describing the behaviour of sensors and their relation to clouds, and (ii) allowing rapid prototyping of simulations. Finally, we validate the applicability of our IoT extensions in five scenarios in the field of weather forecasting

Cost-Aware IoT Extension of DISSECT-CF

In the age of the Internet of Things (IoT), more and more sensors, actuators and smart devices get connected to the network. Application providers often combine this connectivity with novel scenarios involving cloud computing. Before implementing changes in these large-scale systems, an in-depth analysis is often required to identify governance models, bottleneck situations, costs and unexpected behaviours. Distributed systems simulators help in such analysis, but they are often problematic to apply in this newly emerging domain. For example, most simulators are either too detailed (e.g., need extensive knowledge on networking), or not extensible enough to support the new scenarios. To overcome these issues, we discuss our IoT cost analysis oriented extension of DIScrete event baSed Energy Consumption simulaTor for Clouds and Federations (DISSECT-CF). Thus, we present an in-depth analysis of IoT and cloud related pricing models of the most widely used commercial providers. Then, we show how the fundamental properties (e.g., data production frequency) of IoT entities could be linked to the identified pricing models. To allow the adoption of unforeseen scenarios and pricing schemes, we present a declarative modelling language to describe these links. Finally, we validate our extensions by analysing the effects of various identified pricing models through five scenarios coming from the field of weather forecasting

Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook of Software and Services

Sensing, communication, computation and control technologies are the essential building blocks of a cyber-physical system (CPS). Wireless sensor networks (WSNs) are a way to support CPS as they provide fine-grained spatial-temporal sensing, communication and computation at a low premium of cost and power. In this article, we explore the fundamental concepts guiding the design and implementation of WSNs. We report the latest developments in WSN software and services for meeting existing requirements and newer demands; particularly in the areas of: operating system, simulator and emulator, programming abstraction, virtualization, IP-based communication and security, time and location, and network monitoring and management. We also reflect on the ongoing efforts in providing dependable assurances for WSN-driven CPS. Finally, we report on its applicability with a case-study on smart buildings

Analysis and simulation of emergent architectures for internet of things

The Internet of Things (IoT) promises a plethora of new services and applications supported by a wide range of devices that includes sensors and actuators. To reach its potential IoT must break down the silos that limit applications' interoperability and hinder their manageability. These silos' result from existing deployment techniques where each vendor set up its own infrastructure, duplicating the hardware and increasing the costs. Fog Computing can serve as the underlying platform to support IoT applications thus avoiding the silos'. Each application becomes a system formed by IoT devices (i.e. sensors, actuators), an edge infrastructure (i.e. Fog Computing) and the Cloud. In order to improve several aspects of human lives, different systems can interact to correlate data obtaining functionalities not achievable by any of the systems in isolation. Then, we can analyze the IoT as a whole system rather than a conjunction of isolated systems. Doing so leads to the building of Ultra-Large Scale Systems (ULSS), an extension of the concept of Systems of Systems (SoS), in several verticals including Autonomous Vehicles, Smart Cities, and Smart Grids. The scope of ULSS is large in the number of things and complex in the variety of applications, volume of data, and diversity of communication patterns. To handle this scale and complexity in this thesis we propose Hierarchical Emergent Behaviors (HEB), a paradigm that builds on the concepts of emergent behavior and hierarchical organization. Rather than explicitly program all possible situations in the vast space of ULSS scenarios, HEB relies on emergent behaviors induced by local rules that define the interactions of the "things" between themselves and also with their environment. We discuss the modifications to classical IoT architectures required by HEB, as well as the new challenges. Once these challenges such as scalability and manageability are addressed, we can illustrate HEB's usefulness dealing with an IoT-based ULSS through a case study based on Autonomous Vehicles (AVs). To this end we design and analyze well-though simulations that demonstrate its tremendous potential since small modifications to the basic set of rules induce different and interesting behaviors. Then we design a set of primitives to perform basic maneuver such as exiting a platoon formation and maneuvering in anticipation of obstacles beyond the range of on-board sensors. These simulations also evaluate the impact of a HEB deployment assisted by Fog nodes to enlarge the informational scope of vehicles. To conclude we develop a design methodology to build, evaluate, and run HEB-based solutions for AVs. We provide architectural foundations for the second level and its implications in major areas such as communications. These foundations are then validated through simulations that incorporate new rules, obtaining valuable experimental observations. The proposed architecture has a tremendous potential to solve the scalability issue found in ULSS, enabling IoT deployments to reach its true potential.El Internet de las Cosas (IoT) promete una plétora de nuevos servicios y aplicaciones habilitadas por una amplia gama de dispositivos que incluye sensores y actuadores. Para alcanzar su potencial, IoT debe superar los silos que limitan la interoperabilidad de las aplicaciones y dificultan su administración. Estos silos son el resultado de las técnicas de implementación existentes en las que cada proveedor instala su propia infraestructura y duplica el hardware, incrementando los costes. Fog Computing puede servir como la plataforma subyacente que soporte aplicaciones del IoT evitando así los silos. Cada aplicación se convierte en un sistema formado por dispositivos IoT (por ejemplo sensores y actuadores), una infraestructura (como Fog Computing) y la nube. Con el fin de mejorar varios aspectos de la vida humana, diferentes sistemas pueden interactuar para correlacionar datos obteniendo funcionalidades que no pueden lograrse por ninguno de los sistemas de forma aislada. Entonces, podemos analizar el IoT como un único sistema en lugar de una conjunción de sistemas aislados. Esta perspectiva conduce a la construcción de Ultra-Large Scale Systems (ULSS), una extensión del concepto de Systems of Systems (SoS), en varios verticales, incluidos los vehículos autónomos, Smart Cities y Smart Grids. El alcance de ULSS es vasto debido a la cantidad de dispositivos y complejo en la variedad de aplicaciones, volumen de datos y diversidad de patrones de comunicación. Para manejar esta escala y complejidad, en esta tesis proponemos Hierarchical Emergent Behaviors (HEB), un paradigma que se basa en los conceptos de comportamientos emergente y organización jerárquica. En lugar de programar explícitamente todas las situaciones posibles en el vasto espacio de escenarios presentes en los ULSS, HEB se basa en comportamientos emergentes inducidos por reglas locales que definen las interacciones de las "cosas" entre ellas y también con su entorno. Discutimos las modificaciones a las arquitecturas clásicas de IoT requeridas por HEB, así como los nuevos desafíos. Una vez que se abordan estos desafíos, como la escalabilidad y la capacidad de administración, podemos ilustrar la utilidad de HEB cuando se ocupa de un ULSS basado en IoT a través de un caso de estudio basado en Vehículos Autónomos (AV). Con este fin, diseñamos y analizamos simulaciones que demuestran su enorme potencial, ya que pequeñas modificaciones en el conjunto básico de reglas inducen comportamientos diferentes e interesantes. Luego, diseñamos un conjunto de primitivas para realizar una maniobra básica, como salir de un pelotón y maniobrar en anticipación de obstáculos más allá del alcance de los sensores de a bordo. Estas simulaciones también evalúan el impacto de una implementación de HEB asistida por nodos de Fog Computing para ampliar el alcance sensorial de los vehículos. Para concluir, desarrollamos una metodología de diseño para construir, evaluar y ejecutar soluciones basadas en HEB para AV. Brindamos fundamentos arquitectónicos para el segundo nivel de HEB y sus implicaciones en áreas importantes como las comunicaciones. Estas bases se validan a través de simulaciones que incorporan nuevas reglas, obteniendo valiosas observaciones experimentales. La arquitectura propuesta tiene un enorme potencial para resolver el problema de escalabilidad que presentan los ULSS, permitiendo que las implementaciones de IoT alcancen su verdadero potencial

CERN Storage Systems for Large-Scale Wireless

The project aims at evaluating the use of CERN computing infrastructure for next generation sensor networks data analysis. The proposed system allows the simulation of a large-scale sensor array for traffic analysis, streaming data to CERN storage systems in an efficient way. The data are made available for offline and quasi-online analysis, enabling both long term planning and fast reaction on the environment

Advancements and Challenges in IoT Simulators: A Comprehensive Review

The Internet of Things (IoT) has emerged as an important concept, bridging the physical and digital worlds through interconnected devices. Although the idea of interconnected devices predates the term “Internet of Things”, which was coined in 1999 by Kevin Ashton, the vision of a seamlessly integrated world of devices has been accelerated by advancements in wireless technologies, cost-effective computing, and the ubiquity of mobile devices. This study aims to provide an in-depth review of existing and emerging IoT simulators focusing on their capabilities and real-world applications, and discuss the current challenges and future trends in the IoT simulation area. Despite substantial research in the IoT simulation domain, many studies have a narrow focus, leaving a gap in comprehensive reviews that consider broader IoT development metrics, such as device mobility, energy models, Software-Defined Networking (SDN), and scalability. Notably, there is a lack of literature examining IoT simulators’ capabilities in supporting renewable energy sources and their integration with Vehicular Ad-hoc Network (VANET) simulations. Our review seeks to address this gap, evaluating the ability of IoT simulators to simulate complex, large-scale IoT scenarios and meet specific developmental requirements, as well as examining the current challenges and future trends in the field of IoT simulation. Our systematic analysis has identified several significant gaps in the current literature. A primary concern is the lack of a generic simulator capable of effectively simulating various scenarios across different domains within the IoT environment. As a result, a comprehensive and versatile simulator is required to simulate the diverse scenarios occurring in IoT applications. Additionally, there is a notable gap in simulators that address specific security concerns, particularly battery depletion attacks, which are increasingly relevant in IoT systems. Furthermore, there is a need for further investigation and study regarding the integration of IoT simulators with traffic simulation for VANET environments. In addition, it is noteworthy that renewable energy sources are underrepresented in IoT simulations, despite an increasing global emphasis on environmental sustainability. As a result of these identified gaps, it is imperative to develop more advanced and adaptable IoT simulation tools that are designed to meet the multifaceted challenges and opportunities of the IoT domain

Analysis and simulation of emergent architectures for internet of things

The Internet of Things (IoT) promises a plethora of new services and applications supported by a wide range of devices that includes sensors and actuators. To reach its potential IoT must break down the silos that limit applications' interoperability and hinder their manageability. These silos' result from existing deployment techniques where each vendor set up its own infrastructure, duplicating the hardware and increasing the costs. Fog Computing can serve as the underlying platform to support IoT applications thus avoiding the silos'. Each application becomes a system formed by IoT devices (i.e. sensors, actuators), an edge infrastructure (i.e. Fog Computing) and the Cloud. In order to improve several aspects of human lives, different systems can interact to correlate data obtaining functionalities not achievable by any of the systems in isolation. Then, we can analyze the IoT as a whole system rather than a conjunction of isolated systems. Doing so leads to the building of Ultra-Large Scale Systems (ULSS), an extension of the concept of Systems of Systems (SoS), in several verticals including Autonomous Vehicles, Smart Cities, and Smart Grids. The scope of ULSS is large in the number of things and complex in the variety of applications, volume of data, and diversity of communication patterns. To handle this scale and complexity in this thesis we propose Hierarchical Emergent Behaviors (HEB), a paradigm that builds on the concepts of emergent behavior and hierarchical organization. Rather than explicitly program all possible situations in the vast space of ULSS scenarios, HEB relies on emergent behaviors induced by local rules that define the interactions of the "things" between themselves and also with their environment. We discuss the modifications to classical IoT architectures required by HEB, as well as the new challenges. Once these challenges such as scalability and manageability are addressed, we can illustrate HEB's usefulness dealing with an IoT-based ULSS through a case study based on Autonomous Vehicles (AVs). To this end we design and analyze well-though simulations that demonstrate its tremendous potential since small modifications to the basic set of rules induce different and interesting behaviors. Then we design a set of primitives to perform basic maneuver such as exiting a platoon formation and maneuvering in anticipation of obstacles beyond the range of on-board sensors. These simulations also evaluate the impact of a HEB deployment assisted by Fog nodes to enlarge the informational scope of vehicles. To conclude we develop a design methodology to build, evaluate, and run HEB-based solutions for AVs. We provide architectural foundations for the second level and its implications in major areas such as communications. These foundations are then validated through simulations that incorporate new rules, obtaining valuable experimental observations. The proposed architecture has a tremendous potential to solve the scalability issue found in ULSS, enabling IoT deployments to reach its true potential.El Internet de las Cosas (IoT) promete una plétora de nuevos servicios y aplicaciones habilitadas por una amplia gama de dispositivos que incluye sensores y actuadores. Para alcanzar su potencial, IoT debe superar los silos que limitan la interoperabilidad de las aplicaciones y dificultan su administración. Estos silos son el resultado de las técnicas de implementación existentes en las que cada proveedor instala su propia infraestructura y duplica el hardware, incrementando los costes. Fog Computing puede servir como la plataforma subyacente que soporte aplicaciones del IoT evitando así los silos. Cada aplicación se convierte en un sistema formado por dispositivos IoT (por ejemplo sensores y actuadores), una infraestructura (como Fog Computing) y la nube. Con el fin de mejorar varios aspectos de la vida humana, diferentes sistemas pueden interactuar para correlacionar datos obteniendo funcionalidades que no pueden lograrse por ninguno de los sistemas de forma aislada. Entonces, podemos analizar el IoT como un único sistema en lugar de una conjunción de sistemas aislados. Esta perspectiva conduce a la construcción de Ultra-Large Scale Systems (ULSS), una extensión del concepto de Systems of Systems (SoS), en varios verticales, incluidos los vehículos autónomos, Smart Cities y Smart Grids. El alcance de ULSS es vasto debido a la cantidad de dispositivos y complejo en la variedad de aplicaciones, volumen de datos y diversidad de patrones de comunicación. Para manejar esta escala y complejidad, en esta tesis proponemos Hierarchical Emergent Behaviors (HEB), un paradigma que se basa en los conceptos de comportamientos emergente y organización jerárquica. En lugar de programar explícitamente todas las situaciones posibles en el vasto espacio de escenarios presentes en los ULSS, HEB se basa en comportamientos emergentes inducidos por reglas locales que definen las interacciones de las "cosas" entre ellas y también con su entorno. Discutimos las modificaciones a las arquitecturas clásicas de IoT requeridas por HEB, así como los nuevos desafíos. Una vez que se abordan estos desafíos, como la escalabilidad y la capacidad de administración, podemos ilustrar la utilidad de HEB cuando se ocupa de un ULSS basado en IoT a través de un caso de estudio basado en Vehículos Autónomos (AV). Con este fin, diseñamos y analizamos simulaciones que demuestran su enorme potencial, ya que pequeñas modificaciones en el conjunto básico de reglas inducen comportamientos diferentes e interesantes. Luego, diseñamos un conjunto de primitivas para realizar una maniobra básica, como salir de un pelotón y maniobrar en anticipación de obstáculos más allá del alcance de los sensores de a bordo. Estas simulaciones también evalúan el impacto de una implementación de HEB asistida por nodos de Fog Computing para ampliar el alcance sensorial de los vehículos. Para concluir, desarrollamos una metodología de diseño para construir, evaluar y ejecutar soluciones basadas en HEB para AV. Brindamos fundamentos arquitectónicos para el segundo nivel de HEB y sus implicaciones en áreas importantes como las comunicaciones. Estas bases se validan a través de simulaciones que incorporan nuevas reglas, obteniendo valiosas observaciones experimentales. La arquitectura propuesta tiene un enorme potencial para resolver el problema de escalabilidad que presentan los ULSS, permitiendo que las implementaciones de IoT alcancen su verdadero potencial.Postprint (published version