Discrete Event Modeling and Simulation for IoT Efficient Design Combining WComp and DEVSimPy Framework

International audienceOne of today's challenges in the framework of ubiquitous computing concerns the design of ambient systems including sensors, smart-phones, interconnected objects, computers, etc. The major difficulty is to propose a compositional adaptation which aims to integrate new features that were not foreseen in the design, remove or exchange entities that are no longer available in a given context. In order to provide help to overcome this difficulty, a new approach based on the definition of strategies validated using discrete-event simulation is proposed. Such strategies make it possible to take into account conflicts and compositional adaptation of components in ambient systems. These are defined and validate using a discrete-event formalism to be integrated into a prototyping and dynamic execution environment for ambient intelligence applications. The proposed solution allows the designers of ambient systems to define the optimum matching of all components to each other. One pedagogical example is presented (switch-lamp system) as a proof of the proposed approach

Simulators for the Internet of Things

The thesis delivers an extensive review of free and open-source simulation tools useful for IoT simulation. The work deals with free simulators and other tools and sources applicable to simulation of IoT use cases. Roughly 80 tools and other sources were reviewed. Different application domain simulators were enlisted (smart home, connected vehicles, smart city, smart grid, UAV...), network simulators, WSN simulators, discrete event simulators, virtualization tools, emulators and simulators of embedded devices, context simulators (agent based modelling tools), data generators (GPS, MQ), sensor simulators and cosimulators. In connection with simulation we also listed: prototyping tools, real time operating systems (for resource-constrained devices), middleware, development platforms, open testbeds, metodologies, standalone simulator software specifications. Enlisted tools were described with emphasis on key functional characteristics. A comparative table was added to facilitate the process of searching for required tools. Possible procedures for modelling are included, as well as practical tips how to use the use of comparative table. The procedure of modelling and execution of simulation was presented by practical use case. Several risk factors and issues associated with IoT development were identified. A possible approach to deal with them is modelling and simulation. Conclusions and findings: natural correlation between open source simulators and IoT ad hoc architectural characteristics, intuitive modelling by assembling open source simulation tools in manner of lego bricks, usage of agent-based modelling to humanize the simulted situation, simulation as a backbone of IoT development

Simulators for the Internet of Things

The thesis delivers an extensive review of free and open-source simulation tools useful for IoT simulation. The work deals with free simulators and other tools and sources applicable to simulation of IoT use cases. Roughly 80 tools and other sources were reviewed. Different application domain simulators were enlisted (smart home, connected vehicles, smart city, smart grid, UAV...), network simulators, WSN simulators, discrete event simulators, virtualization tools, emulators and simulators of embedded devices, context simulators (agent based modelling tools), data generators (GPS, MQ), sensor simulators and cosimulators. In connection with simulation we also listed: prototyping tools, real time operating systems (for resource-constrained devices), middleware, development platforms, open testbeds, metodologies, standalone simulator software specifications. Enlisted tools were described with emphasis on key functional characteristics. A comparative table was added to facilitate the process of searching for required tools. Possible procedures for modelling are included, as well as practical tips how to use the use of comparative table. The procedure of modelling and execution of simulation was presented by practical use case. Several risk factors and issues associated with IoT development were identified. A possible approach to deal with them is modelling and simulation. Conclusions and findings: natural correlation between open source simulators and IoT ad hoc architectural characteristics, intuitive modelling by assembling open source simulation tools in manner of lego bricks, usage of agent-based modelling to humanize the simulted situation, simulation as a backbone of IoT development

DevOps for Trustworthy Smart IoT Systems

ENACT is a research project funded by the European Commission under its H2020 program. The project consortium consists of twelve industry and research member organisations spread across the whole EU. The overall goal of the ENACT project was to provide a novel set of solutions to enable DevOps in the realm of trustworthy Smart IoT Systems. Smart IoT Systems (SIS) are complex systems involving not only sensors but also actuators with control loops distributed all across the IoT, Edge and Cloud infrastructure. Since smart IoT systems typically operate in a changing and often unpredictable environment, the ability of these systems to continuously evolve and adapt to their new environment is decisive to ensure and increase their trustworthiness, quality and user experience. DevOps has established itself as a software development life-cycle model that encourages developers to continuously bring new features to the system under operation without sacrificing quality. This book reports on the ENACT work to empower the development and operation as well as the continuous and agile evolution of SIS, which is necessary to adapt the system to changes in its environment, such as newly appearing trustworthiness threats

DevOps for Trustworthy Smart IoT Systems

ENACT is a research project funded by the European Commission under its H2020 program. The project consortium consists of twelve industry and research member organisations spread across the whole EU. The overall goal of the ENACT project was to provide a novel set of solutions to enable DevOps in the realm of trustworthy Smart IoT Systems. Smart IoT Systems (SIS) are complex systems involving not only sensors but also actuators with control loops distributed all across the IoT, Edge and Cloud infrastructure. Since smart IoT systems typically operate in a changing and often unpredictable environment, the ability of these systems to continuously evolve and adapt to their new environment is decisive to ensure and increase their trustworthiness, quality and user experience. DevOps has established itself as a software development life-cycle model that encourages developers to continuously bring new features to the system under operation without sacrificing quality. This book reports on the ENACT work to empower the development and operation as well as the continuous and agile evolution of SIS, which is necessary to adapt the system to changes in its environment, such as newly appearing trustworthiness threats

Methodology for technology evaluation under uncertainty and its application in advanced coal gasification processes

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 273-287).Integrated gasification combined cycle (IGCC) technology has attracted interest as a cleaner alternative to conventional coal-fired power generation processes. While a number of pilot projects have been launched to experimentally test IGCC technologies, mathematical simulation remains a central part of the ongoing research efforts. A major challenge in modeling an IGCC power plant is the lack of real experience and reliable data. It is critical to properly understand the state of knowledge and evaluate the impact of uncertainty in every phase of the R&D process. A rigorous investigation of the effect of uncertainty on IGCC system requires accurate quantification of input uncertainty and efficient propagation of uncertainty through system models. This thesis proposes several uncertainty quantification methods which expand the sources of information that can be used for parameter estimation. Key features of these methods include the use of entropy maximization to translate subjective opinions to probability distribution functions, and a more flexible probability model that easily captures anomaly associated with small sample data. In addition, Bayesian estimation is extended to dynamic models. Aided by a computationally efficient algorithm, termed sequential Monte Carlo method, the Bayesian approach is shown to be an effective way to estimate time-variant parameters. Uncertainty propagation is performed using the deterministic equivalent modeling method (DEMM) which is based on polynomial chaos representation of random variables and probabilistic collocation algorithm. One major issue often overlooked in the analysis of IGCC models is to represent correlation in the input parameters. This thesis proposes the use of principal component analysis (PCA) to represent correlated random variables. The resulting formulation is the same as the truncated Karhunen-Lodve expansions. Explicit incorporation of correlation not only improves accuracy of the approximation but also reduces the overall computational time. A comprehensive study of the MIT-BP IGCC model is carried out to determine uncertainties of the key measures of performance and cost, including energy output, thermal efficiency, CO 2 emission, plant capital cost, and cost of electricity. Whenever possible, the probability distributions of input parameters are estimated based on realistic data. Experts' judgments are solicited if data acquisition is infeasible. Uncertainty analysis is conducted in a three-step approach. First, technology-related input parameters are taken into account to determine uncertainties of plant performance. Second, cost uncertainties are determined with only economic inputs in order to identify important economic parameters. Finally, the plant model is integrated with cost model and they are evaluated with the key technical and economic inputs identified in the previous steps. Our study indicates the property of coal feed has a substantial impact on the energy production of the IGCC plant, and subsequently on the cost of electricity. Immature technologies such as gasification and gas turbine have important bearing on model performance hence need to be addressed in future research.by Bo Gong.Ph.D

FAULT DETECTION AND DIAGNOSIS METHODS FOR RESIDENTIAL AIR CONDITIONING SYSTEMS USING CLOUD-BASED DATA

Buildings account for nearly 40% of total energy consumption and nearly 75% of electrical energy consumption in the United States, and a significant portion of this energy consumption is due to the heating and cooling systems. Both commercial and residential heating, ventilation, and air conditioning (HVAC) systems are prone to faults that degrade performance and increase energy consumption. Furthermore, these systems are robust to faults in that they will operate with faults present for an extended period of time and will often continue to maintain a comfortable indoor environment. While considerable work has been devoted to developing fault detection and diagnosis (FDD) strategies for large and small commercial systems, relatively little has been done specifically for residential systems. This research presents novel FDD methods developed specifically for residential air conditioning systems. By using a novel set of virtual sensing methods, the proposed methodology eliminates the need for installing sensors on the outdoor unit. This is a significant advantage for residential ‘split’ air conditioning systems because installing sensors on both the indoor and outdoor units increases the complexity and cost of the data acquisition system. In addition to the proposed set of virtual sensors, this research provides solutions to two other problems that arise when implementing FDD methods on field-operating systems. (1) While most FDD methods use static models and rely on steady state analysis, field-operating systems often will not achieve steady state operation. This research provides a method for predicting the equilibrium operating point for many air conditioning parameters while the system is still in a transient response. This enables the equilibrium point to be determined before steady state operation has been achieved, and thus a static analysis may be performed without the system reaching steady state. (2) Existing change-point detection methods that could be used for detecting faults are impractical to implement on a large scale because they may require a priori knowledge, extensive tuning, or high computational loads. This research proposes a change-point detection algorithm for the purpose of fault detection which requires minimal assumptions, tuning, and computation. This change-point detection algorithm is suitable for deployment across many different systems simultaneously. In addition to the solutions outlined above for performing FDD using installed sensors, this research also proposes methods for performing fault detection and diagnose using only thermostat data. While a full strategy for thermostat data is not presented, crucial preprocessing methods that more complete methods will be built on are presented in detail. Nearly all of the data analyzed for each method described in this study uses event-based data uploaded in real-time to a cloud-based database and then queried and analyzed to perform FDD

IoT Efficient Design Using WComp Framework and Discrete Event Modeling and Simulation

International audienceComplex systems that increasingly involves devices such as sensors, smart-phone, interconnected objects and computers, results in what is called ambient systems. One of today’s challenges in the framework of ubiquitous computing concerns the design of ambient systems. The major difficulty is to propose a compositional adaptation of devices which appear/despair over time. WComp environment is a prototyping and dynamic execution environment for ambient intelligence applications including a management mechanism allowing extensible interference between devices. A new approach based on the definition of strategies validated using discrete-event simulation is proposed in order to take into account conflicts and compositional adaptation of devices in ambient systems. These are defined and validate using a DEVS (Discrete EVent system Specification) formalism to be integrated into a prototyping and dynamic execution environment for ambient intelligence applications. The proposed solution allows the designers of ambient systems to define the optimum matching of all components to each other. One pedagogical example is presented (switch-lamp system) as a proof of the proposed approach

Avances en Ciencias y Técnicas del Frío - 11

Este año 2022 se han cumplido 20 años desde la fundación de la Sociedad Española de Ciencias y Técnicas del Frío (SECYTEF; http://secytef.upct.es/), que tuvo lugar precisamente en la Universidad Politécnica de Cartagena, durante la celebración en esta Universidad del primer congreso CYTEF en 2002. Fue el Primer Congreso Español de Ciencias y Técnicas del Frío de esta serie de congresos CYTEF. Posteriormente, los congresos CYTEF han tenido lugar cada 2 años, y de su organización se ha encargado especialmente la SECYTEF, ya que es su principal cometido Los trabajos de investigación presentados en los Congresos CYTEF han sido publicados en los libros de actas correspondientes que constituyen una serie denominada Avances en Ciencias y Técnicas del Frío. Contando con este libro de Actas del CYTEF 2022, ya son 11 números de esta serie de libros los publicados. Representan una valiosa fuente de información científico-técnica para los investigadores, técnicos y profesionales interesados en las Ciencias y Técnicas del Frío, tanto en lo que se refiere a tecnologías de producción de frío, como a las tecnologías de su aplicación en los distintos sectores