Topic: Simulation
Published:
2025
- DetailsCampanile, L., Iacono, M., Mastroianni, M., & Riccio, C. (2025). Performance Evaluation of an Edge-Blockchain Architecture for Smart City [Conference paper]. Proceedings - European Council for Modelling and Simulation, ECMS, 2025-June, 620–627. https://doi.org/10.7148/2025-0620
Abstract
This paper presents a simulation-based methodology to evaluate the performance of a privacy-compliant edge-blockchain architecture for smart city environments. The proposed model combines edge computing with a private, permissioned blockchain to ensure low-latency processing, secure data management, and verifiable transactions. Using a discrete-event simulation framework, we analyze the behavior of the system under realistic workloads and time-varying traffic conditions. The model captures edge operations, including preprocessing and cryptographic tasks, as well as blockchain validation using Proof of Stake consensus. Several experiments explore saturation thresholds, resource utilization, and latency dynamics, under both synthetic and realistic traffic profiles. Results reveal how architectural bottlenecks shift depending on resource allocation and input rate, and demonstrate the importance of balanced dimensioning between edge and blockchain layers. © ECMS Marco Scarpa, Salvatore Cavalieri, Salvatore Serrano, Fabrizio De Vita (Editors) 2025.
2022
- DetailsCampanile, L., Iacono, M., Marulli, F., Gribaudo, M., & Mastroianni, M. (2022). A DSL-based modeling approach for energy harvesting IoT/WSN [Conference paper]. Proceedings - European Council for Modelling and Simulation, ECMS, 2022-May, 317–323. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130645195&partnerID=40&md5=f2d475b445f76d3b5f49752171c0fada
Abstract
The diffusion of intelligent services and the push for the integration of computing systems and services in the environment in which they operate require a constant sensing activity and the acquisition of different information from the environment and the users. Health monitoring, domotics, Industry 4.0 and environmental challenges leverage the availability of cost-effective sensing solutions that allow both the creation of knowledge bases and the automatic process of them, be it with algorithmic approaches or artificial intelligence solutions. The foundation of these solutions is given by the Internet of Things (IoT), and the substanding Wireless Sensor Networks (WSN) technology stack. Of course, design approaches are needed that enable defining efficient and effective sensing infrastructures, including energy related aspects. In this paper we present a Domain Specific Language for the design of energy aware WSN IoT solutions, that allows domain experts to define sensor network models that may be then analyzed by simulation-based or analytic techniques to evaluate the effect of task allocation and offioading and energy harvesting and utilization in the network. The language has been designed to leverage the SIMTHESys modeling framework and its multiformalism modeling evaluation features. ©ECMS Ibrahim A. Hameed, Agus Hasan, Saleh Abdel-Afou Alaliyat (Editors) 2022
2021
- DetailsCampanile, L., Gribaudo, M., Iacono, M., & Mastroianni, M. (2021). Hybrid Simulation of Energy Management in IoT Edge Computing Surveillance Systems [Conference paper]. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13104 LNCS, 345–359. https://doi.org/10.1007/978-3-030-91825-5_21
Abstract
Internet of Things (IoT) is a well established approach used for the implementation of surveillance systems that are suitable for monitoring large portions of territory. Current developments allow the design of battery powered IoT nodes that can communicate over the network with low energy requirements and locally perform some computing and coordination task, besides running sensing and related processing: it is thus possible to implement edge computing oriented solutions on IoT, if the design encompasses both hardware and software elements in terms of sensing, processing, computing, communications and routing energy costs as one of the quality indices of the system. In this paper we propose a modeling approach for edge computing IoT-based monitoring systems energy related characteristics, suitable for the analysis of energy levels of large battery powered monitoring systems with dynamic and reactive computing workloads. © 2021, Springer Nature Switzerland AG.
2020
- DetailsConference A flexible simulation-based framework for model-based/data-driven dependability evaluationAbate, C., Campanile, L., & Marrone, S. (2020). A flexible simulation-based framework for model-based/data-driven dependability evaluation [Conference paper]. Proceedings - 2020 IEEE 31st International Symposium on Software Reliability Engineering Workshops, ISSREW 2020, 261–266. https://doi.org/10.1109/ISSREW51248.2020.00083
Abstract
Modern predictive maintenance is the convergence of several technological trends: developing new techniques and algorithms can be very costly due to the need for a physical prototype. This research has the final aim to build a simulation-based software framework for modeling and analysing complex systems and for defining predictive maintenance algorithms. By the usage of simulation, quantitative evaluation of the dependability of such systems will be possible. The ERTMS/ETCS dependability case study is presented to prove the applicability of the software. © 2020 IEEE.
2025
- DetailsCampanile, L., Iacono, M., Mastroianni, M., & Riccio, C. (2025). Performance Evaluation of an Edge-Blockchain Architecture for Smart City [Conference paper]. Proceedings - European Council for Modelling and Simulation, ECMS, 2025-June, 620–627. https://doi.org/10.7148/2025-0620
Abstract
This paper presents a simulation-based methodology to evaluate the performance of a privacy-compliant edge-blockchain architecture for smart city environments. The proposed model combines edge computing with a private, permissioned blockchain to ensure low-latency processing, secure data management, and verifiable transactions. Using a discrete-event simulation framework, we analyze the behavior of the system under realistic workloads and time-varying traffic conditions. The model captures edge operations, including preprocessing and cryptographic tasks, as well as blockchain validation using Proof of Stake consensus. Several experiments explore saturation thresholds, resource utilization, and latency dynamics, under both synthetic and realistic traffic profiles. Results reveal how architectural bottlenecks shift depending on resource allocation and input rate, and demonstrate the importance of balanced dimensioning between edge and blockchain layers. © ECMS Marco Scarpa, Salvatore Cavalieri, Salvatore Serrano, Fabrizio De Vita (Editors) 2025.
2022
- DetailsCampanile, L., Iacono, M., Marulli, F., Gribaudo, M., & Mastroianni, M. (2022). A DSL-based modeling approach for energy harvesting IoT/WSN [Conference paper]. Proceedings - European Council for Modelling and Simulation, ECMS, 2022-May, 317–323. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130645195&partnerID=40&md5=f2d475b445f76d3b5f49752171c0fada
Abstract
The diffusion of intelligent services and the push for the integration of computing systems and services in the environment in which they operate require a constant sensing activity and the acquisition of different information from the environment and the users. Health monitoring, domotics, Industry 4.0 and environmental challenges leverage the availability of cost-effective sensing solutions that allow both the creation of knowledge bases and the automatic process of them, be it with algorithmic approaches or artificial intelligence solutions. The foundation of these solutions is given by the Internet of Things (IoT), and the substanding Wireless Sensor Networks (WSN) technology stack. Of course, design approaches are needed that enable defining efficient and effective sensing infrastructures, including energy related aspects. In this paper we present a Domain Specific Language for the design of energy aware WSN IoT solutions, that allows domain experts to define sensor network models that may be then analyzed by simulation-based or analytic techniques to evaluate the effect of task allocation and offioading and energy harvesting and utilization in the network. The language has been designed to leverage the SIMTHESys modeling framework and its multiformalism modeling evaluation features. ©ECMS Ibrahim A. Hameed, Agus Hasan, Saleh Abdel-Afou Alaliyat (Editors) 2022
2021
- DetailsCampanile, L., Gribaudo, M., Iacono, M., & Mastroianni, M. (2021). Hybrid Simulation of Energy Management in IoT Edge Computing Surveillance Systems [Conference paper]. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13104 LNCS, 345–359. https://doi.org/10.1007/978-3-030-91825-5_21
Abstract
Internet of Things (IoT) is a well established approach used for the implementation of surveillance systems that are suitable for monitoring large portions of territory. Current developments allow the design of battery powered IoT nodes that can communicate over the network with low energy requirements and locally perform some computing and coordination task, besides running sensing and related processing: it is thus possible to implement edge computing oriented solutions on IoT, if the design encompasses both hardware and software elements in terms of sensing, processing, computing, communications and routing energy costs as one of the quality indices of the system. In this paper we propose a modeling approach for edge computing IoT-based monitoring systems energy related characteristics, suitable for the analysis of energy levels of large battery powered monitoring systems with dynamic and reactive computing workloads. © 2021, Springer Nature Switzerland AG.
2020
- DetailsConference A flexible simulation-based framework for model-based/data-driven dependability evaluationAbate, C., Campanile, L., & Marrone, S. (2020). A flexible simulation-based framework for model-based/data-driven dependability evaluation [Conference paper]. Proceedings - 2020 IEEE 31st International Symposium on Software Reliability Engineering Workshops, ISSREW 2020, 261–266. https://doi.org/10.1109/ISSREW51248.2020.00083
Abstract
Modern predictive maintenance is the convergence of several technological trends: developing new techniques and algorithms can be very costly due to the need for a physical prototype. This research has the final aim to build a simulation-based software framework for modeling and analysing complex systems and for defining predictive maintenance algorithms. By the usage of simulation, quantitative evaluation of the dependability of such systems will be possible. The ERTMS/ETCS dependability case study is presented to prove the applicability of the software. © 2020 IEEE.