Publications tagged with Performances evaluation
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Publications tagged with "Performances evaluation"
- DetailsCampanile, L., Iacono, M., Mastroianni, M., Riccio, C., & Viscardi, B. (2026). A TOPSIS-Based Approach to Evaluate Alternative Solutions for GDPR-Compliant Smart-City Services Implementation [Conference paper]. Lecture Notes in Computer Science, 15893 LNCS, 303–316. https://doi.org/10.1007/978-3-031-97645-2_20
Abstract
Adapting or designing a system which operates on personal data in EU is impacted by the privacy-by-design and privacy-by-default principles because of the prescriptions of the GDPR. In this paper we propose an approach to decision making which is based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The approach is applied to a GDPR system compliance design process, based on a case study about system performance evaluation by means of queuing networks, but is absolutely general with respect to analogous problems, in which cost issues should be balanced with technical performances and risk exposure. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. - 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. - DetailsCampanile, L., Di Bonito, L. P., Gribaudo, M., & Iacono, M. (2023). A Domain Specific Language for the Design of Artificial Intelligence Applications for Process Engineering [Conference paper]. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 482 LNICST, 133–146. https://doi.org/10.1007/978-3-031-31234-2_8
Abstract
Processes in chemical engineering are frequently enacted by one-of-a-kind devices that implement dynamic processes with feedback regulations designed according to experimental studies and empirical tuning of new devices after the experience obtained on similar setups. While application of artificial intelligence based solutions is largely advocated by researchers in several fields of chemical engineering to face the problems deriving from these practices, few actual cases exist in literature and in industrial plants that leverage currently available tools as much as other application fields suggest. One of the factors that is limiting the spread of AI-based solutions in the field is the lack of tools that support the evaluation of the needs of plants, be those existing or to-be settlements. In this paper we provide a Domain Specific Language based approach for the evaluation of the basic performance requirements for cloud-based setups capable of supporting chemical engineering plants, with a metaphor that attempts to bridge the two worlds. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. - 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 - 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.