Topic: Budget control
Published:
2023
- DetailsMarrone, S., Campanile, L., De Fazio, R., Di Giovanni, M., Gentile, U., Marulli, F., & Verde, L. (2023). A Petri net oriented approach for advanced building energy management systems [Article]. Journal of Ambient Intelligence and Smart Environments, 15(3), 211–233. https://doi.org/10.3233/AIS-230065
Abstract
Sustainability is one of the main goals to pursue in several aspects of everyday life; the recent energy shortage and the price raise worsen this problem, especially in the management of energy in buildings. As the Internet of Things (IoT) is an assessed computing paradigm able to capture meaningful data from the field and send them to cloud infrastructures, other approaches are also enabled, namely model-based approaches. These methods can be used to predict functional and non-functional properties of Building Energy Management Systems (BEMS) before setting up them. This paper aims at bridging the gap between model-based approaches and physical realizations of sensing and small computing devices. Through an integrated approach, able to exploit the power of different dialects of Petri Nets, this paper proposes a methodology for the early evaluation of BEMS properties as well as the automatic generation of IoT controllers. © 2023 - IOS Press. All rights reserved.
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
- DetailsCampanile, L., Iacono, M., Lotito, R., & Mastroianni, M. (2020). A WSN Energy-Aware approach for air pollution monitoring in waste treatment facility site: A case study for landfill monitoring odour [Conference paper]. IoTBDS 2020 - Proceedings of the 5th International Conference on Internet of Things, Big Data and Security, 526–532. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089477488&partnerID=40&md5=13ea9ca38f15c5b885ef7e501067010c
Abstract
The gaseous emissions derived from industrial plants are generally subject to a strictly program of monitoring, both continuous or one-spot, in order to comply with the limits imposed by the permitting license. Nowadays the problem of odour emission, and the consequently nuisance generated to the nearest receptors, has acquired importance so that is frequently asked a specific implementation of the air pollution monitoring program. In this paper we studied the case study of a generic landfill for the implementation of the odour monitoring system and time-specific use of air pollution control technology. The off-site monitoring is based on the deployment of electronic nose as part of a specifically built WSN system. The nodes outside the landfill boundary do not act as a continuously monitoring stations but as sensors activated when specific conditions, inside and outside the landfill, are achieved. The WSN is then organized on an energy-aware approach so to prolong the lifetime of the entire system, with significant cost-benefit advancement, and produce a monitoring-structure that can answer to specific input like threshold overshooting. Copyright © 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved. - DetailsCampanile, L., Iacono, M., Martinelli, F., Marulli, F., Mastroianni, M., Mercaldo, F., & Santone, A. (2020). Towards the Use of Generative Adversarial Neural Networks to Attack Online Resources [Conference paper]. Advances in Intelligent Systems and Computing, 1150 AISC, 890–901. https://doi.org/10.1007/978-3-030-44038-1_81
Abstract
The role of remote resources, such as the ones provided by Cloud infrastructures, is of paramount importance for the implementation of cost effective, yet reliable software systems to provide services to third parties. Cost effectiveness is a direct consequence of a correct estimation of resource usage, to be able to define a budget and estimate the right price to put own services on the market. Attacks that overload resources with non legitimate requests, being them explicit attacks or just malicious, non harmful resource engagements, may push the use of Cloud resources beyond estimation, causing additional costs, or unexpected energy usage, or a lower overall quality of services, so intrusion detection devices or firewalls are set to avoid undesired accesses. We propose the use of Generative Adversarial Neural Networks (GANs) to setup a method for shaping request based attacks capable of reaching resources beyond defenses. The approach is studied by using a publicly available traffic data set, to test the concept and demonstrate its potential applications. © 2020, Springer Nature Switzerland AG.
2023
- DetailsMarrone, S., Campanile, L., De Fazio, R., Di Giovanni, M., Gentile, U., Marulli, F., & Verde, L. (2023). A Petri net oriented approach for advanced building energy management systems [Article]. Journal of Ambient Intelligence and Smart Environments, 15(3), 211–233. https://doi.org/10.3233/AIS-230065
Abstract
Sustainability is one of the main goals to pursue in several aspects of everyday life; the recent energy shortage and the price raise worsen this problem, especially in the management of energy in buildings. As the Internet of Things (IoT) is an assessed computing paradigm able to capture meaningful data from the field and send them to cloud infrastructures, other approaches are also enabled, namely model-based approaches. These methods can be used to predict functional and non-functional properties of Building Energy Management Systems (BEMS) before setting up them. This paper aims at bridging the gap between model-based approaches and physical realizations of sensing and small computing devices. Through an integrated approach, able to exploit the power of different dialects of Petri Nets, this paper proposes a methodology for the early evaluation of BEMS properties as well as the automatic generation of IoT controllers. © 2023 - IOS Press. All rights reserved.
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
- DetailsCampanile, L., Iacono, M., Lotito, R., & Mastroianni, M. (2020). A WSN Energy-Aware approach for air pollution monitoring in waste treatment facility site: A case study for landfill monitoring odour [Conference paper]. IoTBDS 2020 - Proceedings of the 5th International Conference on Internet of Things, Big Data and Security, 526–532. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089477488&partnerID=40&md5=13ea9ca38f15c5b885ef7e501067010c
Abstract
The gaseous emissions derived from industrial plants are generally subject to a strictly program of monitoring, both continuous or one-spot, in order to comply with the limits imposed by the permitting license. Nowadays the problem of odour emission, and the consequently nuisance generated to the nearest receptors, has acquired importance so that is frequently asked a specific implementation of the air pollution monitoring program. In this paper we studied the case study of a generic landfill for the implementation of the odour monitoring system and time-specific use of air pollution control technology. The off-site monitoring is based on the deployment of electronic nose as part of a specifically built WSN system. The nodes outside the landfill boundary do not act as a continuously monitoring stations but as sensors activated when specific conditions, inside and outside the landfill, are achieved. The WSN is then organized on an energy-aware approach so to prolong the lifetime of the entire system, with significant cost-benefit advancement, and produce a monitoring-structure that can answer to specific input like threshold overshooting. Copyright © 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved. - DetailsCampanile, L., Iacono, M., Martinelli, F., Marulli, F., Mastroianni, M., Mercaldo, F., & Santone, A. (2020). Towards the Use of Generative Adversarial Neural Networks to Attack Online Resources [Conference paper]. Advances in Intelligent Systems and Computing, 1150 AISC, 890–901. https://doi.org/10.1007/978-3-030-44038-1_81
Abstract
The role of remote resources, such as the ones provided by Cloud infrastructures, is of paramount importance for the implementation of cost effective, yet reliable software systems to provide services to third parties. Cost effectiveness is a direct consequence of a correct estimation of resource usage, to be able to define a budget and estimate the right price to put own services on the market. Attacks that overload resources with non legitimate requests, being them explicit attacks or just malicious, non harmful resource engagements, may push the use of Cloud resources beyond estimation, causing additional costs, or unexpected energy usage, or a lower overall quality of services, so intrusion detection devices or firewalls are set to avoid undesired accesses. We propose the use of Generative Adversarial Neural Networks (GANs) to setup a method for shaping request based attacks capable of reaching resources beyond defenses. The approach is studied by using a publicly available traffic data set, to test the concept and demonstrate its potential applications. © 2020, Springer Nature Switzerland AG.