2013
Other
Restricted
A numerical method for imaging of biological microstructures by VHF waves
Ala G., Cassarà P., Francomano E., Ganci S.
Imaging techniques give a fundamental support to medical diagnostics during the pathology discovery as well as for the characterization of biological struc- tures. The imaging methods involve electromagnetic waves in a frequency range that spans from some Hz to GHz and over. Most of these methods involve scanning of wide human body areas even if only small areas need to be analyzed. In this paper, a numerical method to evaluate the shape of micro-structures for application in the medical field, with a very low in- vasiveness for the human body, is proposed. A flexible thin-wire antenna radiates the VHF waves and then, by measuring the spatial magnetic field distribution it is possible to reconstruct the micro-structures image by es- timating the location of the antenna against a sensors panel. The typical inverse problem described above is solved numerically, and first simulation results are presented in order to show the validity and the robustness of the proposed approach.
Ala G., Cassarà P., Francomano E., Ganci S.
Imaging techniques give a fundamental support to medical diagnostics during the pathology discovery as well as for the characterization of biological struc- tures. The imaging methods involve electromagnetic waves in a frequency range that spans from some Hz to GHz and over. Most of these methods involve scanning of wide human body areas even if only small areas need to be analyzed. In this paper, a numerical method to evaluate the shape of micro-structures for application in the medical field, with a very low in- vasiveness for the human body, is proposed. A flexible thin-wire antenna radiates the VHF waves and then, by measuring the spatial magnetic field distribution it is possible to reconstruct the micro-structures image by es- timating the location of the antenna against a sensors panel. The typical inverse problem described above is solved numerically, and first simulation results are presented in order to show the validity and the robustness of the proposed approach.
2013
Other
Restricted
Multi-party metering: an architecture for privacy-preserving profiling schemes
Barcellona C., Cassarà P., Di Bella G., Golic J., Tinnirello I.
Several privacy concerns about the massive deploy- ment of smart meters have been arisen recently. Namely, it has been shown that the fine-grained temporal traces generated by these meters can be correlated with different users behaviors. A new architecture, called multi-party metering, for enabling privacy-preserving analysis of high-frequency metering data without requiring additional complexity at the smart meter side is here proposed. The idea is to allow multiple entities to get a share of the high-frequency metering data rather than the real data, where this share does not reveal any information about the real data. By aggregating the shares provided by different users and publishing the results, these entities can statistically analyze the consumption data, without disclosing sensitive information of the users. In particular, it is proposed how to implement a user profiling clustering mechanism in this architecture. The envisaged solution is tested on synthetic electricity consumption data and real gas consumption data.
Barcellona C., Cassarà P., Di Bella G., Golic J., Tinnirello I.
Several privacy concerns about the massive deploy- ment of smart meters have been arisen recently. Namely, it has been shown that the fine-grained temporal traces generated by these meters can be correlated with different users behaviors. A new architecture, called multi-party metering, for enabling privacy-preserving analysis of high-frequency metering data without requiring additional complexity at the smart meter side is here proposed. The idea is to allow multiple entities to get a share of the high-frequency metering data rather than the real data, where this share does not reveal any information about the real data. By aggregating the shares provided by different users and publishing the results, these entities can statistically analyze the consumption data, without disclosing sensitive information of the users. In particular, it is proposed how to implement a user profiling clustering mechanism in this architecture. The envisaged solution is tested on synthetic electricity consumption data and real gas consumption data.
2014
Journal article
Open Access
A numerical method for imaging of biological microstructures by VHF waves
Ala G., Cassarà P., Francomano E., Ganci S., Caruso G., Gallo P. D.
Imaging techniques give a fundamental support to medical diagnostics during the pathology discovery as well as for the characterization of biological struc- tures. The imaging methods involve electromagnetic waves in a frequency range that spans from some Hz to GHz and over. Most of these methods involve scanning of wide human body areas even if only small areas need to be analyzed. In this paper, a numerical method to evaluate the shape of micro-structures for application in the medical field, with a very low in- vasiveness for the human body, is proposed. A flexible thin-wire antenna radiates the VHF waves and then, by measuring the spatial magnetic field distribution it is possible to reconstruct the micro-structures image by es- timating the location of the antenna against a sensors panel. The typical inverse problem described above is solved numerically, and first simulation results are presented in order to show the validity and the robustness of the proposed approach.Source: JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, vol. 259, pp. 805-814
DOI: 10.1016/j.cam.2013.07.020
Metrics:
Ala G., Cassarà P., Francomano E., Ganci S., Caruso G., Gallo P. D.
Imaging techniques give a fundamental support to medical diagnostics during the pathology discovery as well as for the characterization of biological struc- tures. The imaging methods involve electromagnetic waves in a frequency range that spans from some Hz to GHz and over. Most of these methods involve scanning of wide human body areas even if only small areas need to be analyzed. In this paper, a numerical method to evaluate the shape of micro-structures for application in the medical field, with a very low in- vasiveness for the human body, is proposed. A flexible thin-wire antenna radiates the VHF waves and then, by measuring the spatial magnetic field distribution it is possible to reconstruct the micro-structures image by es- timating the location of the antenna against a sensors panel. The typical inverse problem described above is solved numerically, and first simulation results are presented in order to show the validity and the robustness of the proposed approach.Source: JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, vol. 259, pp. 805-814
DOI: 10.1016/j.cam.2013.07.020
Metrics:
See at:
Journal of Computational and Applied Mathematics 
| Archivio istituzionale della ricerca - Università di Palermo | CNR IRIS 
| CNR IRIS | www.sciencedirect.com
2013
Conference article
Restricted
Multi-party metering: an architecture for privacy-preserving profiling schemes
Barcellona C., Cassarà P., Di Bella G., Golic J., Tinnirello I.
Several privacy concerns about the massive deploy- ment of smart meters have been arisen recently. Namely, it has been shown that the fine-grained temporal traces generated by these meters can be correlated with different users behaviors. A new architecture, called multi-party metering, for enabling privacy-preserving analysis of high-frequency metering data without requiring additional complexity at the smart meter side is here proposed. The idea is to allow multiple entities to get a share of the high-frequency metering data rather than the real data, where this share does not reveal any information about the real data. By aggregating the shares provided by different users and publishing the results, these entities can statistically analyze the consumption data, without disclosing sensitive information of the users. In particular, it is proposed how to implement a user profiling clustering mechanism in this architecture. The envisaged solution is tested on synthetic electricity consumption data and real gas consumption data.DOI: 10.1109/sustainit.2013.6685212
Metrics:
Barcellona C., Cassarà P., Di Bella G., Golic J., Tinnirello I.
Several privacy concerns about the massive deploy- ment of smart meters have been arisen recently. Namely, it has been shown that the fine-grained temporal traces generated by these meters can be correlated with different users behaviors. A new architecture, called multi-party metering, for enabling privacy-preserving analysis of high-frequency metering data without requiring additional complexity at the smart meter side is here proposed. The idea is to allow multiple entities to get a share of the high-frequency metering data rather than the real data, where this share does not reveal any information about the real data. By aggregating the shares provided by different users and publishing the results, these entities can statistically analyze the consumption data, without disclosing sensitive information of the users. In particular, it is proposed how to implement a user profiling clustering mechanism in this architecture. The envisaged solution is tested on synthetic electricity consumption data and real gas consumption data.DOI: 10.1109/sustainit.2013.6685212
Metrics:
See at:
doi.org | CNR IRIS | ieeexplore.ieee.org | CNR IRIS
2015
Other
Restricted
A novel mutual information-based feature selection algorithm
Cassarà P., Rozza A.
From a machine learning point of view to identify a subset of relevant features from a real data set can be useful to improve the results achieved by classification methods and to reduce their time and space complexity. To achieve this goal, feature selection methods are usually employed. These approaches assume that the data contains redundant or irrelevant attributes that can be eliminated. In this work we propose a novel feature selection technique that exploits Mutual Information and that is able to automatically estimates the number of dimensions to retain. The main advantages of this new approach are: the ability to automatically estimate the number of features to retain, and the possibility to rank the features to select from the most probable to the less probable. Experiments on standard real data sets and the comparison with state-of-the-art feature selection techniques confirms the high quality of our approach.
Cassarà P., Rozza A.
From a machine learning point of view to identify a subset of relevant features from a real data set can be useful to improve the results achieved by classification methods and to reduce their time and space complexity. To achieve this goal, feature selection methods are usually employed. These approaches assume that the data contains redundant or irrelevant attributes that can be eliminated. In this work we propose a novel feature selection technique that exploits Mutual Information and that is able to automatically estimates the number of dimensions to retain. The main advantages of this new approach are: the ability to automatically estimate the number of features to retain, and the possibility to rank the features to select from the most probable to the less probable. Experiments on standard real data sets and the comparison with state-of-the-art feature selection techniques confirms the high quality of our approach.
2019
Conference article
Restricted
Optimizing adaptive communications in underwater acoustic networks
Petroccia R., Cassarà P., Pelekanakis K.
We consider an Underwater Acoustic Network (UAN) where each node is equipped with a suite of signals and so there is the flexibility to aim for different bit rates at each transmission slot. A Cross-Entropy (CE) centralized algorithm is explored to optimize the combination of modulation scheme and transmission power level in the presence of unreliable channels. Optimization metrics such as throughput, energy per bit, latency and their combination are considered. The motivation for this research stems from the fact that surveillance networks using battery-powered Autonomous Underwater Vehicles (AUVs) need to be able to promptly deliver critical data while prolonging their lifetime and reducing the footprint of their transmissions. The proposed strategy has been validated by post-processing thousands of acoustic signals recorded during the Littoral Acoustic Communications Experiment 2017 (LACE17) sea trial in the Gulf of La Spezia, Italy. Our analysis shows the trade-off between the bit rate and the transmission power given the selected optimization metrics. The solution computed when combining all the considered metrics makes possible to improve up to three times the throughput performance and up to one order of magnitude the energy consumption with respect to considering single other optimization metrics.DOI: 10.23919/oceans40490.2019.8962398
Metrics:
Petroccia R., Cassarà P., Pelekanakis K.
We consider an Underwater Acoustic Network (UAN) where each node is equipped with a suite of signals and so there is the flexibility to aim for different bit rates at each transmission slot. A Cross-Entropy (CE) centralized algorithm is explored to optimize the combination of modulation scheme and transmission power level in the presence of unreliable channels. Optimization metrics such as throughput, energy per bit, latency and their combination are considered. The motivation for this research stems from the fact that surveillance networks using battery-powered Autonomous Underwater Vehicles (AUVs) need to be able to promptly deliver critical data while prolonging their lifetime and reducing the footprint of their transmissions. The proposed strategy has been validated by post-processing thousands of acoustic signals recorded during the Littoral Acoustic Communications Experiment 2017 (LACE17) sea trial in the Gulf of La Spezia, Italy. Our analysis shows the trade-off between the bit rate and the transmission power given the selected optimization metrics. The solution computed when combining all the considered metrics makes possible to improve up to three times the throughput performance and up to one order of magnitude the energy consumption with respect to considering single other optimization metrics.DOI: 10.23919/oceans40490.2019.8962398
Metrics:
See at:
doi.org | CNR IRIS | ieeexplore.ieee.org | CNR IRIS
2016
Other
Restricted
Relazione ASIMOV
Cassarà P.
Progetto MONSTER-Nel documento è presentata la progettazione e la realizzazione del sistema di acquisizione basato su accelerometri MEMS, denominato ASIMOV.
Cassarà P.
Progetto MONSTER-Nel documento è presentata la progettazione e la realizzazione del sistema di acquisizione basato su accelerometri MEMS, denominato ASIMOV.
2020
Journal article
Open Access
The Internet of Ships
Martelli M., Cassarà P., Virdis A., Tonellotto N.
A distributed computing platform can provide automatic control for maritime services, with likely economic and social benefits. In this context, the nodes involved in the computing tasks are autonomous complex cyber-physical systems, i.e., ships. The platform allows node computing cooperation through a high-level abstraction of the underlying sensor system. The computing tasks are related to the predictive analysis, employing artificial intelligence (AI) techniques based on the federated-learning paradigm.Source: ERCIM NEWS, pp. 17-18
Martelli M., Cassarà P., Virdis A., Tonellotto N.
A distributed computing platform can provide automatic control for maritime services, with likely economic and social benefits. In this context, the nodes involved in the computing tasks are autonomous complex cyber-physical systems, i.e., ships. The platform allows node computing cooperation through a high-level abstraction of the underlying sensor system. The computing tasks are related to the predictive analysis, employing artificial intelligence (AI) techniques based on the federated-learning paradigm.Source: ERCIM NEWS, pp. 17-18
See at:
ercim-news.ercim.eu | CNR IRIS | ISTI Repository | CNR IRIS
2018
Other
Restricted
Communication architecture for command and control systems (C2) in maritime environment, through machine-to-machine (M2M) technologies
Cassarà P.
Nel documento è presentata la descrizione del sistema: "infrastruttura di comunicazione" sottostante il sistema denominato Virtual Bridge che permette ad un operatore del ponte di una nave di avere a propria disposizione su un display di un dispositivo indomabile tipo OCULUS i dati riguardanti i parametri di una nave e dell'ambiente circostante attraverso l'ausilio della realtà aumentata. Alla base del sistema le informazioni sono veicolate da una rete di sensori basata su paradigma IoT che fa uso di un protocollo MQTT.
Cassarà P.
Nel documento è presentata la descrizione del sistema: "infrastruttura di comunicazione" sottostante il sistema denominato Virtual Bridge che permette ad un operatore del ponte di una nave di avere a propria disposizione su un display di un dispositivo indomabile tipo OCULUS i dati riguardanti i parametri di una nave e dell'ambiente circostante attraverso l'ausilio della realtà aumentata. Alla base del sistema le informazioni sono veicolate da una rete di sensori basata su paradigma IoT che fa uso di un protocollo MQTT.
2015
Journal article
Open Access
Load match optimisation of a residential building case study: A cross-entropy based electricity storage sizing algorithm
Guarino F., Cassarà P., Longo S., Cellura M., Ferro E.
The EU EPBD recast regulation marked the application of the net zero energy building (Net ZEB) concept in all fields of building construction in Europe as a building able to generate as much energy as it con- sumes over a selected time frame. A more detailed insight is however needed, as even if a building achieves a long-term energy balance between energy generated and consumed, smaller time scales must also be considered. For example, from the utility's point of view, if a Net ZEB is a heavy consumer in the winter, it will appear to be quite similar to a conventional building, requiring the use of additional gen- eration. The increase in the generation-load match means reducing the stress to the energy grid, the peak system energy required, and the wasted energy, thus avoiding unnecessary generation and, consequently, limiting carbon-related emissions. In this paper, the authors address the problem of determining the optimal storage size starting from the data of an Italian nearly net zero energy building that produced a detailed database on generated and consumed electricity. The study presented in this paper analyses the following steps: modelling of energy consumption through non-parametric estimators, modelling of energy generation through detailed models available in the literature, quantification of the load match levels for existing case studies, analysis of the state of charge (SOC) for a given model of the energy consumption probability distribution, and the identifica- tion of the minimum size of the storage required to improve energy load match. The results show that even when selecting unfavourable boundary conditions it could be possible to lower the energy import from the electricity grid by approximately 40%, that can possibly rise to more than 90% during summer.Source: APPLIED ENERGY, vol. 154, pp. 380-391
DOI: 10.1016/j.apenergy.2015.04.116
Metrics:
Guarino F., Cassarà P., Longo S., Cellura M., Ferro E.
The EU EPBD recast regulation marked the application of the net zero energy building (Net ZEB) concept in all fields of building construction in Europe as a building able to generate as much energy as it con- sumes over a selected time frame. A more detailed insight is however needed, as even if a building achieves a long-term energy balance between energy generated and consumed, smaller time scales must also be considered. For example, from the utility's point of view, if a Net ZEB is a heavy consumer in the winter, it will appear to be quite similar to a conventional building, requiring the use of additional gen- eration. The increase in the generation-load match means reducing the stress to the energy grid, the peak system energy required, and the wasted energy, thus avoiding unnecessary generation and, consequently, limiting carbon-related emissions. In this paper, the authors address the problem of determining the optimal storage size starting from the data of an Italian nearly net zero energy building that produced a detailed database on generated and consumed electricity. The study presented in this paper analyses the following steps: modelling of energy consumption through non-parametric estimators, modelling of energy generation through detailed models available in the literature, quantification of the load match levels for existing case studies, analysis of the state of charge (SOC) for a given model of the energy consumption probability distribution, and the identifica- tion of the minimum size of the storage required to improve energy load match. The results show that even when selecting unfavourable boundary conditions it could be possible to lower the energy import from the electricity grid by approximately 40%, that can possibly rise to more than 90% during summer.Source: APPLIED ENERGY, vol. 154, pp. 380-391
DOI: 10.1016/j.apenergy.2015.04.116
Metrics:
See at:
CNR IRIS | ISTI Repository | www.sciencedirect.com | Applied Energy | CNR IRIS | CNR IRIS
2015
Contribution to conference
Open Access
Il progetto MONSTER: monitoraggio strutturale di edifici storici con tecnologie wireless e strumenti di calcolo innovativi
Cassarà P., Pellegrini D.
MONSTER - Structural health monitoring of historic buildings via wireless sensor networks and numerical tools The project aims at developing an integrated monitoring and simulation framework for the structural health control of ancient masonry constructions. Sensing will be based on small, inexpensive and interconnected wireless devices, developed by the Wireless Network Lab of ISTI-CNR. The data produced become the input for numerical simulations based on the NOSA-ITACA code, a finite-element software developed by the Mechanics of Materials and Structures Lab of ISTI-CNR to simulate the static and dynamic behaviour of masonry buildings, while taking into account the effects of cracking. The project's activities include some laboratory tests on the prototypes and the installation of a wireless accelerometer network on a monument in Lucca.
Cassarà P., Pellegrini D.
MONSTER - Structural health monitoring of historic buildings via wireless sensor networks and numerical tools The project aims at developing an integrated monitoring and simulation framework for the structural health control of ancient masonry constructions. Sensing will be based on small, inexpensive and interconnected wireless devices, developed by the Wireless Network Lab of ISTI-CNR. The data produced become the input for numerical simulations based on the NOSA-ITACA code, a finite-element software developed by the Mechanics of Materials and Structures Lab of ISTI-CNR to simulate the static and dynamic behaviour of masonry buildings, while taking into account the effects of cracking. The project's activities include some laboratory tests on the prototypes and the installation of a wireless accelerometer network on a monument in Lucca.
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2018
Conference article
Restricted
How to support the machine learning take-off: challenges and hints for achieving intelligent UAVS
Dazzi P., Cassarà P.
Unmanned Aerial Vehicles (UAVs) are getting momentum. A growing number of industries and scientific institutions are focusing on these devices. UAVs can be used for a really wide spectrum of civilian and military applications. Usually these devices run on batteries, thus it is fundamental to efficiently exploit their hardware to reduce their energy footprint. A key aspect in facing the "energy issue" is the exploitation of properly designed solutions in order to target the energy-and hardware-constraints characterising these devices. However, there are not universal approaches easing the implementation of ad-hoc solutions for UAVs; it just depends on the class of problems to be faced. As matter of fact, targeting machine-learning solutions to UAVs could foster the development of a wide range of interesting application. This contribution is aimed at sketching the challenges deriving from the porting of machine-learning solutions, and the associated requirements, to highly distributed, constrained, inter-connected devices, highlighting the issues that could hinder their exploitation for UAVs.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING, pp. 106-114. Oxford, UK, 14-15 September 2017
DOI: 10.1007/978-3-319-76571-6_11
Metrics:
Dazzi P., Cassarà P.
Unmanned Aerial Vehicles (UAVs) are getting momentum. A growing number of industries and scientific institutions are focusing on these devices. UAVs can be used for a really wide spectrum of civilian and military applications. Usually these devices run on batteries, thus it is fundamental to efficiently exploit their hardware to reduce their energy footprint. A key aspect in facing the "energy issue" is the exploitation of properly designed solutions in order to target the energy-and hardware-constraints characterising these devices. However, there are not universal approaches easing the implementation of ad-hoc solutions for UAVs; it just depends on the class of problems to be faced. As matter of fact, targeting machine-learning solutions to UAVs could foster the development of a wide range of interesting application. This contribution is aimed at sketching the challenges deriving from the porting of machine-learning solutions, and the associated requirements, to highly distributed, constrained, inter-connected devices, highlighting the issues that could hinder their exploitation for UAVs.Source: LECTURE NOTES OF THE INSTITUTE FOR COMPUTER SCIENCES, SOCIAL INFORMATICS AND TELECOMMUNICATIONS ENGINEERING, pp. 106-114. Oxford, UK, 14-15 September 2017
DOI: 10.1007/978-3-319-76571-6_11
Metrics:
See at:
doi.org | CNR IRIS | CNR IRIS | link.springer.com
2020
Journal article
Open Access
A Statistical Framework for Performance Analysis of Diversity Framed Slotted Aloha With Interference Cancellation
Cassarà P., Gotta A., De Cola T.
As the Internet of Things (IoT)/machine-to-machine market is rapidly growing, a special role is expected to be played by satellite communications in that they offer ubiquitous coverage and therefore enable typical monitoring, telemetry, and control services also in areas with a poor terrestrial infrastructure. In this respect, the case of massive IoT devices deployment calls for random access solutions, which have been long analyzed by the scientific satellite community in the last ten years. This article further elaborates on the relation between the normalized offered load and the achievable performance in terms of packet loss rate, which was not much addressed so far at high loads. The proposed theoretical framework has been validated through extensive simulation campaigns, which show an excellent match at different loads and number of interfering packets configurations, by significantly improving the results achievable through other existing theoretical frameworks.Source: IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, vol. 56 (issue 6), pp. 4327-4337
DOI: 10.1109/taes.2020.2989068
Metrics:
Cassarà P., Gotta A., De Cola T.
As the Internet of Things (IoT)/machine-to-machine market is rapidly growing, a special role is expected to be played by satellite communications in that they offer ubiquitous coverage and therefore enable typical monitoring, telemetry, and control services also in areas with a poor terrestrial infrastructure. In this respect, the case of massive IoT devices deployment calls for random access solutions, which have been long analyzed by the scientific satellite community in the last ten years. This article further elaborates on the relation between the normalized offered load and the achievable performance in terms of packet loss rate, which was not much addressed so far at high loads. The proposed theoretical framework has been validated through extensive simulation campaigns, which show an excellent match at different loads and number of interfering packets configurations, by significantly improving the results achievable through other existing theoretical frameworks.Source: IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, vol. 56 (issue 6), pp. 4327-4337
DOI: 10.1109/taes.2020.2989068
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | ISTI Repository | IEEE Transactions on Aerospace and Electronic Systems | CNR IRIS | CNR IRIS | CNR IRIS
2021
Journal article
Open Access
An outlook on the future marine traffic management system for autonomous ships
Martelli M., Virdis A., Gotta A., Cassarà P., Di Summa M.
In the shipping digitalisation process, the peak will be reached with the advent of a wholly autonomous and at the same time safe and reliable ship. Full autonomy could be obtained by two linked Artificial-Intelligence systems representing the ship navigator and the ship engineer that possess sensing and analysis skills, situational awareness, planning, and control capabilities. Many efforts have been made in developing onboard systems; however, the shore facilities are not ready yet to deal with these new technologies. The paper aims to present the innovative technologies and methodologies needed to develop a futuristic Vessel Traffic System. The proposed systems will aim at faultless data acquisition and processing, provide input to decision-making systems, and suggest evasive manoeuvre; to deal with hazards and systems failure without human intervention onboard. The system is composed of three different and interacting layers. The first is an artificially intelligent tool to detect and control autonomous ships, thanks to situation recognition and obstacle avoidance strategies. The second is an orchestration and management platform designed to coordinate the sensing/actuation infrastructure and the AI algorithms' results made available by multiple ships, mustering edge, and distributed computing techniques to fulfil the specific harsh requirements of the sea environment. The final part is a holistic guidance-navigation-control framework to manage autonomous ships' navigation in a crowded area. Eventually, a cyber-physical scenario, using both a ship digital-twin and a real model-scale ship, is suggested to test and validate the innovative system without the availability of a full-scale scenario.Source: IEEE ACCESS, vol. 9, pp. 157316-157328
DOI: 10.1109/access.2021.3130741
Metrics:
Martelli M., Virdis A., Gotta A., Cassarà P., Di Summa M.
In the shipping digitalisation process, the peak will be reached with the advent of a wholly autonomous and at the same time safe and reliable ship. Full autonomy could be obtained by two linked Artificial-Intelligence systems representing the ship navigator and the ship engineer that possess sensing and analysis skills, situational awareness, planning, and control capabilities. Many efforts have been made in developing onboard systems; however, the shore facilities are not ready yet to deal with these new technologies. The paper aims to present the innovative technologies and methodologies needed to develop a futuristic Vessel Traffic System. The proposed systems will aim at faultless data acquisition and processing, provide input to decision-making systems, and suggest evasive manoeuvre; to deal with hazards and systems failure without human intervention onboard. The system is composed of three different and interacting layers. The first is an artificially intelligent tool to detect and control autonomous ships, thanks to situation recognition and obstacle avoidance strategies. The second is an orchestration and management platform designed to coordinate the sensing/actuation infrastructure and the AI algorithms' results made available by multiple ships, mustering edge, and distributed computing techniques to fulfil the specific harsh requirements of the sea environment. The final part is a holistic guidance-navigation-control framework to manage autonomous ships' navigation in a crowded area. Eventually, a cyber-physical scenario, using both a ship digital-twin and a real model-scale ship, is suggested to test and validate the innovative system without the availability of a full-scale scenario.Source: IEEE ACCESS, vol. 9, pp. 157316-157328
DOI: 10.1109/access.2021.3130741
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | ISTI Repository | ISTI Repository | CNR IRIS | CNR IRIS
2021
Other
Metadata Only Access
Orbital edge offloading on mega-LEO constellations for equal access to computing
Cassarà P., Gotta A., Marchese M., Patrone F.
Mega-LEO satellite constellations are becoming a concrete reality. Companies such as SpaceX, Virgin Orbit, and OneWeb have already started launching hundreds of LEO satellites and are turning their services on. Even if the aim of such LEO satellite constellations is just, for now, to offer worldwide Internet access equality, their deployment proves their feasibility and suggests usefulness for further purposes. In this article, we shed some light on the possible integration of the in-network computing paradigm in Mega-LEO satellite constellations. Terrestrial and/or non-terrestrial nodes can benefit from offloading the computing to an Orbital Edge platform reachable through the satellite constellation, exploiting its fast and distributed computational capability. In this context, a preliminary analysis highlights that task offloading strategies can lead to performance improvements that open to novel challenges about the design and set up of Orbital Edge platforms.
Cassarà P., Gotta A., Marchese M., Patrone F.
Mega-LEO satellite constellations are becoming a concrete reality. Companies such as SpaceX, Virgin Orbit, and OneWeb have already started launching hundreds of LEO satellites and are turning their services on. Even if the aim of such LEO satellite constellations is just, for now, to offer worldwide Internet access equality, their deployment proves their feasibility and suggests usefulness for further purposes. In this article, we shed some light on the possible integration of the in-network computing paradigm in Mega-LEO satellite constellations. Terrestrial and/or non-terrestrial nodes can benefit from offloading the computing to an Orbital Edge platform reachable through the satellite constellation, exploiting its fast and distributed computational capability. In this context, a preliminary analysis highlights that task offloading strategies can lead to performance improvements that open to novel challenges about the design and set up of Orbital Edge platforms.
See at:
CNR IRIS
2022
Journal article
Open Access
Orbital edge offloading on mega-LEO satellite constellations for equal access to computing
Cassarà P., Gotta A., Marchese M., Patrone F.
Mega-LEO satellite constellations are becoming a concrete reality. Companies such as SpaceX, Virgin Orbit, and OneWeb have already started launching hundreds of LEO satellites and are turning their services on. Even if the aim of such LEO satellite constellations is just, for now, to offer worldwide Internet access equality, their deployment proves their feasibility and suggests usefulness for further purposes. In this article, we shed some light on the possible integration of the in-network computing paradigm in mega-LEO satellite constellations. Terrestrial and/or non-terrestrial nodes can benefit from offloading the computing to an orbital edge (OE) platform reachable through the satellite constellation, exploiting its fast and distributed computational capability. In this context, a preliminary analysis highlights that task offloading strategies can lead to performance improvements that open up novel challenges in the design and setup of OE platforms.Source: IEEE COMMUNICATIONS MAGAZINE (PRINT), vol. 60 (issue 4), pp. 32-36
DOI: 10.1109/mcom.001.2100818
Metrics:
Cassarà P., Gotta A., Marchese M., Patrone F.
Mega-LEO satellite constellations are becoming a concrete reality. Companies such as SpaceX, Virgin Orbit, and OneWeb have already started launching hundreds of LEO satellites and are turning their services on. Even if the aim of such LEO satellite constellations is just, for now, to offer worldwide Internet access equality, their deployment proves their feasibility and suggests usefulness for further purposes. In this article, we shed some light on the possible integration of the in-network computing paradigm in mega-LEO satellite constellations. Terrestrial and/or non-terrestrial nodes can benefit from offloading the computing to an orbital edge (OE) platform reachable through the satellite constellation, exploiting its fast and distributed computational capability. In this context, a preliminary analysis highlights that task offloading strategies can lead to performance improvements that open up novel challenges in the design and setup of OE platforms.Source: IEEE COMMUNICATIONS MAGAZINE (PRINT), vol. 60 (issue 4), pp. 32-36
DOI: 10.1109/mcom.001.2100818
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | ISTI Repository | IEEE Communications Magazine | CNR IRIS | CNR IRIS | CNR IRIS
2022
Conference article
Open Access
Exploring Machine Learning for classification of QUIC flows over satellite
Secchi R., Cassarà P., Gotta A.
Automatic traffic classification is increasingly important in networking due to the current trend of encrypting transport information (e.g., behind HTTP encrypted tunnels) which prevent intermediate nodes to access end-to-end transport headers. This paper proposes an architecture for supporting Quality of Service (QoS) in hybrid terrestrial and SATCOM networks based on automated traffic classification. Traffic profiles are constructed by machine-learning (ML) algorithms using the series of packet sizes and arrival times of QUIC connections. Thus, the proposed QoS method does not require explicit setup of a path (i.e. it provides soft QoS), but employs agents within the network to verify that flows conform to a given traffic profile. Results over a range of ML models encourage integrating ML technology in SATCOM equipment. The availability of higher computation power at low-cost creates the fertile ground for implementation of these techniques.DOI: 10.1109/icc45855.2022.9838463
Metrics:
Secchi R., Cassarà P., Gotta A.
Automatic traffic classification is increasingly important in networking due to the current trend of encrypting transport information (e.g., behind HTTP encrypted tunnels) which prevent intermediate nodes to access end-to-end transport headers. This paper proposes an architecture for supporting Quality of Service (QoS) in hybrid terrestrial and SATCOM networks based on automated traffic classification. Traffic profiles are constructed by machine-learning (ML) algorithms using the series of packet sizes and arrival times of QUIC connections. Thus, the proposed QoS method does not require explicit setup of a path (i.e. it provides soft QoS), but employs agents within the network to verify that flows conform to a given traffic profile. Results over a range of ML models encourage integrating ML technology in SATCOM equipment. The availability of higher computation power at low-cost creates the fertile ground for implementation of these techniques.DOI: 10.1109/icc45855.2022.9838463
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CNR IRIS | ieeexplore.ieee.org | ISTI Repository | CNR IRIS | CNR IRIS
2023
Journal article
Open Access
Towards a fully-observable Markov decision process with generative models for integrated 6G-non-terrestrial networks
Machumilane A., Cassarà P., Gotta A.
The upcoming sixth generation (6G) mobile networks require integration between terrestrial mobile networks and non-terrestrial networks (NTN) such as satellites and high altitude platforms (HAPs) to ensure wide and ubiquitous coverage, high connection density, reliable communications and high data rates. The main challenge in this integration is the requirement for line-of-sight (LOS) communication between the user equipment (UE) and the satellite. In this paper, we propose a framework based on actorcritic reinforcement learning and generative models for LOS estimation and traffic scheduling on multiple links connecting a user equipment to multiple satellites in 6G-NTN integrated networks. The agent learns to estimate the LOS probabilities of the available channels and schedules traffic on appropriate links to minimise end-to-end losses with minimal bandwidth. The learning process is modelled as a partially observable Markov decision process (POMDP), since the agent can only observe the state of the channels it has just accessed. As a result, the learning agent requires a longer convergence time compared to the satellite visibility period at a given satellite elevation angle. To counteract this slow convergence, we use generative models to transform a POMDP into a fully observable Markov decision process (FOMDP). We use generative adversarial networks (GANs) and variational autoencoders (VAEs) to generate synthetic channel states of the channels that are not selected by the agent during the learning process, allowing the agent to have complete knowledge of all channels, including those that are not accessed, thus speeding up the learning process. The simulation results show that our framework enables the agent to converge in a short time and transmit with an optimal policy for most of the satellite visibility period, which significantly reduces end-to-end losses and saves bandwidth. We also show that it is possible to train generative models in real time without requiring prior knowledge of the channel models and without slowing down the learning process or affecting the accuracy of the models.Source: IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, vol. 4, pp. 1913-1930
DOI: 10.1109/ojcoms.2023.3307209
Project(s): TRANTOR
, RESTART, Sustainable Mobility National Research Center
Metrics:
Machumilane A., Cassarà P., Gotta A.
The upcoming sixth generation (6G) mobile networks require integration between terrestrial mobile networks and non-terrestrial networks (NTN) such as satellites and high altitude platforms (HAPs) to ensure wide and ubiquitous coverage, high connection density, reliable communications and high data rates. The main challenge in this integration is the requirement for line-of-sight (LOS) communication between the user equipment (UE) and the satellite. In this paper, we propose a framework based on actorcritic reinforcement learning and generative models for LOS estimation and traffic scheduling on multiple links connecting a user equipment to multiple satellites in 6G-NTN integrated networks. The agent learns to estimate the LOS probabilities of the available channels and schedules traffic on appropriate links to minimise end-to-end losses with minimal bandwidth. The learning process is modelled as a partially observable Markov decision process (POMDP), since the agent can only observe the state of the channels it has just accessed. As a result, the learning agent requires a longer convergence time compared to the satellite visibility period at a given satellite elevation angle. To counteract this slow convergence, we use generative models to transform a POMDP into a fully observable Markov decision process (FOMDP). We use generative adversarial networks (GANs) and variational autoencoders (VAEs) to generate synthetic channel states of the channels that are not selected by the agent during the learning process, allowing the agent to have complete knowledge of all channels, including those that are not accessed, thus speeding up the learning process. The simulation results show that our framework enables the agent to converge in a short time and transmit with an optimal policy for most of the satellite visibility period, which significantly reduces end-to-end losses and saves bandwidth. We also show that it is possible to train generative models in real time without requiring prior knowledge of the channel models and without slowing down the learning process or affecting the accuracy of the models.Source: IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, vol. 4, pp. 1913-1930
DOI: 10.1109/ojcoms.2023.3307209
Project(s): TRANTOR
, RESTART, Sustainable Mobility National Research CenterMetrics:
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CNR IRIS | ieeexplore.ieee.org | ISTI Repository | CNR IRIS
2023
Journal article
Open Access
E-Navigation: a distributed decision support system with extended reality for bridge and ashore seafarers
Cassarà P., Di Summa M., Gotta A., Martelli M.
A distributed decision support system has beendeveloped to assist seafarers during several navigation tasks, forinstance, in avoiding a collision with a detected obstacle in the seaand envisioning a future autonomous navigation system. In thispaper, the decision support system is based on the results ofa customized simulation model representing the ship's behavior,including hydrodynamics, propulsion, and control effects. Sensorsmonitor and collect the parameters of the environment andthe ship onboard. The telemetry and the calculated route arevisualized on a wearable visor exploiting augmented reality.Such context information is also replicated ashore through anarrow-band satellite link using an IoT publish-subscribe communicationparadigm to allow one or more remote seafarers tosupervise the situation in a virtual reality environment. Overall,the potential of the proposed system is presented and discussedfor application in the context of autonomous navigation.Source: IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (ONLINE), vol. 24 (issue 11), pp. 13384-13395
DOI: 10.1109/tits.2023.3311817
Metrics:
Cassarà P., Di Summa M., Gotta A., Martelli M.
A distributed decision support system has beendeveloped to assist seafarers during several navigation tasks, forinstance, in avoiding a collision with a detected obstacle in the seaand envisioning a future autonomous navigation system. In thispaper, the decision support system is based on the results ofa customized simulation model representing the ship's behavior,including hydrodynamics, propulsion, and control effects. Sensorsmonitor and collect the parameters of the environment andthe ship onboard. The telemetry and the calculated route arevisualized on a wearable visor exploiting augmented reality.Such context information is also replicated ashore through anarrow-band satellite link using an IoT publish-subscribe communicationparadigm to allow one or more remote seafarers tosupervise the situation in a virtual reality environment. Overall,the potential of the proposed system is presented and discussedfor application in the context of autonomous navigation.Source: IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (ONLINE), vol. 24 (issue 11), pp. 13384-13395
DOI: 10.1109/tits.2023.3311817
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CNR IRIS | ieeexplore.ieee.org | ISTI Repository | IEEE Transactions on Intelligent Transportation Systems | CNR IRIS | CNR IRIS
2018
Conference article
Open Access
Enhanced navigation at sea: an augmented reality-based tool for bridge operators
Martelli M., Figari M., Di Summa M., Viganò G. P., Sacco M., Cassarà P., Gotta A., Sebastiani L., Delucchi G., Guglia P.
This paper presents the design framework, in which a Decision Support System (DSS) tool has been developed to assist the bridge operator during a challenging navigation condition. The present project would be another step for using state of the art, IT devices and hardware, to increase safety at sea mainly focusing on both collision and grounding avoidance. In this paper, the modules to detect an obstacle and to calculate the evasive route are based on a customized simulation model: such a model is able to represent the dynamic behaviour of a ship, including hydrodynamics, propulsion, and control effects. The suggested route selected by the decision support system and some environmental parameters coupled with some of the ship parameters are visualized on a smart "virtual bridge" exploiting virtual reality techniques. A suitable graphical interface has been developed and installed, in order to enhance the situation awareness. The project also focuses on the communication architecture, which relies on a publish-subscribe paradigm and is responsible to forward ship control parameters both to the virtual bridge and towards an ashore control centre, either for supervising or for remote control.Overall, both the potentiality and the limits of the proposed system have been critically discussed.DOI: 10.24868/issn.2515-818x.2018.017
Metrics:
Martelli M., Figari M., Di Summa M., Viganò G. P., Sacco M., Cassarà P., Gotta A., Sebastiani L., Delucchi G., Guglia P.
This paper presents the design framework, in which a Decision Support System (DSS) tool has been developed to assist the bridge operator during a challenging navigation condition. The present project would be another step for using state of the art, IT devices and hardware, to increase safety at sea mainly focusing on both collision and grounding avoidance. In this paper, the modules to detect an obstacle and to calculate the evasive route are based on a customized simulation model: such a model is able to represent the dynamic behaviour of a ship, including hydrodynamics, propulsion, and control effects. The suggested route selected by the decision support system and some environmental parameters coupled with some of the ship parameters are visualized on a smart "virtual bridge" exploiting virtual reality techniques. A suitable graphical interface has been developed and installed, in order to enhance the situation awareness. The project also focuses on the communication architecture, which relies on a publish-subscribe paradigm and is responsible to forward ship control parameters both to the virtual bridge and towards an ashore control centre, either for supervising or for remote control.Overall, both the potentiality and the limits of the proposed system have been critically discussed.DOI: 10.24868/issn.2515-818x.2018.017
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