2013
Report
Unknown
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.Source: ISTI Technical reports, 2013
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.Source: ISTI Technical reports, 2013
See at: CNR ExploRA
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 259 (2014): 805–814. doi:10.1016/j.cam.2013.07.020
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 259 (2014): 805–814. doi:10.1016/j.cam.2013.07.020
DOI: 10.1016/j.cam.2013.07.020
Metrics:
See at:
Journal of Computational and Applied Mathematics 
| Archivio istituzionale della ricerca - Università di Palermo | www.sciencedirect.com 
| CNR ExploRA
2015
Report
Unknown
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.Source: ISTI Technical reports, 2015
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.Source: ISTI Technical reports, 2015
See at: CNR ExploRA
2019
Conference article
Closed Access
Optimizing adaptive communications in underwater acoustic networks
Petroccia R., Cassara 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.Source: OCEANS 2019 - MTS/IEEE SEATTLE, Seattle, United States, 27-31 October, 2019
DOI: 10.23919/oceans40490.2019.8962398
Metrics:
Petroccia R., Cassara 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.Source: OCEANS 2019 - MTS/IEEE SEATTLE, Seattle, United States, 27-31 October, 2019
DOI: 10.23919/oceans40490.2019.8962398
Metrics:
See at:
doi.org | ieeexplore.ieee.org | CNR ExploRA
2016
Other
Unknown
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.
See at: CNR ExploRA
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 (2020): 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 (2020): 17–18.
See at:
ercim-news.ercim.eu | ISTI Repository | CNR ExploRA
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 154 (2015): 380–391. doi:10.1016/j.apenergy.2015.04.116
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 154 (2015): 380–391. doi:10.1016/j.apenergy.2015.04.116
DOI: 10.1016/j.apenergy.2015.04.116
Metrics:
See at:
ISTI Repository | Applied Energy | www.sciencedirect.com | CNR ExploRA
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.Source: BRIGHT 2015 - BRIGHT Toscana 2015 - La notte dei ricercatori, Pisa, Italy, 25 settembre 2015
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.Source: BRIGHT 2015 - BRIGHT Toscana 2015 - La notte dei ricercatori, Pisa, Italy, 25 settembre 2015
See at:
ISTI Repository | CNR ExploRA
2018
Conference article
Closed Access
How to support the machine learning take-off: challenges and hints for achieving intelligent UAVS
Dazzi P., Cassara 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: WiSATS 2017 - 9th International Conference on Wireless and Satellite Systems, pp. 106–114, Oxford, UK, 14-15 September 2017
DOI: 10.1007/978-3-319-76571-6_11
Metrics:
Dazzi P., Cassara 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: WiSATS 2017 - 9th International Conference on Wireless and Satellite Systems, pp. 106–114, Oxford, UK, 14-15 September 2017
DOI: 10.1007/978-3-319-76571-6_11
Metrics:
See at:
doi.org | link.springer.com | CNR ExploRA
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 56 (2020): 4327–4337. doi:10.1109/TAES.2020.2989068
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 56 (2020): 4327–4337. doi:10.1109/TAES.2020.2989068
DOI: 10.1109/taes.2020.2989068
Metrics:
See at:
ISTI Repository | IEEE Transactions on Aerospace and Electronic Systems | ieeexplore.ieee.org | CNR ExploRA
2021
Report
Unknown
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.Source: ISTI Working Paper, 2021
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.Source: ISTI Working Paper, 2021
See at: CNR ExploRA
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) 60 (2022): 32–36. doi:10.1109/MCOM.001.2100818
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) 60 (2022): 32–36. doi:10.1109/MCOM.001.2100818
DOI: 10.1109/mcom.001.2100818
Metrics:
See at:
ISTI Repository | IEEE Communications Magazine | ieeexplore.ieee.org | CNR ExploRA
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.Source: ICC 2022 - IEEE International Conference on Communications, pp. 4709–4714, Seoul, Korea, 16-20/05/2022
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.Source: ICC 2022 - IEEE International Conference on Communications, pp. 4709–4714, Seoul, Korea, 16-20/05/2022
DOI: 10.1109/icc45855.2022.9838463
Metrics:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
2023
Journal article
Open Access
Towards a fully-observable Markov decision process with generative models for integrated 6G-non-terrestrial networks
Machumilane A., Cassara 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 4 (2023): 1913–1930. doi:10.1109/OJCOMS.2023.3307209
DOI: 10.1109/ojcoms.2023.3307209
Metrics:
Machumilane A., Cassara 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 4 (2023): 1913–1930. doi:10.1109/OJCOMS.2023.3307209
DOI: 10.1109/ojcoms.2023.3307209
Metrics:
See at:
ieeexplore.ieee.org | ISTI Repository | CNR ExploRA
2013
Report
Unknown
Single-channel versus multi-channel scanning in device-free indoor radio localization
Barsocchi P., Cassarà P., Nepa P., Potortì F.
Indoor localization systems that involve Wireless Sensor Networks (WSNs) identify the target position by mea- suring the Received Signal Strength (RSS), the Time of Arrival (ToA), the Time Difference of Arrival (TDoA) or the Angle of Arrival (AoA). Of these, the most promising for low-cost applications are those based on RSS measures, which exploit approximate path loss models, or more reliably the relationship between the multi-path interference (shadowing) and the target position. These methods can work with WSNs based on Wi-Fi, Bluetooth and ZigBee wireless technologies. In this paper we concentrate on device-free RSS-based indoor localization methods. These methods, which have generated much research interest in the last few years, are now starting to hit the market. Specifically, the purpose of this paper is to assess the perfor- mance improvements of a Variance-based Radio Tomographic Imaging technique, when scanning various radio channels with respect to using only one, the latter being the "minimum introduced interference" option. In our setup, the data used for target localization are captured by wireless sensors deployed in the localization area, which are in line of sight among them. The localization error metrics include the mean square error and percentiles of the error distribution.Source: ISTI Technical reports, 2013
Project(s): UNIVERSAAL
Barsocchi P., Cassarà P., Nepa P., Potortì F.
Indoor localization systems that involve Wireless Sensor Networks (WSNs) identify the target position by mea- suring the Received Signal Strength (RSS), the Time of Arrival (ToA), the Time Difference of Arrival (TDoA) or the Angle of Arrival (AoA). Of these, the most promising for low-cost applications are those based on RSS measures, which exploit approximate path loss models, or more reliably the relationship between the multi-path interference (shadowing) and the target position. These methods can work with WSNs based on Wi-Fi, Bluetooth and ZigBee wireless technologies. In this paper we concentrate on device-free RSS-based indoor localization methods. These methods, which have generated much research interest in the last few years, are now starting to hit the market. Specifically, the purpose of this paper is to assess the perfor- mance improvements of a Variance-based Radio Tomographic Imaging technique, when scanning various radio channels with respect to using only one, the latter being the "minimum introduced interference" option. In our setup, the data used for target localization are captured by wireless sensors deployed in the localization area, which are in line of sight among them. The localization error metrics include the mean square error and percentiles of the error distribution.Source: ISTI Technical reports, 2013
Project(s): UNIVERSAAL
See at: CNR ExploRA
2013
Contribution to book
Restricted
Generalized encoding CRDSA: maximizing throughput in enhanced random access schemes for satellite
Bacco F. M., Cassarà P., Ferro E., Gotta A.
This work starts from the analysis of the literature about the Random Access protocols with contention resolution as Contention Resolution Diversity Slotted Aloha (CRDSA) and introduces a possible enhancement, named Gener- alized Contention Resolution Diversity Slotted Aloha (GE-CRDSA). The GE- CRDSA aims to improve the aggregated throughput when the system load is less than 50%, playing on the opportunity of transmitting an optimal combination of information and parity packets frame by frame.Source: Personal Satellite Services. Revised Selected Papers, edited by Riadh Dhaou, André-Luc Beylot, Marie-José Montpetit, Daniel Enrique Lucani, Lorenzo Mucchi, pp. 115–122, 2013
DOI: 10.1007/978-3-319-02762-3
Metrics:
Bacco F. M., Cassarà P., Ferro E., Gotta A.
This work starts from the analysis of the literature about the Random Access protocols with contention resolution as Contention Resolution Diversity Slotted Aloha (CRDSA) and introduces a possible enhancement, named Gener- alized Contention Resolution Diversity Slotted Aloha (GE-CRDSA). The GE- CRDSA aims to improve the aggregated throughput when the system load is less than 50%, playing on the opportunity of transmitting an optimal combination of information and parity packets frame by frame.Source: Personal Satellite Services. Revised Selected Papers, edited by Riadh Dhaou, André-Luc Beylot, Marie-José Montpetit, Daniel Enrique Lucani, Lorenzo Mucchi, pp. 115–122, 2013
DOI: 10.1007/978-3-319-02762-3
Metrics:
See at:
doi.org | CNR ExploRA
2014
Journal article
Open Access
Generalized encoding CRDSA: maximizing throughput in enhanced random access schemes for satellite
Bacco F. M., Cassarà P., Gotta A.
This work starts from the analysis of the literature about the Random Access protocols with contention resolution, such as Contention Resolution Diversity Slotted Aloha (CRDSA), and introduces a possible enhancement, named Generalized Encoding Contention Resolution Diversity Slotted Aloha (GE-CRDSA). The GE-CRDSA aims at improving the aggregated throughput when the system load is less than 50%, playing on the opportunity of transmitting an optimal combination of information and parity packets frame by frame. This paper shows the improvement in terms of throughput, by performing traffic estimation and adaptive choice of information and parity rates, when a satellite network undergoes a variable traffic load profile.Source: ICST Transactions on Mobile Communications and Applications 2 (2014): 1–16. doi:10.4108/mca.2.5.e2
DOI: 10.4108/mca.2.5.e2
Metrics:
Bacco F. M., Cassarà P., Gotta A.
This work starts from the analysis of the literature about the Random Access protocols with contention resolution, such as Contention Resolution Diversity Slotted Aloha (CRDSA), and introduces a possible enhancement, named Generalized Encoding Contention Resolution Diversity Slotted Aloha (GE-CRDSA). The GE-CRDSA aims at improving the aggregated throughput when the system load is less than 50%, playing on the opportunity of transmitting an optimal combination of information and parity packets frame by frame. This paper shows the improvement in terms of throughput, by performing traffic estimation and adaptive choice of information and parity rates, when a satellite network undergoes a variable traffic load profile.Source: ICST Transactions on Mobile Communications and Applications 2 (2014): 1–16. doi:10.4108/mca.2.5.e2
DOI: 10.4108/mca.2.5.e2
Metrics:
See at:
EAI Endorsed Transactions on Mobile Communications and Applications | EAI Endorsed Transactions on Mobile Communications and Applications | EAI Endorsed Transactions on Mobile Communications and Applications | CNR ExploRA
2015
Report
Unknown
Choosing an RSS device-free localization algorithm for ambient assisted living
Cassarà P., Potorti F., Barsocchi P., Girolami M.
Device-free localization algorithms attract, among others, the attention of researchers working in the Ambient Assisted Living (AAL) scenarios, where the target user might not be able or willing to wear any devices. We concentrate on systems that exploit the Received Signal Strength indicator coming from wireless devices whose position is known, called anchors. In this paper we select and test the main device-free localization solutions and experimentally compare their performance using a smaller number of anchors than commonly found in the literature. We illustrate the procedure used to validate our comparing procedure and we give suggestions on usability in the application scenarios typical of AAL.Source: ISTI Technical reports, 2015
Cassarà P., Potorti F., Barsocchi P., Girolami M.
Device-free localization algorithms attract, among others, the attention of researchers working in the Ambient Assisted Living (AAL) scenarios, where the target user might not be able or willing to wear any devices. We concentrate on systems that exploit the Received Signal Strength indicator coming from wireless devices whose position is known, called anchors. In this paper we select and test the main device-free localization solutions and experimentally compare their performance using a smaller number of anchors than commonly found in the literature. We illustrate the procedure used to validate our comparing procedure and we give suggestions on usability in the application scenarios typical of AAL.Source: ISTI Technical reports, 2015
See at: CNR ExploRA
2015
Report
Unknown
Lessons learned on device free localization with single and multi channel mode
Cassarà P., Potorti F., Barsocchi P., Girolami M., Nepa P.
In this paper we concentrate on device-free RSS- based indoor localization methods, which have been the subject of intensive studies in the last few years. Specifically, the purpose of this paper is to assess the performance improvements of a Variance-based Radio Tomographic Imaging (VRTI) technique, when scanning various radio channels. We compare the perfor- mance of such technique compared with a VRTI configured with only single channel, the latter being the "minimum introduced interference" option. Moreover, in this paper we discuss in which application scenarios the multi-channel scanning technique is usable and appropriate. We describe how we configure the measurements campaigns to gather RSS values as well two indicative performance metrics, namely the mean square error and percentiles of the error distribution.Source: ISTI Technical reports, 2015
Cassarà P., Potorti F., Barsocchi P., Girolami M., Nepa P.
In this paper we concentrate on device-free RSS- based indoor localization methods, which have been the subject of intensive studies in the last few years. Specifically, the purpose of this paper is to assess the performance improvements of a Variance-based Radio Tomographic Imaging (VRTI) technique, when scanning various radio channels. We compare the perfor- mance of such technique compared with a VRTI configured with only single channel, the latter being the "minimum introduced interference" option. Moreover, in this paper we discuss in which application scenarios the multi-channel scanning technique is usable and appropriate. We describe how we configure the measurements campaigns to gather RSS values as well two indicative performance metrics, namely the mean square error and percentiles of the error distribution.Source: ISTI Technical reports, 2015
See at: CNR ExploRA
2015
Bachelor thesis
Restricted
Modeling web search query traffic with batch arrival processes
Colucci M.
This thesis aims to study the Batch Markovian Arrival Process as a possible candidate to model the input stream of a queueing system. The characterization of the process is based on the estimation of the corresponding probability density function exploiting a non- parametric density estimation technique: the Generalized Cross Entropy method. The estimation provided by the proposed method is compared with an alternative one already studied in literature exploiting a Markov Modulated Poisson Process to model the arrival process.
Colucci M.
This thesis aims to study the Batch Markovian Arrival Process as a possible candidate to model the input stream of a queueing system. The characterization of the process is based on the estimation of the corresponding probability density function exploiting a non- parametric density estimation technique: the Generalized Cross Entropy method. The estimation provided by the proposed method is compared with an alternative one already studied in literature exploiting a Markov Modulated Poisson Process to model the arrival process.
See at:
etd.adm.unipi.it | CNR ExploRA