2022
Conference article
Open Access
Data models for an imaging bio-bank for colorectal, prostate and gastric cancer: the NAVIGATOR project
Berti A., Carloni G., Colantonio S., Pascali M. A., Manghi P., Pagano P., Buongiorno R., Pachetti E., Caudai C., Di Gangi D., Carlini E., Falaschi Z., Ciarrocchi E., Neri E., Bertelli E., Miele V., Carpi R., Bagnacci G., Di Meglio N., Mazzei M. A., Barucci A.
Researchers nowadays may take advantage of broad collections of medical data to develop personalized medicine solutions. Imaging bio-banks play a fundamental role, in this regard, by serving as organized repositories of medical images associated with imaging biomarkers. In this context, the NAVIGATOR Project aims to advance colorectal, prostate, and gastric oncology translational research by leveraging quantitative imaging and multi-omics analyses. As Project's core, an imaging bio-bank is being designed and implemented in a web-accessible Virtual Research Environment (VRE). The VRE serves to extract the imaging biomarkers and further process them within prediction algorithms. In our work, we present the realization of the data models for the three cancer use-cases of the Project. First, we carried out an extensive requirements analysis to fulfill the necessities of the clinical partners involved in the Project. Then, we designed three separate data models utilizing entity-relationship diagrams. We found diagrams' modeling for colorectal and prostate cancers to be more straightforward, while gastric cancer required a higher level of complexity. Future developments of this work would include designing a common data model following the Observational Medical Outcomes Partnership Standards. Indeed, a common data model would standardize the logical infrastructure of data models and make the bio-bank easily interoperable with other bio-banks.Source: BHI '22 - IEEE-EMBS International Conference on Biomedical and Health Informatics, Ioannina, Greece, 27-30/09/2022
DOI: 10.1109/bhi56158.2022.9926910
Metrics:
Berti A., Carloni G., Colantonio S., Pascali M. A., Manghi P., Pagano P., Buongiorno R., Pachetti E., Caudai C., Di Gangi D., Carlini E., Falaschi Z., Ciarrocchi E., Neri E., Bertelli E., Miele V., Carpi R., Bagnacci G., Di Meglio N., Mazzei M. A., Barucci A.
Researchers nowadays may take advantage of broad collections of medical data to develop personalized medicine solutions. Imaging bio-banks play a fundamental role, in this regard, by serving as organized repositories of medical images associated with imaging biomarkers. In this context, the NAVIGATOR Project aims to advance colorectal, prostate, and gastric oncology translational research by leveraging quantitative imaging and multi-omics analyses. As Project's core, an imaging bio-bank is being designed and implemented in a web-accessible Virtual Research Environment (VRE). The VRE serves to extract the imaging biomarkers and further process them within prediction algorithms. In our work, we present the realization of the data models for the three cancer use-cases of the Project. First, we carried out an extensive requirements analysis to fulfill the necessities of the clinical partners involved in the Project. Then, we designed three separate data models utilizing entity-relationship diagrams. We found diagrams' modeling for colorectal and prostate cancers to be more straightforward, while gastric cancer required a higher level of complexity. Future developments of this work would include designing a common data model following the Observational Medical Outcomes Partnership Standards. Indeed, a common data model would standardize the logical infrastructure of data models and make the bio-bank easily interoperable with other bio-banks.Source: BHI '22 - IEEE-EMBS International Conference on Biomedical and Health Informatics, Ioannina, Greece, 27-30/09/2022
DOI: 10.1109/bhi56158.2022.9926910
Metrics:
See at:
ISTI Repository 
| ieeexplore.ieee.org 
| CNR ExploRA
2022
Conference article
Open Access
A novel approach to distributed model aggregation using Apache Kafka
Bano S., Carlini E., Cassarà P., Coppola M., Dazzi P., Gotta A.
Multi-Access Edge Computing (MEC) is attracting a lot of interest because it complements cloud-based approaches. Indeed, MEC is opening up in the direction of reducing both interaction delays and data sharing, called Cyber-Physical Systems (CPSs). In the near fu-ture, edge technologies will be a fundamental tool to better support time-dependent and data-intensive applications. In this context, this work explores existing and emerging platforms for MEC and human-centric applications, and proposes a suitable architecture that can be used in the context of autonomous vehicle systems.The proposed architecture will support scalable communication among sensing devices and edge/cloud computing platforms, as well as orchestrate services for computing, storage, and learning with the use of an Information-centric paradigm such as Apache KafkaSource: FRAME '22 - 2nd Workshop on Flexible Resource and Application Management on the Edge, pp. 33–36, Minneapolis, Minnesota, USA, 27/06-01/07/2022
DOI: 10.1145/3526059.3533621
Project(s): TEACHING
Metrics:
Bano S., Carlini E., Cassarà P., Coppola M., Dazzi P., Gotta A.
Multi-Access Edge Computing (MEC) is attracting a lot of interest because it complements cloud-based approaches. Indeed, MEC is opening up in the direction of reducing both interaction delays and data sharing, called Cyber-Physical Systems (CPSs). In the near fu-ture, edge technologies will be a fundamental tool to better support time-dependent and data-intensive applications. In this context, this work explores existing and emerging platforms for MEC and human-centric applications, and proposes a suitable architecture that can be used in the context of autonomous vehicle systems.The proposed architecture will support scalable communication among sensing devices and edge/cloud computing platforms, as well as orchestrate services for computing, storage, and learning with the use of an Information-centric paradigm such as Apache KafkaSource: FRAME '22 - 2nd Workshop on Flexible Resource and Application Management on the Edge, pp. 33–36, Minneapolis, Minnesota, USA, 27/06-01/07/2022
DOI: 10.1145/3526059.3533621
Project(s): TEACHING
Metrics:
See at:
ZENODO | dl.acm.org | doi.org | CNR ExploRA
2022
Conference article
Open Access
A federated cloud solution for transnational mobility data sharing
Carlini E., Chevalier T., Dazzi P., Lettich F., Perego R., Renso C., Trani S.
Nowadays, innovative digital services are massively spreading both in the public and private sectors. In this work we focus on the digital data regarding the mobility of persons and goods, which are experiencing exponential growth thanks to the significant diffusion of telecommunication infrastructures and inexpensive GPS-equipped devices. The volume, velocity, and heterogeneity of mobility data call for advanced and efficient services to collect and integrate various data sources from different data producers. The MobiDataLab H2020 project aims to deal with these challenges by introducing an efficient and highly interoperable digital framework for mobility data sharing. In particular, the project aims to propose to the mobility stakeholders (i.e., transport organising authorities, operators, industry, governments, and innovators) reproducible methodologies and sustainable tools that can foster the development of a data-sharing culture in Europe and beyond. This paper introduces the key concepts driving the design and definition of a cloud-based data-sharing federation we call the Transport Cloud platform, which represents one of the main pillars of the MobiDataLab project. Such platform aims to ensure transnational access to mobility data in a secure, efficient, and seamless way, and to ensure that FAIR principles (i.e., mobility data should be findable, accessible, interoperable, and reusable) are enforced.Source: SEBD 2022 - 30th Italian Symposium on Advanced Database Systems, pp. 586–592, Tirrenia, Pisa, Italy, 19-22/06/2022
Project(s): ACCORDION, MobiDataLab
Carlini E., Chevalier T., Dazzi P., Lettich F., Perego R., Renso C., Trani S.
Nowadays, innovative digital services are massively spreading both in the public and private sectors. In this work we focus on the digital data regarding the mobility of persons and goods, which are experiencing exponential growth thanks to the significant diffusion of telecommunication infrastructures and inexpensive GPS-equipped devices. The volume, velocity, and heterogeneity of mobility data call for advanced and efficient services to collect and integrate various data sources from different data producers. The MobiDataLab H2020 project aims to deal with these challenges by introducing an efficient and highly interoperable digital framework for mobility data sharing. In particular, the project aims to propose to the mobility stakeholders (i.e., transport organising authorities, operators, industry, governments, and innovators) reproducible methodologies and sustainable tools that can foster the development of a data-sharing culture in Europe and beyond. This paper introduces the key concepts driving the design and definition of a cloud-based data-sharing federation we call the Transport Cloud platform, which represents one of the main pillars of the MobiDataLab project. Such platform aims to ensure transnational access to mobility data in a secure, efficient, and seamless way, and to ensure that FAIR principles (i.e., mobility data should be findable, accessible, interoperable, and reusable) are enforced.Source: SEBD 2022 - 30th Italian Symposium on Advanced Database Systems, pp. 586–592, Tirrenia, Pisa, Italy, 19-22/06/2022
Project(s): ACCORDION
, MobiDataLab
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA
2022
Conference article
Open Access
A mathematical model for latency constrained self-organizing application placement in the edge
Mordacchini M., Carlini E., Dazzi P.
The highly dynamic and heterogeneous environment that characterizes the edge of the Cloud/Edge Continuum calls for new intelligent methods for tackling the needs of such a complex scenario. In particular, adaptive and self-organizing decentralized solutions have been advanced for optimizing the placement of applications at the Edge. In this paper, we propose a probabilistic mathematical model that allows to describe one of such solutions. The goal of the model is twofold: i) to make it possible to demonstrate the convergence of the proposed solution; ii) to study the impact of the self-organizing solution without the need of an actual implementation or simulation of the system, allowing to evaluate the suitability of the solution in specific contexts. The paper presents the mathematical formulation of the proposed solution as well as the validation of the proposed model against a simulation of the system.Source: FRAME: 2nd Workshop on Flexible Resource and Application Management on the Edge (colocated with HPDC 2022), pp. 29–32, Minneapolis, Minnestota, USA, 01/07/2022
DOI: 10.1145/3526059.3533620
Project(s): ACCORDION
Metrics:
Mordacchini M., Carlini E., Dazzi P.
The highly dynamic and heterogeneous environment that characterizes the edge of the Cloud/Edge Continuum calls for new intelligent methods for tackling the needs of such a complex scenario. In particular, adaptive and self-organizing decentralized solutions have been advanced for optimizing the placement of applications at the Edge. In this paper, we propose a probabilistic mathematical model that allows to describe one of such solutions. The goal of the model is twofold: i) to make it possible to demonstrate the convergence of the proposed solution; ii) to study the impact of the self-organizing solution without the need of an actual implementation or simulation of the system, allowing to evaluate the suitability of the solution in specific contexts. The paper presents the mathematical formulation of the proposed solution as well as the validation of the proposed model against a simulation of the system.Source: FRAME: 2nd Workshop on Flexible Resource and Application Management on the Edge (colocated with HPDC 2022), pp. 29–32, Minneapolis, Minnestota, USA, 01/07/2022
DOI: 10.1145/3526059.3533620
Project(s): ACCORDION
Metrics:
See at:
ISTI Repository | dl.acm.org | doi.org | CNR ExploRA
2022
Conference article
Open Access
Network measurements with function-as-a-service for distributed low-latency edge applications
Carlini E., Kavalionak H., Dazzi P., Ferrucci L., Coppola M., Mordacchini M.
Edge computing promises to bring computation and storage close to end-users, opening exciting new areas of improvement for applications with a high level of interactivity and requiring low latency. However, these improvements require careful scheduling of applications in the correct Edge resource. This decision is generally taken by considering multiple parameters, including the network capabilities. In this paper, we discuss an approach that measures latency and bandwidth between multiple clients and Edge servers. The approach is based on recent Serverless computing technologies, and it is meant as a support to take timely and correct scheduling decisions in the Edge. We also provide the description of a proof of concept implementation of the said approach.Source: FRAME 2022 - 2nd Workshop on Flexible Resource and Application Management on the Edge (colocated with HPDC 2022), pp. 25–28, Minneapolis, Minnestota, USA, 01/07/2022
DOI: 10.1145/3526059.3533622
Project(s): ACCORDION
Metrics:
Carlini E., Kavalionak H., Dazzi P., Ferrucci L., Coppola M., Mordacchini M.
Edge computing promises to bring computation and storage close to end-users, opening exciting new areas of improvement for applications with a high level of interactivity and requiring low latency. However, these improvements require careful scheduling of applications in the correct Edge resource. This decision is generally taken by considering multiple parameters, including the network capabilities. In this paper, we discuss an approach that measures latency and bandwidth between multiple clients and Edge servers. The approach is based on recent Serverless computing technologies, and it is meant as a support to take timely and correct scheduling decisions in the Edge. We also provide the description of a proof of concept implementation of the said approach.Source: FRAME 2022 - 2nd Workshop on Flexible Resource and Application Management on the Edge (colocated with HPDC 2022), pp. 25–28, Minneapolis, Minnestota, USA, 01/07/2022
DOI: 10.1145/3526059.3533622
Project(s): ACCORDION
Metrics:
See at:
ISTI Repository | dl.acm.org | doi.org | CNR ExploRA
2022
Conference article
Open Access
Energy and QoE aware placement of applications and data at the edge
Mordacchini M., Ferrucci L., Carlini E., Kavalionak H., Coppola M., Dazzi P.
Recent years are witnessing extensions of cyber-infrastructures towards distributed environments. The Edge of the network is gaining a central role in the agenda of both infrastructure and application providers. Following the actual distributed structure of such a computational environment, nowadays, many solutions face resource and application management needs in Cloud/Edge continua. One of the most challenging aspects is ensuring highly available computing and data infrastructures while optimizing the system's energy consumption. In this paper, we describe a decentralized solution that limits the energy consumption by the system without failing to match the users' expectations, defined as the services' Quality of Experience (QoE) when accessing data and leveraging applications at the Edge. Experimental evaluations through simulation conducted with PureEdgeSim demonstrate the effectiveness of the approach.Source: SEBD 2022 - 30th Italian Symposium on Advanced Database Systems, pp. 109–116, Tirrenia, Pisa, Italy, 19-22/06/2022
Mordacchini M., Ferrucci L., Carlini E., Kavalionak H., Coppola M., Dazzi P.
Recent years are witnessing extensions of cyber-infrastructures towards distributed environments. The Edge of the network is gaining a central role in the agenda of both infrastructure and application providers. Following the actual distributed structure of such a computational environment, nowadays, many solutions face resource and application management needs in Cloud/Edge continua. One of the most challenging aspects is ensuring highly available computing and data infrastructures while optimizing the system's energy consumption. In this paper, we describe a decentralized solution that limits the energy consumption by the system without failing to match the users' expectations, defined as the services' Quality of Experience (QoE) when accessing data and leveraging applications at the Edge. Experimental evaluations through simulation conducted with PureEdgeSim demonstrate the effectiveness of the approach.Source: SEBD 2022 - 30th Italian Symposium on Advanced Database Systems, pp. 109–116, Tirrenia, Pisa, Italy, 19-22/06/2022
See at:
ISTI Repository | ceur-ws.org | CNR ExploRA
2022
Conference article
Open Access
Decentralized federated learning and network topologies: an empirical study on convergence
Kavalionak H., Carlini E., Dazzi P., Ferrucci L., Mordacchini M., Coppola M.
Federated Learning is a well-known learning paradigm that allows the distributed training of machine learning models. Federated Learning keeps data in the source devices and communicates only the model's coefficients to a centralized server. This paper studies the decentralized flavor of Federated Learning. A peer-to-peer network replaces the centralized server, and nodes exchange model's coefficients directly. In particular, we look for empirical evidence on the effect of different network topologies and communication parameters on the convergence in the training of distributed models. Our observations suggest that small-world networks converge faster for small amounts of nodes, while xx are more suitable for larger setups.Source: SEBD 2022 - 30th Italian Symposium on Advanced Database Systems, pp. 317–324, Tirrenia, Pisa, Italy, 19-22/06/2022
Project(s): TEACHING
Kavalionak H., Carlini E., Dazzi P., Ferrucci L., Mordacchini M., Coppola M.
Federated Learning is a well-known learning paradigm that allows the distributed training of machine learning models. Federated Learning keeps data in the source devices and communicates only the model's coefficients to a centralized server. This paper studies the decentralized flavor of Federated Learning. A peer-to-peer network replaces the centralized server, and nodes exchange model's coefficients directly. In particular, we look for empirical evidence on the effect of different network topologies and communication parameters on the convergence in the training of distributed models. Our observations suggest that small-world networks converge faster for small amounts of nodes, while xx are more suitable for larger setups.Source: SEBD 2022 - 30th Italian Symposium on Advanced Database Systems, pp. 317–324, Tirrenia, Pisa, Italy, 19-22/06/2022
Project(s): TEACHING
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA
2022
Conference article
Open Access
A topological perspective of port networks from three years (2017-2019) of AIS Data
Carlini E., De Lira V. M., Soares A., Etemad M., Brandoli B., Matwin S.
Complex network analysis is a fundamental tool to understand non-trivial aspects of graphs and networks and is widely used in many fields. In this paper, we apply complex network techniques to study port networks, in which nodes are ports and edges are maritime lines between ports. In particular, we study the temporal evolution of several topological features of a network of ports, including connected components, shortest paths, and clustering coefficients. We built the network with three years of Automatic Identification System data from 2017 to 2019. We highlight several interesting trends and behaviors that differentiate long-range vessels from short-range vessels.Source: SEBD 2022 - 30th Italian Symposium on Advanced Database Systems, pp. 268–275, Tirrenia, Pisa, Italy, 19-22/06/2022
Project(s): MASTER
Carlini E., De Lira V. M., Soares A., Etemad M., Brandoli B., Matwin S.
Complex network analysis is a fundamental tool to understand non-trivial aspects of graphs and networks and is widely used in many fields. In this paper, we apply complex network techniques to study port networks, in which nodes are ports and edges are maritime lines between ports. In particular, we study the temporal evolution of several topological features of a network of ports, including connected components, shortest paths, and clustering coefficients. We built the network with three years of Automatic Identification System data from 2017 to 2019. We highlight several interesting trends and behaviors that differentiate long-range vessels from short-range vessels.Source: SEBD 2022 - 30th Italian Symposium on Advanced Database Systems, pp. 268–275, Tirrenia, Pisa, Italy, 19-22/06/2022
Project(s): MASTER
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA
2022
Journal article
Open Access
NAVIGATOR: an Italian regional imaging biobank to promote precision medicine for oncologic patients
Borgheresi R., Barucci A., Colantonio S., Aghakhanyan G., Assante M., Bertelli E., Carlini E., Carpi R., Caudai C., Cavallero D., Cioni D., Cirillo R., Colcelli V., Dell'Amico A., Di Gangi D., Erba P. A., Faggioni L., Falaschi Z., Gabelloni M., Gini R., Lelii L., Liò P., Lorito A., Lucarini S., Manghi P., Mangiacrapa F., Marzi C., Mazzei M. A., Mercatelli L., Mirabile A., Mungai F., Miele V., Olmastroni M., Pagano P., Paiar F., Panichi G., Pascali M. A., Pasquinelli F., Shortrede J. E., Tumminello L., Volterrani L., Neri E., On Behalf Of The Navigator Consortium Group
NAVIGATOR is an Italian regional project to boost precision medicine in oncology with the aim to make it more predictive, preventive, and personalised by advancing translational research based on quantitative imaging and integrative omics analyses. The project's goal is to develop an open imaging biobank for the collection and preservation of a large amount of standardised imaging multimodal datasets, including computed tomography, magnetic resonance imaging, and positron emission tomography data, together with the corresponding patient-related and omics-related relevant information extracted from regional healthcare services using an adapted privacy-preserving model. The project is based on an open-source imaging biobank and an open-science oriented virtual research environment (VRE). Available integrative omics and multi-imaging data of three use cases (prostate cancer, rectal cancer, and gastric cancer) will be collected. All data confined in NAVIGATOR (i.e. standard and novel imaging biomarkers, non-imaging data, health agency data) will be used to create a digital patient model, to support the reliable prediction of the disease phenotype and risk stratification. The VRE that relies on a well-established infrastructure, called D4Science.org, will further provide a multiset infrastructure for processing the integrative omics data, extracting specific radiomic signatures, and for identification and testing of novel imaging biomarkers through big data analytics and artificial intelligence.Source: European radiology experimental Online 6 (2022). doi:10.1186/s41747-022-00306-9
DOI: 10.1186/s41747-022-00306-9
Metrics:
Borgheresi R., Barucci A., Colantonio S., Aghakhanyan G., Assante M., Bertelli E., Carlini E., Carpi R., Caudai C., Cavallero D., Cioni D., Cirillo R., Colcelli V., Dell'Amico A., Di Gangi D., Erba P. A., Faggioni L., Falaschi Z., Gabelloni M., Gini R., Lelii L., Liò P., Lorito A., Lucarini S., Manghi P., Mangiacrapa F., Marzi C., Mazzei M. A., Mercatelli L., Mirabile A., Mungai F., Miele V., Olmastroni M., Pagano P., Paiar F., Panichi G., Pascali M. A., Pasquinelli F., Shortrede J. E., Tumminello L., Volterrani L., Neri E., On Behalf Of The Navigator Consortium Group
NAVIGATOR is an Italian regional project to boost precision medicine in oncology with the aim to make it more predictive, preventive, and personalised by advancing translational research based on quantitative imaging and integrative omics analyses. The project's goal is to develop an open imaging biobank for the collection and preservation of a large amount of standardised imaging multimodal datasets, including computed tomography, magnetic resonance imaging, and positron emission tomography data, together with the corresponding patient-related and omics-related relevant information extracted from regional healthcare services using an adapted privacy-preserving model. The project is based on an open-source imaging biobank and an open-science oriented virtual research environment (VRE). Available integrative omics and multi-imaging data of three use cases (prostate cancer, rectal cancer, and gastric cancer) will be collected. All data confined in NAVIGATOR (i.e. standard and novel imaging biomarkers, non-imaging data, health agency data) will be used to create a digital patient model, to support the reliable prediction of the disease phenotype and risk stratification. The VRE that relies on a well-established infrastructure, called D4Science.org, will further provide a multiset infrastructure for processing the integrative omics data, extracting specific radiomic signatures, and for identification and testing of novel imaging biomarkers through big data analytics and artificial intelligence.Source: European radiology experimental Online 6 (2022). doi:10.1186/s41747-022-00306-9
DOI: 10.1186/s41747-022-00306-9
Metrics:
See at:
eurradiolexp.springeropen.com | ISTI Repository | CNR ExploRA
2021
Contribution to conference
Open Access
Cloud and Data Federation in MobiDataLab
Carlini E., Dazzi P., Lettich F., Perego R., Renso C.
Today's innovative digital services dealing with the mobility of per- sons and goods produce huge amount of data. To propose advanced and efficient mobility services, the collection and aggregation of new sources of data from various producers are necessary. The overall objective of the MobiDataLab H2020 project is to propose to the mobility stakeholders (transport organising authorities, operators, industry, government and innovators) reproducible methodologies and sustainable tools that foster the development of a data-sharing culture in Europe and beyond. This short paper introduces the key concepts driving the design and definition of the Cloud and Data Federation that stands at the basis of MobiDataLab.Source: FRAME'21 - 1st Workshop on Flexible Resource and Application Management on the Edge, Virtual Event, Sweden, 25/06/2021
DOI: 10.1145/3452369.3463819
Project(s): ACCORDION
Metrics:
Carlini E., Dazzi P., Lettich F., Perego R., Renso C.
Today's innovative digital services dealing with the mobility of per- sons and goods produce huge amount of data. To propose advanced and efficient mobility services, the collection and aggregation of new sources of data from various producers are necessary. The overall objective of the MobiDataLab H2020 project is to propose to the mobility stakeholders (transport organising authorities, operators, industry, government and innovators) reproducible methodologies and sustainable tools that foster the development of a data-sharing culture in Europe and beyond. This short paper introduces the key concepts driving the design and definition of the Cloud and Data Federation that stands at the basis of MobiDataLab.Source: FRAME'21 - 1st Workshop on Flexible Resource and Application Management on the Edge, Virtual Event, Sweden, 25/06/2021
DOI: 10.1145/3452369.3463819
Project(s): ACCORDION
Metrics:
See at:
ISTI Repository | CNR ExploRA
2021
Conference article
Open Access
Inter-operability and Orchestration in Heterogeneous Cloud/Edge Resources: The ACCORDION Vision
Korontanis I., Tserpes K., Pateraki M., Blasi L., Violos J., Ferran D., Marin E., Kourtellis N., Coppola M., Carlini E., Ledwo? Z., Tarkowski P., Loven T., González Rozas Y., Kentros M., Dodis M., Dazzi P.
This paper introduces the ACCORDION framework, a novel frame- work for the management of the cloud-edge continuum, targeting the support of NextGen applications with strong QoE requirements. The framework addresses the need for an ever expanding and het- erogeneous pool of edge resources in order to deliver the promise of ubiquitous computing to the NextGen application clients. This endeavor entails two main technical challenges. First, to assure interoperability when incorporating heterogeneous infrastructures in the pool. Second, the management of the largely dynamic pool of edge nodes. The optimization of the delivered QoE stands as the core driver to this work, therefore its monitoring and modelling comprises a core part of the conducted work. The paper discusses the main pillars that support the ACCORDION vision, and provide a description of the three planned use case that are planned to demonstrate ACCORDION capabilities.Source: FRAME'21 - 1st Workshop on Flexible Resource and Application Management on the Edge, Virtual Event, Sweden, 25/06/2021
DOI: 10.1145/3452369.3463816
Project(s): ACCORDION, ACCORDION
Metrics:
Korontanis I., Tserpes K., Pateraki M., Blasi L., Violos J., Ferran D., Marin E., Kourtellis N., Coppola M., Carlini E., Ledwo? Z., Tarkowski P., Loven T., González Rozas Y., Kentros M., Dodis M., Dazzi P.
This paper introduces the ACCORDION framework, a novel frame- work for the management of the cloud-edge continuum, targeting the support of NextGen applications with strong QoE requirements. The framework addresses the need for an ever expanding and het- erogeneous pool of edge resources in order to deliver the promise of ubiquitous computing to the NextGen application clients. This endeavor entails two main technical challenges. First, to assure interoperability when incorporating heterogeneous infrastructures in the pool. Second, the management of the largely dynamic pool of edge nodes. The optimization of the delivered QoE stands as the core driver to this work, therefore its monitoring and modelling comprises a core part of the conducted work. The paper discusses the main pillars that support the ACCORDION vision, and provide a description of the three planned use case that are planned to demonstrate ACCORDION capabilities.Source: FRAME'21 - 1st Workshop on Flexible Resource and Application Management on the Edge, Virtual Event, Sweden, 25/06/2021
DOI: 10.1145/3452369.3463816
Project(s): ACCORDION
, ACCORDION Metrics:
See at:
ISTI Repository | CNR ExploRA | ZENODO
2021
Conference article
Open Access
Latency Preserving Self-optimizing Placement at the Edge
Ferrucci L., Mordacchini M., Coppola M., Carlini E., Kavalionak H., Dazzi P.
The Internet is experiencing a fast expansion at its edges. The wide availability of heterogeneous resources at the Edge is pivotal in the definition and extension of traditional Cloud solutions toward supporting the development of new applications. However, the dynamic and distributed nature of these resources poses new challenges for the optimization of the behaviour of the system. New decentralized and self-organizing methods are needed to face the needs of the Edge/Cloud scenario and to optimize the exploitation of Edge resources. In this paper we propose a distributed and adaptive solution that reduces the number of replicas of application services that are executed throughout the system, all the while ensuring that the latency constraints of applications are met, thus allowing to also meet the end users' QoS requirements. Experimental evaluations through simulation show the effectiveness of the proposed approach.Source: FRAME'21 - 1st Workshop on Flexible Resource and Application Management on the Edge, Virtual Event, Sweden, 25/06/2021
DOI: 10.1145/3452369.3463815
Project(s): ACCORDION, ACCORDION
Metrics:
Ferrucci L., Mordacchini M., Coppola M., Carlini E., Kavalionak H., Dazzi P.
The Internet is experiencing a fast expansion at its edges. The wide availability of heterogeneous resources at the Edge is pivotal in the definition and extension of traditional Cloud solutions toward supporting the development of new applications. However, the dynamic and distributed nature of these resources poses new challenges for the optimization of the behaviour of the system. New decentralized and self-organizing methods are needed to face the needs of the Edge/Cloud scenario and to optimize the exploitation of Edge resources. In this paper we propose a distributed and adaptive solution that reduces the number of replicas of application services that are executed throughout the system, all the while ensuring that the latency constraints of applications are met, thus allowing to also meet the end users' QoS requirements. Experimental evaluations through simulation show the effectiveness of the proposed approach.Source: FRAME'21 - 1st Workshop on Flexible Resource and Application Management on the Edge, Virtual Event, Sweden, 25/06/2021
DOI: 10.1145/3452369.3463815
Project(s): ACCORDION
, ACCORDION Metrics:
See at:
ISTI Repository | CNR ExploRA | ZENODO
2021
Conference article
Restricted
An Osmotic Ecosystem for Data Streaming Applications in Smart Cities
Carlini E., Carnevale L., Coppola M., Dazzi P., Mencagli G., Talia D., Villari M.
Modern multi-tier Cloud-Edge-IoT computational platforms seamlessly map with the distributed and hierarchical nature of smart cities infrastructure. However, classical tools and methodologies to organise data as well as computational and network resources are poorly equipped to tackle the dynamic and heterogeneous environments of smart cities. In this paper we propose a reference architecture that aims to establish a unified approach for the orchestration of modern Cloud-Edge-IoT infrastructures and resources specifically tailored for data streaming applications in smart-cities. Stemming from the proposed reference architecture, we also discuss a series of open challenges, which we believe represent relevant research directions in the nearest future.Source: FRAME'21 - 1st Workshop on Flexible Resource and Application Management on the Edge, online, Sweden, 25/06/2021
DOI: 10.1145/3452369.3463822
Metrics:
Carlini E., Carnevale L., Coppola M., Dazzi P., Mencagli G., Talia D., Villari M.
Modern multi-tier Cloud-Edge-IoT computational platforms seamlessly map with the distributed and hierarchical nature of smart cities infrastructure. However, classical tools and methodologies to organise data as well as computational and network resources are poorly equipped to tackle the dynamic and heterogeneous environments of smart cities. In this paper we propose a reference architecture that aims to establish a unified approach for the orchestration of modern Cloud-Edge-IoT infrastructures and resources specifically tailored for data streaming applications in smart-cities. Stemming from the proposed reference architecture, we also discuss a series of open challenges, which we believe represent relevant research directions in the nearest future.Source: FRAME'21 - 1st Workshop on Flexible Resource and Application Management on the Edge, online, Sweden, 25/06/2021
DOI: 10.1145/3452369.3463822
Metrics:
See at:
CNR ExploRA
2021
Report
Open Access
ACCORDION D6.1 - Pilot Plans (I)
Dodis M., Ledwon Z., Tarkowski P., Loven T., Carlini E., Zadtootaghaj S., Dazzi P.
This deliverable provides a first release of the report on the plans to implement and evaluate the scenarios addressed for each project Use Case. The deliverable comprises and reports on tree main subtasks. The first subtask relates to a detailed description of the Use Cases and the scenarios under which evaluation which revolve. The second subtask relates to the description of the pilot prototypes, the evaluation methodology, the experimentation requirements, the modules/functionalities that will be assessed and the metrics for assessing the value of ACCORDION in terms of technology and subjective Quality of Experience. The third subtask specifies the integration plan for the components and technologies of ACCORDION, the design of the infrastructure along with the testbed combinations for pilot execution and evaluation and the execution methodology. Regarding ethical and privacy issues, all necessary measures have been considered as part of conducting the subjective Quality of experience evaluation and are reported.Source: ISTI Project report, ACCORDION, D6.1, 2021
Project(s): ACCORDION
Dodis M., Ledwon Z., Tarkowski P., Loven T., Carlini E., Zadtootaghaj S., Dazzi P.
This deliverable provides a first release of the report on the plans to implement and evaluate the scenarios addressed for each project Use Case. The deliverable comprises and reports on tree main subtasks. The first subtask relates to a detailed description of the Use Cases and the scenarios under which evaluation which revolve. The second subtask relates to the description of the pilot prototypes, the evaluation methodology, the experimentation requirements, the modules/functionalities that will be assessed and the metrics for assessing the value of ACCORDION in terms of technology and subjective Quality of Experience. The third subtask specifies the integration plan for the components and technologies of ACCORDION, the design of the infrastructure along with the testbed combinations for pilot execution and evaluation and the execution methodology. Regarding ethical and privacy issues, all necessary measures have been considered as part of conducting the subjective Quality of experience evaluation and are reported.Source: ISTI Project report, ACCORDION, D6.1, 2021
Project(s): ACCORDION
See at:
ISTI Repository | CNR ExploRA
2021
Conference article
Open Access
TEACHING - Trustworthy autonomous cyber-physical applications through human-centred intelligence
Bacciu D., Akarmazyan S., Armengaud E., Bacco M., Bravos G., Calandra C., Carlini E., Carta A., Cassarà P., Coppola M., Davalas C., Dazzi P., Degennaro M. C., Di Sarli D., Dobaj J., Gallicchio C., Girbal S., Gotta A., Groppo R., Lomonaco V., Macher G., Mazzei D., Mencagli G., Michail D., Micheli A., Peroglio R., Petroni S., Potenza R., Pourdanesh F., Sardianos C., Tserpes K., Tagliabò F., Vatl J., Varlamis I., Veledar O.
This paper discusses the perspective of the H2020 TEACHING project on the next generation of autonomous applications running in a distributed and highly heterogeneous environment comprising both virtual and physical resources spanning the edge-cloud continuum. TEACHING puts forward a human-centred vision leveraging the physiological, emotional, and cognitive state of the users as a driver for the adaptation and optimization of the autonomous applications. It does so by building a distributed, embedded and federated learning system complemented by methods and tools to enforce its dependability, security and privacy preservation. The paper discusses the main concepts of the TEACHING approach and singles out the main AI-related research challenges associated with it. Further, we provide a discussion of the design choices for the TEACHING system to tackle the aforementioned challenges.Source: IEEE COINS 2021 - IEEE International Conference on Omni-layer Intelligent systems, Online conference, 23-26/08/2021
DOI: 10.1109/coins51742.2021.9524099
DOI: 10.5281/zenodo.5293769
DOI: 10.5281/zenodo.5293768
Project(s): TEACHING
Metrics:
Bacciu D., Akarmazyan S., Armengaud E., Bacco M., Bravos G., Calandra C., Carlini E., Carta A., Cassarà P., Coppola M., Davalas C., Dazzi P., Degennaro M. C., Di Sarli D., Dobaj J., Gallicchio C., Girbal S., Gotta A., Groppo R., Lomonaco V., Macher G., Mazzei D., Mencagli G., Michail D., Micheli A., Peroglio R., Petroni S., Potenza R., Pourdanesh F., Sardianos C., Tserpes K., Tagliabò F., Vatl J., Varlamis I., Veledar O.
This paper discusses the perspective of the H2020 TEACHING project on the next generation of autonomous applications running in a distributed and highly heterogeneous environment comprising both virtual and physical resources spanning the edge-cloud continuum. TEACHING puts forward a human-centred vision leveraging the physiological, emotional, and cognitive state of the users as a driver for the adaptation and optimization of the autonomous applications. It does so by building a distributed, embedded and federated learning system complemented by methods and tools to enforce its dependability, security and privacy preservation. The paper discusses the main concepts of the TEACHING approach and singles out the main AI-related research challenges associated with it. Further, we provide a discussion of the design choices for the TEACHING system to tackle the aforementioned challenges.Source: IEEE COINS 2021 - IEEE International Conference on Omni-layer Intelligent systems, Online conference, 23-26/08/2021
DOI: 10.1109/coins51742.2021.9524099
DOI: 10.5281/zenodo.5293769
DOI: 10.5281/zenodo.5293768
Project(s): TEACHING
Metrics:
See at:
arXiv.org e-Print Archive | ieeexplore.ieee.org | CNR ExploRA | xplorestaging.ieee.org
2021
Conference article
Open Access
Impact of network topology on the convergence of decentralized federated learning systems
Kavalionak H., Carlini E., Dazzi P., Ferrucci L., Mordacchini M., Coppola M.
Federated learning is a popular framework that enables harvesting edge resources' computational power to train a machine learning model distributively. However, it is not always feasible or profitable to have a centralized server that controls and synchronizes the training process. In this paper, we consider the problem of training a machine learning model over a network of nodes in a fully decentralized fashion. In particular, we look for empirical evidence on how sensitive is the training process for various network characteristics and communication parameters. We present the outcome of several simulations conducted with different network topologies, datasets, and machine learning models.Source: ISCC 2021 - 26th IEEE Symposium on Computers and Communications, Athens, Greece, 05-08/09/2021
DOI: 10.1109/iscc53001.2021.9631460
Project(s): TEACHING
Metrics:
Kavalionak H., Carlini E., Dazzi P., Ferrucci L., Mordacchini M., Coppola M.
Federated learning is a popular framework that enables harvesting edge resources' computational power to train a machine learning model distributively. However, it is not always feasible or profitable to have a centralized server that controls and synchronizes the training process. In this paper, we consider the problem of training a machine learning model over a network of nodes in a fully decentralized fashion. In particular, we look for empirical evidence on how sensitive is the training process for various network characteristics and communication parameters. We present the outcome of several simulations conducted with different network topologies, datasets, and machine learning models.Source: ISCC 2021 - 26th IEEE Symposium on Computers and Communications, Athens, Greece, 05-08/09/2021
DOI: 10.1109/iscc53001.2021.9631460
Project(s): TEACHING
Metrics:
See at:
ISTI Repository | ieeexplore.ieee.org | CNR ExploRA
2021
Conference article
Open Access
Self- organizing energy-minimization placement of QoE-constrained services at the edge
Mordacchini M., Ferrucci L., Carlini E., Kavalionak H., Coppola M., Dazzi P.
The wide availability of heterogeneous resources at the Edgeof the network is gaining a central role in defining and developing newcomputing paradigms for both the infrastructures and the applications.However, it becomes challenging to optimize the system's behaviour, dueto the Edge's highly distributed and dynamic nature. Recent solutionspropose new decentralized, self-adaptive approaches to face the needs ofthis scenario. One of the most challenging aspect is related to the opti-mization of the system's energy consumption. In this paper, we proposea fully decentralized solution that limits the energy consumed by thesystem, without failing to match the users expectations, defined as theservices' Quality of Experience (QoE.). Specifically, we propose a schemewhere the autonomous coordination of entities at Edge is able to reducethe energy consumption by reducing the number of instances of the ap-plications executed in system. This result is achieve without violatingthe services' QoE, expressed in terms of latency. Experimental evalua-tions through simulation conducted with PureEdgeSim demonstrate theeffectiveness of the approachSource: GECON 2021: 18th International Conference on Economics of Grids, Clouds, Systems and Services, pp. 133–142, Virtual Event, Rome, 21-23/09/2021
DOI: 10.1007/978-3-030-92916-9_11
Project(s): ACCORDION
Metrics:
Mordacchini M., Ferrucci L., Carlini E., Kavalionak H., Coppola M., Dazzi P.
The wide availability of heterogeneous resources at the Edgeof the network is gaining a central role in defining and developing newcomputing paradigms for both the infrastructures and the applications.However, it becomes challenging to optimize the system's behaviour, dueto the Edge's highly distributed and dynamic nature. Recent solutionspropose new decentralized, self-adaptive approaches to face the needs ofthis scenario. One of the most challenging aspect is related to the opti-mization of the system's energy consumption. In this paper, we proposea fully decentralized solution that limits the energy consumed by thesystem, without failing to match the users expectations, defined as theservices' Quality of Experience (QoE.). Specifically, we propose a schemewhere the autonomous coordination of entities at Edge is able to reducethe energy consumption by reducing the number of instances of the ap-plications executed in system. This result is achieve without violatingthe services' QoE, expressed in terms of latency. Experimental evalua-tions through simulation conducted with PureEdgeSim demonstrate theeffectiveness of the approachSource: GECON 2021: 18th International Conference on Economics of Grids, Clouds, Systems and Services, pp. 133–142, Virtual Event, Rome, 21-23/09/2021
DOI: 10.1007/978-3-030-92916-9_11
Project(s): ACCORDION
Metrics:
See at:
ISTI Repository | link.springer.com | CNR ExploRA
2021
Journal article
Open Access
Understanding evolution of maritime networks from automatic identification system data
Carlini E., De Lira V. M., Soares A., Etemad M., Brandoli B., Matwin S.
Recent studies on maritime traffic model the interplay between vessels and ports as a graph, which is often built using automatic identification system (AIS) data. However, only a few works explicitly study the evolution of such graphs and, when they do, generally consider coarse-grained time intervals. Our goal is to fill this gap by providing a conceptual framework for the fine-grained systematic study of maritime graphs evolution. To this end, this paper presents the month-by-month analysis of world-wide graphs built using a 3-years AIS dataset. The analysis focuses on the evolution of several topological graph features, as well as their stationarity and statistical correlation. Results have revealed some interesting seasonal and trending patterns that can provide insights in the world-wide maritime context and be used as building blocks toward the prediction of graphs topology.Source: Geoinformatica (Dordrecht) (2021). doi:10.1007/s10707-021-00451-0
DOI: 10.1007/s10707-021-00451-0
Project(s): MASTER
Metrics:
Carlini E., De Lira V. M., Soares A., Etemad M., Brandoli B., Matwin S.
Recent studies on maritime traffic model the interplay between vessels and ports as a graph, which is often built using automatic identification system (AIS) data. However, only a few works explicitly study the evolution of such graphs and, when they do, generally consider coarse-grained time intervals. Our goal is to fill this gap by providing a conceptual framework for the fine-grained systematic study of maritime graphs evolution. To this end, this paper presents the month-by-month analysis of world-wide graphs built using a 3-years AIS dataset. The analysis focuses on the evolution of several topological graph features, as well as their stationarity and statistical correlation. Results have revealed some interesting seasonal and trending patterns that can provide insights in the world-wide maritime context and be used as building blocks toward the prediction of graphs topology.Source: Geoinformatica (Dordrecht) (2021). doi:10.1007/s10707-021-00451-0
DOI: 10.1007/s10707-021-00451-0
Project(s): MASTER
Metrics:
See at:
ISTI Repository | link.springer.com | CNR ExploRA
2021
Report
Open Access
D6.3 ACCORDION system implementation (I)
Carlini E., Vailati A., Rola J., Ferrucci L., Kavalionak H., Tserpes K., Ferrann D.
This document covers the implementation activities put in place in the ACCORDION consortium to enable a smooth integration of the distributed ACCORDION platform. The first part of the document describes the three core components of the platform, while the second part describes the first integration testing performed on such components.Source: ISTI Project report, ACCORDION, D6.3, 2021
Project(s): ACCORDION
Carlini E., Vailati A., Rola J., Ferrucci L., Kavalionak H., Tserpes K., Ferrann D.
This document covers the implementation activities put in place in the ACCORDION consortium to enable a smooth integration of the distributed ACCORDION platform. The first part of the document describes the three core components of the platform, while the second part describes the first integration testing performed on such components.Source: ISTI Project report, ACCORDION, D6.3, 2021
Project(s): ACCORDION
See at:
CNR ExploRA
2021
Report
Open Access
ACCORDION D6.4 Pilot prototypes implementation (I)
Pateraki M., Ledwo? Z., Loven T., Rubaj M., Carlini E.
This deliverable describes the implementation and operation of real-life experiments from the virtual reality, multiplayermobile gaming and QoE in digital content delivery domains in order to demonstrate how the ACCORDION solution has been applied in real-world environments. It provides a report on the progress of the operational experiments' specification; the preparation of the datasets and experimentation environment to be exploited in each pilot prototype; and the indicators to be measured in order to validate both the operational (business) and technical performance of the ACCORDION platform, according to the ACCORDION pilot plans and experimentation protocol. Furthermore, this deliverable provides the guidelines for the execution and evaluation of pilots, in order to serve as proof of concept for the effectiveness of ACCORDION offerings. This is the first out of two implementation cycles that will validate the promised impact delivery.Source: ISTI Project report, ACCORDION, D6.4, 2021
Project(s): ACCORDION
Pateraki M., Ledwo? Z., Loven T., Rubaj M., Carlini E.
This deliverable describes the implementation and operation of real-life experiments from the virtual reality, multiplayermobile gaming and QoE in digital content delivery domains in order to demonstrate how the ACCORDION solution has been applied in real-world environments. It provides a report on the progress of the operational experiments' specification; the preparation of the datasets and experimentation environment to be exploited in each pilot prototype; and the indicators to be measured in order to validate both the operational (business) and technical performance of the ACCORDION platform, according to the ACCORDION pilot plans and experimentation protocol. Furthermore, this deliverable provides the guidelines for the execution and evaluation of pilots, in order to serve as proof of concept for the effectiveness of ACCORDION offerings. This is the first out of two implementation cycles that will validate the promised impact delivery.Source: ISTI Project report, ACCORDION, D6.4, 2021
Project(s): ACCORDION
See at:
ISTI Repository | CNR ExploRA