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Federated and distributed inference leveraging sensing and communication in the...

Federated and distributed inference leveraging sensing and communication in the computing continuum The integration of sensing and communication is attracting a fervent research activity and will result in a myriad of contextual data that, if properly processed, may enable a better understanding of local and global phenomena whi... ver más

30/06/2028

UNITOV

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

UNIVERSITA DEGLI STUDI DI ROMA TOR VERGATA No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-05-04

Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:

ERC-2022-STG: ERC STARTING GRANTS

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Cerrada hace 2 años

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1 Participantes

UNITOV

1.02M€ | Lider

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Últimas noticias

01-12-2024: REDES En las últimas 48 horas el Organismo REDES ha otorgado 1337 concesiones

01-12-2024: IDAE En las últimas 48 horas el Organismo IDAE ha otorgado 4 concesiones

01-12-2024: AEI En las últimas 48 horas el Organismo AEI ha otorgado 23 concesiones

Duración del proyecto: 61 meses Fecha Inicio: 2023-05-04
Fecha Fin: 2028-06-30

Líder del proyecto

UNIVERSITA DEGLI STUDI DI ROMA TOR VERGATA

TRL 4-5

Presupuesto del proyecto 1M€

Descripción del proyecto The integration of sensing and communication is attracting a fervent research activity and will result in a myriad of contextual data that, if properly processed, may enable a better understanding of local and global phenomena while increasing the quality, security, and efficiency of our ecosystems. The computing continuum offers a timely and unique solution for processing such a massive volume of sensed data, as it provides virtually unlimited and widely distributed computing resources. Nevertheless, the deployment of data analysis at the edge or in the cloud has many implications regarding latency, privacy, security, and data integrity. As we learn how to sense ubiquitously and we build a tool able to handle the sensed data, the greatest challenge is to understand how and where to process them. The purpose of this project is the development of a pioneering framework to guide the design of federated and distributed inference systems, leveraging sensing and communication and harnessing the computing continuum. The framework will build on: (i) the definition of statistical and mathematical models for the sensed data, which capture the complex and interrelated phenomena underpinning sensing and communication systems, with different levels of integration; (ii) the development of cloud-native inference algorithms, mainly distributed and parallelized, with scalable complexity that can be adapted to dynamic performance requirements; (iii) the design of orchestration strategies to guide the flexible deployment of the inference process at the edge and in the cloud with a dynamic allocation of the computing resources. The aim is to overcome the paradigmatic accuracy-complexity trade-off that has driven distributed inference for decades, leading to a paradigm shift that encompasses multi-level performance indicators beyond accuracy, including latency, integrity, privacy, and security aspects and how these impact the confidence on the inferred phenomena.

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