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Federated and distributed inference leveraging sensing and communication in the computing continuum

Project description

When sensing and communication merge

Devices such as traffic cameras and wearable sensors collect data to build smarter cities and safer systems. However, a difficult question arises: should the data be processed at the network edge, near the device, or in distant cloud servers? The ERC-funded FIND-OUT project aims to answer this question. It will create a blueprint for these systems and develop a framework that allows networks to decide how to split tasks across the computing continuum. The project also uses new mathematical models and cloud algorithms to manage these decisions in real time. This approach is designed to redefine how we build smart systems.

Objective

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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Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

(opens in new window) ERC-2022-STG

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Host institution

UNIVERSITA DEGLI STUDI DI ROMA TOR VERGATA
Net EU contribution
€ 1 019 000,00
Address
VIA CRACOVIA 50
00133 Roma
Italy
Region
Centro (IT) Lazio Roma
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 1 019 000,00

Beneficiaries (1)