Social-aware Federated Learning: Challenges and Opportunities in Collaborative Data Training

Abdul-Rasheed  Ottun; Pramod C.  Mane; Zhigang Yin; Souvik  Paul; Mohan Liyanage; Jason  Pridmore; Aaron Yi Ding; Rajesh Sharma; Petteri Nurmi; Huber Flores

doi:10.1109/MIC.2022.3219263

Social-aware Federated Learning: Challenges and Opportunities in Collaborative Data Training

Abdul-Rasheed Ottun, Pramod C. Mane, Zhigang Yin, Souvik Paul, Mohan Liyanage, Jason Pridmore, Aaron Yi Ding, Rajesh Sharma, Petteri Nurmi, Huber Flores

Tietojenkäsittelytieteen osasto

Tutkimustuotos: Artikkelijulkaisu › Artikkeli › Tieteellinen › vertaisarvioitu

Abstrakti

Federated learning (FL) is a promising privacy-preserving solution to build powerful AI models. In many FL scenarios, such as healthcare or smart city monitoring, the user's devices may lack the required capabilities to collect suitable data which limits their contributions to the global model. We contribute social-aware federated learning as a solution to boost the contributions of individuals by allowing outsourcing tasks to social connections. We identify key challenges and opportunities, and establish a research roadmap for the path forward. Through a user study with N = 30 participants, we study collaborative incentives for FL showing that social-aware collaborations can significantly boost the number of contributions to a global model provided that the right incentive structures are in place.

Alkuperäiskieli	englanti
Lehti	IEEE Internet Computing
Vuosikerta	27
Numero	2
Sivut	36-44
Sivumäärä	9
ISSN	1089-7801
DOI - pysyväislinkit	https://doi.org/10.1109/MIC.2022.3219263
Tila	Julkaistu - maalisk. 2023
OKM-julkaisutyyppi	A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä, vertaisarvioitu

Lisätietoja

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”

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113 Tietojenkäsittely- ja informaatiotieteet
516 Kasvatustieteet

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10.1109/MIC.2022.3219263Lisenssi: CC BY-NC-ND

Social_Aware_Federated_Machine_Learning_IEEE_Internet_ComputingHyväksytty kirjoittajan käsikirjoitus, 2,63 MBLisenssi: Muu
FeatureLopullinen julkaistu versio, 1,38 MBLisenssi: CC BY-NC-ND

Foundations of Pervasive Sensing Systems
Nurmi, P. (Principal Investigator)
01/09/2021 → 31/08/2025
Projekti: Suomen Akatemia: Akatemiahanke

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Social-aware Federated Learning: Challenges and Opportunities in Collaborative Data Training

Abstrakti

Lisätietoja

Tieteenalat

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Projektit

Foundations of Pervasive Sensing Systems

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