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TITLE:
Co-Utile Peer-to-Peer Decentralized Computing - imarina:7474008
Handle:
https://hdl.handle.net/20.500.11797/imarina7474008
URV's Author/s:
Blanco Justicia, Alberto / Domingo Ferrer, Josep / Jebreel, Najeeb Moharram Salim / Sánchez Ruenes, David
Author, as appears in the article.:
Domingo-Ferrer, Josep; Blanco-Justicia, Alberto; Sanchez, David; Jebreel, Najeeb
Author's mail:
najeeb.jebreel@urv.cat
alberto.blanco@urv.cat
najeeb.jebreel@urv.cat
david.sanchez@urv.cat
josep.domingo@urv.cat
Author identifier
:
0000-0002-1108-8082
0000-0001-7275-7887
0000-0001-7213-4962
Journal publication year:
2020
Publication Type:
Proceedings Paper
ISSN:
9781728160955
APA
:
Domingo-Ferrer, Josep; Blanco-Justicia, Alberto; Sanchez, David; Jebreel, Najeeb (2020). Co-Utile Peer-to-Peer Decentralized Computing.
Papper original source
:
Proceedings - 20th Ieee/Acm International Symposium On Cluster, Cloud And Internet Computing, Ccgrid 2020. 31-40
Abstract:
© 2020 IEEE. Outsourcing computation allows wielding huge computational power. Even though cloud computing is the most usual type of outsourcing, resorting to idle edge devices for decentralized computation is an increasingly attractive alternative. We tackle the problem of making peer honesty and thus computation correctness self-enforcing in decentralized computing with untrusted peers. To do so, we leverage the co-utility property, which characterizes a situation in which honest co-operation is the best rational option to take even for purely selfish agents; in particular, if a protocol is co-utile, it is self-enforcing. Reputation is a powerful incentive that can make a P2P protocol co-utile. We present a co-utile P2P decentralized computing protocol that builds on a decentralized reputation calculation, which is itself co-utile and therefore self-enforcing. In this protocol, peers are given a computational task including code and data and they are incentivized to compute it correctly. Based also on co-utile reputation, we then present a protocol for federated learning, whereby peers compute on their local private data and have no incentive to randomly attack or poison the model. Our experiments show the viability of our co-utile approach to obtain correct results in both decentralized computation and federated learning.
Article's DOI:
10.1109/CCGrid49817.2020.00-90
Link to the original source:
https://ieeexplore.ieee.org/document/9139739
Papper version:
info:eu-repo/semantics/acceptedVersion
licence for use:
https://creativecommons.org/licenses/by/3.0/es/
Department:
Enginyeria Informàtica i Matemàtiques
Licence document URL:
https://repositori.urv.cat/ca/proteccio-de-dades/
Keywords:
Self-enforcing protocols
Self-enforcement
Reputation
P2p computing
Federated learning
Edge computing
Co-utility
Entity:
Universitat Rovira i Virgili
Record's date:
2024-10-12
Description:
© 2020 IEEE. Outsourcing computation allows wielding huge computational power. Even though cloud computing is the most usual type of outsourcing, resorting to idle edge devices for decentralized computation is an increasingly attractive alternative. We tackle the problem of making peer honesty and thus computation correctness self-enforcing in decentralized computing with untrusted peers. To do so, we leverage the co-utility property, which characterizes a situation in which honest co-operation is the best rational option to take even for purely selfish agents; in particular, if a protocol is co-utile, it is self-enforcing. Reputation is a powerful incentive that can make a P2P protocol co-utile. We present a co-utile P2P decentralized computing protocol that builds on a decentralized reputation calculation, which is itself co-utile and therefore self-enforcing. In this protocol, peers are given a computational task including code and data and they are incentivized to compute it correctly. Based also on co-utile reputation, we then present a protocol for federated learning, whereby peers compute on their local private data and have no incentive to randomly attack or poison the model. Our experiments show the viability of our co-utile approach to obtain correct results in both decentralized computation and federated learning.
Coverage:
Anglès
Type:
Proceedings Paper
Contributor:
Universitat Rovira i Virgili
Títol:
Co-Utile Peer-to-Peer Decentralized Computing
Subject:
Self-enforcing protocols
Self-enforcement
Reputation
P2p computing
Federated learning
Edge computing
Co-utility
Date:
2020
Creator:
Domingo-Ferrer, Josep
Blanco-Justicia, Alberto
Sanchez, David
Jebreel, Najeeb
Rights:
info:eu-repo/semantics/openAccess
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