FedOrbit: Energy Efficient Federated Learning for Orbital Edge Computing Using Block Minifloat Arithmetic

Mohammad Reza Jabbarpour; Bahman Javadi; Philip H. W. Leong; Rodrigo N. Calheiros; David Boland

doi:10.1109/tsc.2024.3478768

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FedOrbit: Energy Efficient Federated Learning for Orbital Edge Computing Using Block Minifloat Arithmetic

Mohammad Reza Jabbarpour Bahman Javadi Philip H. W. Leong Rodrigo N. Calheiros David Boland

Year: 2024 Journal: IEEE Transactions on Services Computing Vol: 17 (6)Pages: 3657-3671 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/tsc.2024.3478768

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Keywords:

Computer science Block (permutation group theory) Parallel computing Arithmetic Enhanced Data Rates for GSM Evolution Theoretical computer science Efficient energy use Artificial intelligence Mathematics

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Advanced Wireless Communication Technologies

Physical Sciences → Engineering → Electrical and Electronic Engineering

Cryptography and Data Security

Physical Sciences → Computer Science → Artificial Intelligence

Wireless Communication Security Techniques

Physical Sciences → Engineering → Electrical and Electronic Engineering

FedOrbit: Energy Efficient Federated Learning for Orbital Edge Computing Using Block Minifloat Arithmetic

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