iFogSim partially covers IoT simulation objectives but requires workarounds for non-canonical architectures that bias results such as latency and path computation; the paper maps gaps and proposes source-code fixes.
and Iranmanesh, M
2 Pith papers cite this work. Polarity classification is still indexing.
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Extends Flower framework with FedSaSync semi-asynchronous strategy, claiming reduced idle time versus synchronous baselines in heterogeneous settings.
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Source-Code Analysis of iFogSim for Simulating Distributed IoT Architectures: Coverage, Challenges, and Enhancements
iFogSim partially covers IoT simulation objectives but requires workarounds for non-canonical architectures that bias results such as latency and path computation; the paper maps gaps and proposes source-code fixes.
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Semi-asynchronous Federated Learning in Flower: Framework Extension and Performance Assessment
Extends Flower framework with FedSaSync semi-asynchronous strategy, claiming reduced idle time versus synchronous baselines in heterogeneous settings.