A Lifecycle Cost Analysis of Smart-Contract-Coordinated Federated Learning Marketplaces

The evaluated cost structure is amortizing because substantial deployment expenditure is paid per hired trainer only at setup, while recurring expenditure is markedly smaller and becomes diluted over the federation lifetime.

Source: E012, E014

Lifecycle-level cost decomposition and amortization analysis provide a basis for assessing decentralized coordination architectures beyond isolated transaction measurements.

Source: E023

The evaluated configurations reached statistically indistinguishable final accuracy, indicating preserved learning outcomes within this experiment.

Source: E002

Local training remained the dominant runtime component across tested federation sizes, while coordination overhead stayed limited and matching grew sublinearly.

Source: E018, E021

The evaluated cost structure is amortizing because substantial deployment expenditure is paid per hired trainer only at setup, while recurring expenditure is markedly smaller and becomes diluted over the federation lifetime.

Source: E012, E014

Lifecycle-level cost decomposition and amortization analysis provide a basis for assessing decentralized coordination architectures beyond isolated transaction measurements.

Source: E023

The study asks whether marketplace operating cost is chiefly a fixed deployment burden or a recurring burden that accumulates through training.

Source: E010

The evaluated design joins compatible smart contracts with decentralized storage and a federated-learning framework.

Source: E030

Coordination rules are executed autonomously through the contract layer.

Source: E005

The lifecycle separates a per-trainer setup stage from a training loop that recurs across communication rounds.

Source: E028

Settlement proceeds asynchronously through a layered transaction arrangement with periodic base-layer commitments.

Source: E005

The implementation uses local contract execution and local decentralized storage to provide deterministic execution and controlled artifact availability.

Source: E026

The baseline is a conventional federated-averaging deployment without blockchain interaction or decentralized storage.

Source: E006

The intermediate configuration retains contract coordination while substituting direct deterministic hashes for storage uploads, whereas the full configuration includes both coordination and decentralized storage.

Source: E006

The experiments use a compact image-classification workload and federated averaging, with separate ablation and scaling settings and repeated randomized runs.

Source: E006, E016

The evaluation covers lifecycle gas use, round execution time, final predictive performance, matching scalability, and deployment-cost amortization.

Source: E023, E032

The measured fixed setup component for the experimental federation is reported in the supporting quantitative record.

Source: E013

The recurring communication-round component for that federation is reported separately in the supporting quantitative record.

Source: E004

Final predictive results were reported for the baseline, coordination-only, and full configurations after the evaluated training schedule.

Source: E003, E011

The evaluated configurations reached statistically indistinguishable final accuracy, indicating preserved learning outcomes within this experiment.

Source: E002

Lifecycle gas consumption per hired trainer was concentrated in initial deployment, especially participant onboarding and offer acceptance.

Source: E012

For the experimental federation, the amortization knee is defined where average round cost reaches a specified multiple of the long-run recurring cost.

Source: E019, E033

Reported average round durations were closely aligned across the evaluated configurations.

Source: E025, E027

Local training remained the dominant runtime component across tested federation sizes, while coordination overhead stayed limited and matching grew sublinearly.

Source: E018, E021

Across the tested range of hired trainers, the amortization knee remains bounded and approaches a limiting value under the measured regime.

Source: E001

The amortization model expresses average operating cost by separating fixed setup expenditure from recurring round expenditure over the operational horizon.

Source: E017, E029

The amortization finding assumes the measured offer-availability regime at acceptance, and alternative matching regimes were not evaluated.

Source: E007, E024

Accuracy preservation is limited to the compact workload and coordination task evaluated, rather than establishing generality across task difficulty or model scale.

Source: E007, E024

Monetary cost depends on the target network, and local storage results do not include variability associated with public storage gateways.

Source: E026

The evaluated cost structure is amortizing because substantial deployment expenditure is paid per hired trainer only at setup, while recurring expenditure is markedly smaller and becomes diluted over the federation lifetime.

Source: E012, E014

Lifecycle-level cost decomposition and amortization analysis provide a basis for assessing decentralized coordination architectures beyond isolated transaction measurements.

Source: E023