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An Empirical Smart Contracts Latency Analysis on Ethereum Blockchain for Trustworthy Inter-Provider Agreements
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As 6G networks evolve, inter-provider agreements become crucial for dynamic resource sharing and network slicing across multiple domains, requiring on-demand capacity provisioning while enabling trustworthy interaction among diverse operators. To address these challenges, we propose a blockchain-based Decentralized Application (DApp) on Ethereum that introduces four smart contracts, organized into a Preliminary Agreement Phase and an Enforcement Phase, and measures their gas usage, thereby establishing an open marketplace where service providers can list, lease, and enforce resource sharing. We present an empirical evaluation of how gas price, block size, and transaction count affect transaction processing time on the live Sepolia Ethereum testnet in a realistic setting, focusing on these distinct smart-contract phases with varying computational complexities. We first examine transaction latency as the number of users (batch size) increases, observing median latencies from 12.5 s to 23.9 s in the Preliminary Agreement Phase and 10.9 s to 24.7 s in the Enforcement Phase. Building on these initial measurements, we perform a comprehensive Kruskal-Wallis test (p < 0.001) to compare latency distributions across quintiles of gas price, block size, and transaction count. The post-hoc analyses reveal that high-volume blocks overshadow fee variations when transaction logic is more complex (effect sizes up to 0.43), whereas gas price exerts a stronger influence when the computation is lighter (effect sizes up to 0.36). Overall, 86% of transactions finalize within 30 seconds, underscoring that while designing decentralized applications, there must be a balance between contract complexity and fee strategies. The implementation of this work is publicly accessible online.
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Unraveling Ethereum's Mempool: The Impact of Fee Fairness, Transaction Prioritization, and Consensus Efficiency
Empirical evidence from live Geth and Prysm nodes shows Ethereum's post-EIP-1559 mempool still favors high fees, while high congestion correlates with longer finalization times.
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