Adaptive Consensus Mechanisms for Smart Contract Optimization - Tsudzenko, Yurii; Pavlyshenko, Bohdan (Комп’ютерне моделювання та інформаційні технології, 2026)
The paper proposes an adaptive hybrid consensus model for a social platform blockchain system that integrates PoS, DPoS, and PoA. The model provides dynamic adjustment of consensus modes depending on the Download network and transaction type, and also takes into account the reputation of validators to increase the reliability of verifications. This approach will help to increase throughput, reduce transaction processing time, and optimize energy consumption with classical mecha nisms. The approach allows for an effective combination of performance and security of blockchain systems, and promising areas for further research include the use of machine learning for load forecasting and integration into hybrid blockchains with cross-chain smart contracts.