Real-time difficulty adjustment is a mechanism in some blockchain protocols that automatically changes the computational effort required to mine a new block. This adjustment occurs dynamically, often after each block or a small number of blocks, to maintain a consistent block production rate despite fluctuations in network hash power. It ensures the network remains secure and functional by preventing a single entity from dominating block creation or slowing down transaction processing. This adaptive feature is vital for the stability and predictability of proof-of-work blockchains.
Context
Real-time difficulty adjustment is a core component of several proof-of-work blockchains, ensuring their operational stability and resistance to external influences. Discussions often highlight its role in maintaining network security and preventing mining centralization. Future innovations in consensus mechanisms may incorporate more sophisticated real-time adaptive parameters to enhance network responsiveness.
A new Deep Reinforcement Learning model dynamically selects validators and adjusts difficulty, fundamentally solving the scalability-latency trade-off.
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