Communication cost refers to the resources expended for data transmission and reception within a distributed system. In blockchain networks, this includes the bandwidth and computational power necessary for nodes to exchange transaction data and consensus messages. High communication costs can restrict scalability and increase operational expenses for network participants. Optimizing these costs is crucial for efficient decentralized network operation.
Context
The communication cost is a central topic in scaling solutions for blockchain, particularly in sharding and layer-2 protocols. Researchers are actively pursuing methods to reduce data propagation overhead, which directly impacts transaction throughput and latency. Future advancements aim to minimize these costs to support broader adoption of decentralized applications and services.
This optimistic consensus design fundamentally challenges the quadratic communication lower bound, enabling optimal scalability for distributed state machine replication.
A new Zero-Knowledge Proof of Training (ZKPoT) consensus mechanism leverages zk-SNARKs to validate machine learning model contributions privately, resolving the efficiency and privacy trade-off in decentralized AI.
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