Rhythm's BlockBeats: On October 1st, Ethereum's two-tier expansion solution SKALE announced that it had entered the second phase of its main network, with a total lock-up volume of $80 million. The SKALE ecosystem now has 4,000 participants in 90 countries around the world, with 46 node operators operating 135 validation nodes.
SKALE Labs lianchuang and CEO Jack O 'Holleran, said: "it is very important for distributed ecological progress. Participation a validation of SKALE network and client like to participate in the DeFi liquidity mining, users only need to pledge tokens can obtain network distribute rewards. Different is, however, participate in liquidity is dig in for the application to provide liquidity, participate in SKALE network pledge is, however, in ensuring the safety of the PoS network."
With ethereum's Gas charges soaring and network congestion growing, the entire ethereum ecosystem needs a complete solution. The second phase of SKALE's main network provides a new platform for the sustainable development of ethereum ecology. SKALE operates on a body deep inside the body, and is therefore perfectly compatible and cohesive with ethereum's main network. Since transaction fees and network congestion are no longer an issue in the SKALE network, developers can move mass-used apps up the chain.
The PoS consensus protocol for SKALE network applications incorporates the concept of Shared security pool and implements the randomly selected verification node verification to further ensure network security. At the same time, SKALE transforms a service node into 128 virtual child nodes in the form of virtualization. This design expands the node pool and gives clients the opportunity to participate in the network.
The SKALE network is a two-tier expansion solution that is fully compatible with the ethereum host network. Its block time reaches sub-second level, each SKALE chain throughput can achieve 2000Tps, and can deploy full-state intelligent contract, support decentralized storage, implementation of Rollups scheme and EVM machine learning.
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