Enterprise-grade blockchain platform Nuls and cross-blockchain layer-2 network Aleph have completed testing of a staking service that applies a new type of reward model.
Enterprise-grade blockchain platform Nuls and cross-blockchain layer-2 network Aleph have jointly completed testing of a new staking service dubbed staked coin output (SCO), which applies a new type of reward model.
Per a press release published on Aug. 13, the new service allows community members to stake tokens to receive tokens from other projects building on the Nuls platform. Those who own NULS tokens can choose how they want to receive rewards earned for participating in consensus as validation nodes. The release explained:
“Every NULS staker must hold 2,000 NULS because staking nodes validate blocks, while the NULS consensus nodes produce the blocks. When a staker delegates their node into a consensus node for an SCO project, such as Aleph, they can earn the alternative (Aleph) token instead of the NULS token as their consensus reward.”
During the trial, Aleph ostensibly secured over 2.1 million of staked NULS tokens, at a valuation of roughly $1.25 million.
In its latest rankings released in late July, the Chinese CCID Research Institute — an initiative of China’s Ministry of Industry and Information Technology that provides a monthly assessment of cryptocurrency projects — put Nuls in fourth place. The assessment considers crypto’s properties such as basic technology, applicability and innovation, which put together form a total value index.
As Cointelegraph reported in a dedicated analysis piece earlier this month, INDX, the Tokenized Masternode Investment Fund, calculated the top-10 proof-of-stake (PoS) blockchains based on the expected yield of their tokens. The company did this by quantifying the volatility, volume, liquidity, risk and integrity.
According to INDX, the top-10 projects were Pundi-X, IOStoken, Cosmos, Waves, Qtum, VeChain, Tron, NEM, NEO and EOS. The tokens were ordered based on expected yield as predicted by INDX’s proprietary algorithm.