Lido on Polkadot Onboarding Process
Lido on Polkadot, developed in collaboration with MixBytes, is a liquid staking solution for DOT. For more detail: https://blog.lido.fi/lido-on-polkadot/
Lido on Polkadot Selection Procedures
Unlike many of the other Lido staking protocols, validators for Polkadot and it’s canary network Kusama are not chosen through a permissioned set, but through an algorithm that selects operators based off of chain-based performance that maximizes APR.
The strategy utilized includes nominating an optimal number of validators that prioritizes a higher chance of getting into the active set without decreasing average APR. According to the short and long-term simulations and as well as the rules of the Phragmén algorithm we nominate three validators from each ledger.
Slashing is then hedged by splitting stake and nominating at least two ledgers. In Polkadot's network data a stake of over 1,000 DOT ensures selection in the top 256 nominators of a validator. Therefore: 500,000 DOT / 3 Ledgers / 3 Validators ~ 55,555 DOT may be nominated per validator. Meaning for the first stage, maximum stake per ledger may be, and is limited at 100,000 DOT.
For more information about the selection algorithm read on:
Possible factors of validator underperformance:
According to research conducted by the MixBytes team for Lido on Kusama, prospective validators interested in improving their Polkadot performance would be well served to address the following causes of lower returns:
- Bad Server Configuration
- Suboptimal configuration, including inadequate hardware specs, lack of storage, memory, or network performance are among potential factors. There are recommendations given on hardware requirements in the Polkadot Wiki.
- Small Amount of Stake
- As per the Polkadot Wiki, the minimum requirement for inclusion in the active set it is equal to 1.8068 MDOT. Validators with smaller amount of stake could lead to low activity ratios and lower APRs for nominators.
- Node Oversubscription
- Validator nodes can be oversubscribed, which leads to bad APR for nominators. Per the allocation model having more than the optimal stake will cause underperformance.
- Improper Maintenance and Upkeep
- Misconfigured infrastructure or improper deployments, in addition to slashing, are among factors that may lead to lower APRs.
