Data sourcing

At the heart of Lumina is a decentralized data collection system composed of an independent network of Feeders, in charge of sourcing data and feeding it into the Lasernet chain.

Key components

# Feeders

Feeders are nodes that fetch granular market data directly from decentralized exchanges (DEXs) and centralized exchanges (CEXs). These Feeders are responsible for sourcing trade ticks and pushing them to Pods—smart contracts running on DIA’s Lasernet—at configurable intervals i.e 30 seconds. If during those time intervals more than one trade takes place, each Feeder will generate a median (price) value for each asset per exchange, using all trade data.

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Key benefits

• Crypto-Economic Security: DIA Lumina relies on a decentralized network of nodes (Feeders) backed by staked assets, ensuring the integrity and reliability of data sourcing. Both operators and delegators contribute to the system’s security and are rewarded for their participation. Malfunctioning nodes get slashed, losing their staked assets and reputation.

• Cryptographic Security: Lumina incorporates advanced cryptographic techniques such as zero-knowledge proofs to ensure data verifiability. The system is designed to accommodate future cryptographic advancements, ensuring long-term security and flexibility.

• Any Asset from Any Chain: Lumina’s data sourcing framework is built on first-party scrapers. This allows DIA Lumina to provide feeds for any asset on any chain, with data sourced directly from where it is generated while maintaining transparency and bypassing reliance on third-party data providers.

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Staking Incentives

To encourage honest behavior, oracle feeders will be rewarded for successful operations and penalized for harmful actions. These incentives ensure that dishonest behavior is punished and becomes economically unviable.

Rewards and penalties will primarily be based on uptime and accuracy, measured by the timeliness of updates and the accuracy of prices compared to other feeders. Initially, feeders will gather the last traded price for assets from centralized exchanges (CEXs). For decentralized exchanges (DEXs), we will use trade simulation-based price estimation, which simulates trades to obtain current exchange rates. This approach ensures more accurate pricing, particularly for assets that are infrequently traded.