Reading | Phala Network Economic Paper Preview
This article is a preview of Konstantin Shamruk’s upcoming “Phala Economics White Paper V0.9”. It will also be submitted to the Khala Network Council as a proposal, and will be launched after the democratic referendum is passed.
The overall economic design is built to address these points:
1. Support Phala Network’s trustless cloud computing architecture
- Consensus-Computation Separation
- Linearly-scalable computing workers (100k order of magnitude number of miners)
2. Incentivize miners to join the network
- Ensure payment for power supplied irrespective of demand, especially at network bootstrap
- Subsidize pool with 70% of the initial supply
- Bitcoin-like budget halving schedule
3. Application pricing
4. On-chain performance
The following details some key elements of the economic model.
Value Promise (V)
- A virtual score for an individual miner representing value earned which is payable in the future, to motivate miners to behave honestly and reliably
- Equal to the expected value of the revenues earned by the miner for providing power for the platform
- Changes dynamically based on the miner’s behaviors and the repayment of Rewards
- Mining honestly: V grows gradually over time
- Harmful conduct: punished by reduction of V
A Miner will run a Performance Test and stake some tokens to get the initial V:
- S is the miner stake; a Minimum Stake is required to start mining. Stake can’t be increased or decreased while mining, but can be set higher than the Minimum.
- C is the estimated cost of the miner rigs, inferred from the Performance Test.
- ConfidenceScore is based on the miner’s SGX capabilities.
Params used in simulation:
- ConfidenceScore for different Confidence Levels
A performance test measures how much computation can be done in a unit time:
The table is based on the version while writing of this doc and is subject to changes.
The performance test will be performed:
- Before mining to determine the Minimum Stake
- During mining to measure the current performance, and to adjust the V increment dynamically
- P — Performance Test score
- k — adjustable multiplier factor
Locked state $PHA token can also be used for mining staking, e.g., Khala Crowdloan reward.
- ϕ is the current PHA/USD quote, dynamically updated on-chain via Oracles
- PP is the initial Performance Test score.
- In the early stages, we are compensating the equipment cost C with a higher Value Promise.
General mining process
Each individual’s V is updated at every block:
When a miner gets a payout w(Vt) , they will receive the amount immediately in their Phala wallet. The payout follows Payout Schedule and cannot exceed the Subsidy Budget.
- Increased by ΔVt if the worker keeps mining
- Decreased by w(Vt) if the miner got a payout
- Decreased according to the Slash Rules if the miner misbehaves
Finally, once the miner decides to stop mining, they will wait for a Cooling Down period δ. They will receive an one-time final payout after the cooldown.
*δ=blocks equivalent to 7 days
Update of V
When there’s no payout or slash event:
TBD: define the equation of adjusted ΔVt based on the current performance test score Pt
In order to stay within the subsidy budget, at every block the budget is distributed proportionally based on the current Miner Shares:
where B is the current network subsidy budget for the given payout period. Whenever w(Vt) is paid to a miner, his V will be updated accordingly:
Share represents how much the miner is paid out from VV. We expect it will approximate the share baseline, but with minor adjustment to reflect the property of the worker:
Heartbeat & Payout Schedule
In any block t, if the Miner’s VRF is smaller than their current Heartbeat Threshold γ(Vt), they must send the Heartbeat transaction to the chain, which will update the on-chain record of their Value Promise and send a Mining Reward w(Vt)to their reward wallet:
If they fail to send the Heartbeat transaction to the chain within the challenge window, the update of their value promise will be:
and their status is changed to unresponsive, and they will get repeatedly punished until they send a heartbeat, or stop mining. The slash amount h is defined in the Slash section.
The target is to process around 20 heartbeat challenges per block. The heartbeat challenge probability γ(Vt) will be adjusted to target this number of challenges.
The slash rules for miners are defined below. Note that currently only the Level 1 slash is currently implemented.
When a miner chooses to disconnect from the platform, they send an Exit Transaction and receives their Severance Pay after δ blocks.
After the cooling down period, the miner gets their final payout, representing the return of the initial stake. However, if Vt goes lower than the initial Ve, the miner will get less stake returned as a punishment:
Note that the following constraint must hold to avoid arbitrage:
In essence, the miner will receive their initial stake back, unless they have been heavily slashed for misbehavior.
Phala Network tackles the issue of trust in the computation cloud.
This blockchain is a trustless computation platform that enables massive cloud processing without sacrificing data confidentiality. Built around TEE-based privacy technology already embedded into modern processors, Phala Network’s distributed computing cloud is versatile and confidential. By separating the consensus mechanism from computation, Phala ensures processing power is highly scalable but not wasteful. Together, this creates the infrastructure for a powerful, secure, and scalable trustless computing cloud.
As a member parachain of the Polkadot cross-chain ecosystem, Phala will be able to provide computing power to other blockchain applications while protecting the data layer, enabling possibilities like privacy-protected DeFi trading positions and transaction history, co-computing DID confidential data, developing light-node cross-chain bridges, and more.
On-chain services currently being developed on Phala Network include Web3 Analytics: high-performance smart contracts from Phala to enable highly concurrent mass data analytics with privacy, paving the way for an alternative to Google Analytics that inherently respects individual confidentiality.