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Dynamic Reward Allocation

Overview of Reward Mechanisms​

Centive Network incorporates dynamic reward mechanisms to ensure that rewards are allocated fairly based on contributions over time. Instead of rewarding nodes solely for discrete tasks, Centive focuses on long-term, sustained contributions, providing a balanced and scalable reward structure that adapts as the network grows.

Key Reward Mechanisms​

  1. Halving Mechanism: As the network scales, rewards gradually decrease through halving events, ensuring sustainability and reducing the inflation of rewards.
  2. Linear Rewards: Fixed rewards for nodes based on the level and type of contribution, allowing for predictable income for reliable nodes.
  3. Dynamic Scaling: As the DePIN network grows, the reward pool adjusts based on network activity, balancing demand and resource availability.

Reward Distribution Models​

The Centive Network allows DePIN services to adopt various reward distribution models tailored to the specific requirements of their ecosystem. These models dictate how rewards are allocated among nodes and validators based on their sustained contributions over time.

Key Reward Models​

  1. Fixed Reward Model: Nodes receive a consistent reward for maintaining uptime and meeting contribution thresholds, regardless of the traffic or usage of the network.
  2. Performance-Based Model: Rewards are directly tied to the node’s performance, ensuring higher rewards for nodes that excel in delivering services like storage, compute, or content delivery.
  3. Staking Rewards: Nodes are rewarded simply for maintaining a contribution commitment (staking), ensuring they remain an active participant in the network.

Dynamic Rewards Based on Network Growth​

As the DePIN service scales, Centive dynamically adjusts the reward pool, ensuring fair compensation across nodes while maintaining network sustainability. Nodes that remain active during the network's expansion will benefit from more predictable rewards.

Reward Allocation​

The Centive Network uses precise mathematical models to calculate rewards for each participating node based on their contributions. Here are the key equations that govern the allocation process.

Reward Per Contribution​

This equation calculates the base reward each contribution is eligible to receive, based on the total available rewards and the contributions in the network:

Reward Per Contribution=Total RewardsTotal Contributions\text{Reward Per Contribution} = \frac{\text{Total Rewards}}{\text{Total Contributions}}

Where:

  • Total Rewards is the reward pool available for distribution during the current period.
  • Total Contributions refers to the sum of all node contributions during that period.

Node Reward​

Each node's reward is a fraction of the total rewards, proportional to its contribution:

Node Reward=ContributionnodeTotal Contributions×Total Reward Pool\text{Node Reward} = \frac{\text{Contribution}_{\text{node}}}{\text{Total Contributions}} \times \text{Total Reward Pool}

Where:

  • Contributionnode_{\text{node}} is the contribution made by an individual node.
  • Total Contributions is the sum of contributions from all nodes.
  • Total Reward Pool is the overall reward amount available for distribution in that cycle.

Customizing Distribution for DePIN Services​

Each DePIN service has unique requirements, and Centive Network allows for the full customization of the reward distribution models. This flexibility ensures that DePIN services can tailor the network's reward structure to meet the demands of their ecosystem.

Customizable Factors​

  • Reward Frequency: Some services may choose to distribute rewards daily, while others might prefer weekly or monthly distribution.
  • Performance Weighting: Services can allocate more rewards to nodes that demonstrate higher performance, such as low-latency compute or high-availability storage.
  • Task vs. Uptime Rewards: Some services may reward specific tasks (e.g., data storage, content delivery), while others reward consistent uptime.

Dynamic Scaling with DePIN Growth​

As the network grows and more nodes participate, the reward pool might dynamically adjust to maintain fair compensation. Centive Network includes mechanisms to scale the reward pool based on network activity and contribution levels.

Key Scaling Features​

  1. Growth-Based Scaling: As the DePIN service increases in users and nodes, the reward pool adapts, ensuring long-term sustainability.
  2. Traffic-Based Adjustments: During periods of high traffic or network usage, additional rewards can be unlocked to incentivize nodes to maintain high availability and performance.

Scaling​

The scaling mechanism can be governed by the following equation:

Popt=min⁡(∑L(ni,si)+1T(ni,si))P_{\text{opt}} = \min \left( \sum L(n_i, s_i) + \frac{1}{T(n_i, s_i)} \right)

Where:

  • L(ni,si)L(n_i, s_i) is the latency between node nin_i and subset sis_i.
  • T(ni,si)T(n_i, s_i) represents the throughput of processing subset sis_i at node nin_i.

The overall objective is to minimize this sum across all nodes in the network, meaning that we want to:

  • Minimize latency (i.e., reduce the time it takes for a node to receive or send data),
  • Maximize throughput (i.e., increase the rate at which the node can process data).

By minimizing the combined effect of these two factors, we achieve an optimal performance PoptP_{\text{opt}}.

This ensures that as demand grows, the network scales to meet the performance and availability needs of the service.

Dynamic Reward Allocation ensures that nodes are consistently incentivized to perform and scale their contributions in line with network demand. With these mechanisms, Centive Network provides a reliable, fair, and scalable reward structure tailored to the specific requirements of each DePIN service.