Topic Life Cycle

What You'll Learn

• Understanding the complete lifecycle of topics from creation to conclusion
• Key terms and concepts that govern topic behavior and transitions
• Topic states and the conditions that determine state changes
• Economic mechanisms including weight, effective revenue, and competitiveness

Overview

The Topic Life Cycle in the Allora Network is a dynamic process that determines the stages a topic goes through from creation to conclusion. These stages are influenced by various factors such as funding, popularity, and performance metrics. Understanding the life cycle of a topic is crucial for engaging with the network.

Why Topic Lifecycle Matters

Understanding the lifecycle helps you:

• Predict topic behavior: Know when topics become active and how they evolve
• Optimize participation: Time your involvement for maximum effectiveness
• Manage resources: Allocate funding and stake strategically
• Plan strategies: Develop long-term approaches to topic engagement

Core Concepts and Terminology

Timing and Scheduling

Epoch Length

Definition: How often inferences are sampled and scored in the topic. Defined when creating a topic as EpochLength.

Practical Impact:

• Determines prediction frequency
• Affects participant workload and resource requirements
• Influences topic competitiveness through activity levels

Epoch Last Ended

Definition: The timestamp indicating when the last epoch ended, important for tracking topic activity.

Use Cases:

• Monitoring topic activity patterns
• Calculating time since last network interaction
• Planning participation timing

Ground Truth Lag

Definition: The amount of time into the future a specific inference is calculating for. Defined when creating a topic as GroundTruthLag.

Example: "Every 15 minutes, provide BTC prediction for 1 day in the future":

• 10 min: EpochLength
• 1 day: GroundTruthLag

Strategic Importance:

• Determines when predictions can be evaluated
• Affects topic activation timing
• Influences participant reward cycles

Network Coordination

Nonce

Definition: The block height at which a given outbound request from network validators is made. Nonces ensure that responses are correctly paired with their requests to facilitate accurate reward distribution and loss calculation.

Why Nonces Matter: Every topic will inevitably generate multiple worker and reputer requests, each needing to be matched with rewards for participants. The blockchain must differentiate between responses still pending rewards and those already rewarded, and reputers must identify which worker payloads to use for loss calculations. This requires uniquely identifying each outbound request.

Nonce Lifecycle: The same nonce value will be used to fulfill a complete work and reputation cycle:

1. Request Phase: A request for inferences and forecasts using a particular nonce is issued first.
2. Worker Response: Once the workers have submitted their work, the worker nonce is fulfilled and a reputer nonce is created using the same value.
3. Evaluation Phase: This reputer nonce will be processed when appropriate, triggering a reputation request.
4. Completion: When the reputers respond by submitting their work, the reputer nonce is also fulfilled, ending its cycle.

Economic Mechanisms

Topic Competitiveness

Definition: Competitiveness in the Allora Network refers to a topic's ability to attract and retain funding, stakes, and participation relative to other topics.

Characteristics of Competitive Topics:

• High Effective Revenue: A greater accumulation of revenue indicates strong interest.
• Significant Stake: Large amounts of reputer and delegated stakes signify confidence in the topic's value.

Key Insight: Both of these metrics are a function of weight, which proxies overall participation and ultimately topic competitiveness.

Effective Revenue

Definition: Effective Revenue is the measure of the impact that the total accrued revenue has on a topic's weight. It determines how much influence the revenue has on making a topic active and competitive.

Revenue Mechanics:

• Initial State: Initially, Effective Revenue equals the total amount of money a topic accrues before the first epoch.
• Active Operation: Once a topic becomes active, funds from Effective Revenue are used, impacting the ecosystem bucket.
• Time Decay: The Effective Revenue drips over time, reflecting the topic's diminishing competitiveness relative to other topics.

Ecosystem Bucket

Definition: The Ecosystem Bucket is a mechanism that distributes a portion of the total funds at a rate (approximately 10%) that decreases exponentially over time. This bucket serves as a comparative baseline for topic competitiveness. The effective revenue of a topic needs to be balanced with the ecosystem bucket to ensure the topic's competitiveness.

Bucket Mechanics:

• Fund Management: The bucket holds the money and drips at a certain rate.
• Independent Operation: This rate is uncoupled from the effective revenue drip to avoid complex calculations to determine how much effective revenue the topic actually has remaining.
• Estimation Tool: It provides an estimation but doesn't have a bearing on the total amount of money dripped from the ecosystem, ensuring financial safety.

Weight

Definition: Weight is a measure of a topic's competitiveness within the blockchain network. It is a function of the combined stake of reputers (including delegated stakes) and the topic's Effective Revenue. The weight of a topic determines its likelihood of becoming active and indirectly influences the distribution of rewards and resources within the network.

Weight Characteristics:

• Competitiveness Indicator: Higher weight signifies greater competitiveness.
• Multi-Factor Calculation: Driven by the total stake and the impact of effective revenue.
• Dynamic Nature: Changes based on participant behavior and funding levels

Topic States

Inactive State

Definition: A topic is inactive after it is created but before it becomes sufficiently funded.

Characteristics:

• Newly created topics start in this state
• No network activity or inference requests
• Waiting for sufficient funding and participation

Transition Requirements: Topics move out of inactive state when they achieve sufficient weight through funding and staking.

Active State

Definition: A topic becomes active once it is sufficiently funded. A topic is sufficiently funded once it has more than a threshold amount of weight, which is a function of the amount of:

• Reputer stake placed in the topic
• Delegated stake
• Effective revenue garnered by the topic

Funding Mechanisms: Different actors can permissionlessly fund a topic using the allorad CLI tool.

Active State Benefits:

• Topic becomes eligible for network processing
• Can receive inference and reputation requests
• Participants can earn rewards from contributions

Churnable State

Definition: A topic becomes churnable once it is:

• Active
• One of the top topics by weight (descending)
• The topic's EpochLength has passed since its inception or last epoch

Churnable Operations: Once a topic is churnable, the chain can emit worker (and eventually reputer) requests to topic workers and reputers, respectively.

Processing Timeline: Reputer requests start after a topic's GroundTruthLag amount of blocks have passed. Once worker and reputer responses are fulfilled, the topic becomes churned.

Rewardable State

Definition: A topic is rewardable once:

• It has been churned
• It has fulfilled worker and reputer requests
• It is ready to have its rewards calculated

Final Stage: This represents the completion of a full topic cycle, where all participants can receive their earned rewards.

State Transition Strategy

For Topic Creators

Activation Strategy:

1. Initial Funding: Provide sufficient effective revenue to reach active state
2. Stake Coordination: Encourage reputers to stake on your topic
3. Competitive Positioning: Monitor weight relative to other topics

For Participants

Timing Considerations:

• Workers: Join when topics are churnable for regular inference requests
• Reputers: Stake early to influence topic activation and competitiveness
• Delegators: Support topics with strong fundamentals and good management

Monitoring and Management

Key Metrics to Track:

• Topic weight and ranking among active topics
• Effective revenue levels and decay rates
• Participation levels and engagement quality
• State transition timing and patterns

Next Steps

• Learn to query topic data for lifecycle monitoring
• Understand how to create topics with optimal parameters
• Explore reputer staking to influence topic weight