Node operators process transactions and receive token incentives. These independently owned high-spec node machines around the world are connected via Internet Computer Protocol (ICP), creating a self-sovereign network not reliant on any cloud services. Advanced cryptography allows any application or service to be run on the network in a decentralized manner via smart contracts.

The Internet Computer is a decentralized cloud blockchain, where apps can be built fully onchain, using AI, or by coding. Try caffeine.ai & icp.ninja.

ICP tokenholders own and govern the protocol. They currently take (burn) all of the total transaction fees paid by users (revenue). ICP Holders can stake their ICP on the Network Nervous System (NNS), an advanced fully on-chain DAO that facilitates liquid democracy. Staking ICP allows users to submit proposals, vote on proposals, and earn rewards for their participation in governance. Internet Computer's investors include Polychain, Scalar Capital, Amino Capital, etc.

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Internet Computer

# Internet Computer Cycles burn rate Methodology

## 1. Overview

The Internet Computer cycles burn rate metric measures the daily average rate at which cycles are consumed (burned) on the Internet Computer network. Cycles are the computational units used to pay for computation and storage on the Internet Computer blockchain. This metric provides insight into network activity and resource consumption by tracking how many cycles are being used on average each day.

## 2. Data sources

The calculation relies on a single primary data source:
- **Internet Computer network statistics**: Daily statistical data scraped from the Internet Computer protocol's API endpoints, containing aggregated network metrics including cycle consumption rates
- **Time-series data**: JSON-formatted daily statistics with insertion timestamps for data quality and deduplication purposes

## 3. Step-by-step calculation

### Component A: Raw data extraction and parsing
- **Purpose**: Extract daily cycle burn rate statistics from scraped Internet Computer network data
- **Logic**: The system processes JSON-formatted statistics from the Internet Computer scraper, extracting data from nested `daily_stats` arrays. Each record contains a `day` timestamp field and a `cycle_burn_rate_average` numeric value representing the average cycles burned on that specific day. The extraction process parses these JSON values and converts them to appropriate data types for further processing.
- **Key fields**: `day` timestamp converted to timestamp format, `cycle_burn_rate_average` converted to numeric format, and `inserted_at` timestamp tracking when the data was scraped

### Component B: Data deduplication and quality control
- **Purpose**: Handle potential duplicate records from multiple scraping operations and select the most recent data for each day
- **Logic**: Since the scraper may collect statistics multiple times for the same day, the system applies deduplication logic using window functions. Records are partitioned by the day timestamp and ranked by insertion time in descending order, ensuring that only the most recently scraped data for each day is retained. This prevents double-counting and ensures data accuracy.
- **Key fields**: Row numbering based on `inserted_at` timestamp with only rank 1 records (most recent) being selected for each day

### Final aggregation
- **Combining components**: The processed daily cycle burn rate data flows through a standardized metric finalization process that applies consistent schema formatting and metadata fields
- **Currency conversion**: Not applicable as cycles are protocol-native computational units, not currency-denominated values  
- **Time aggregation**: Data is already aggregated at the daily level from the source, with the finalization process applying a 'fill zeros' strategy to handle any gaps in the time series by inserting zero values for missing days
- **Final calculation**: The metric value represents the daily average cycle burn rate as provided by the Internet Computer protocol statistics, with additional metadata fields for chain identification, business categorization, and version tracking applied through the finalization macro

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Average number of cycles burned per second.

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Cycles burn rate

Cycles burn rate

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