Clustering

Definition

Groups identical/similar data points together and at the end of each aggregation window outputs the value corresponding to the heaviest cluster assuming sufficient weight (x% of total validators stake)

Default parameters:

• Aggregation window of one block

• Sufficient stake is 67% of the total validators stake

Rationale and Properties

• Proper in cases where we expect the same result among all data validators . For example, fetching from a single and stable source or performing the same computation

• Final result is strictly backed by most validators or stake weight (assuming 67% requirement)

• Given a relative majority submitting accurate reports, iInaccurate reports do not affect final result (as deviant or malicious reports fall into smaller clusters)

• Efficient online implementation and possible optimizations (Cleaning small clusters occasionally etc)

Limitations

• Storage inefficiency in worst case scenarios (ccurs when reports have high variance)

• Limited effectiveness with volatile data—when values change rapidly, multiple small clusters form instead of a clear majority, making it difficult to reach consensus.