Sentinel Layer

Flex is a community-owned platform that rapidly boosts dApp user growth, ensuring the value generated directly benefits the Flex community.

This layer utilizes machine learning and real-time analytics to monitor network health and optimize performance.

Node health classification:

Node health is now classified using a multi-factor model:

$$H(v)=w 1 ​ U(v)+w 2 ​ P(v)+w 3 ​ S(v)+w 4 ​ N(v)$$

where:

• U(v) is the uptime of validator v

• P(v) is the performance score of validator v

• S(v) is the stake of validator v

• N(v) is the network contribution of validator v

• w1, w2, w3 and w4 are weight coefficients

Anomaly detection:

This sentinel layer employs an Isolation Forest algorithm to detect anomalies in validator behavior:

Copy codefrom sklearn.ensemble import IsolationForest

def detect_anomalies(validator_metrics):
    clf = IsolationForest(contamination=0.1, random_state=42)
    clf.fit(validator_metrics)
    return clf.predict(validator_metrics)

We invite developers, researchers, and enthusiasts to work with our contributors for this section. Start contributing here.